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Michael
Nitzsche
Cambridge, MA
Hatton Research Group - Massachusetts Institute of Technology
My work is in electrochemically driven carbon capture for decarbonizing heavy industry, and I am hoping to start a company to mitigate hard-to-abate emissions. I'm passionate about sustainability and the environment, and my career goal is to maximize my negative carbon footprint.
Our technology uses an electrochemically mediated amine regeneration process (EMAR), where plating and stripping of copper ions into an amine solution drives capture and release of CO2. Initial work on EMAR began in the Hatton Lab nearly a decade ago. Several students and postdocs have worked on the technology, with patents and papers ranging from fundamental chemistry to system-level design, and demonstrations reaching the 50 gCO2/day scale for 100 hours. Michael and I have continued to develop the technology in the lab, with our recent IP advances focused on de-risking and scalability for commercialization.
On the technical side, de-risking efforts will focus on understanding and enhancing long-term stability, particularly in the presence of oxygen and improving chemical kinetics, as these can still be done at the bench scale. Towards commercialization, our primary goal is to improve our system-level technoeconomic models with benchmarking against existing carbon capture technologies to assess commercial viability and find our best market fit.
Neal
Amin
San Francisco
Stanford University (for now!) I’m leaving to go full time on founding Collage Biosciences later this year.
I am developing RNA splice-modifying therapeutics for neurodegeneration and the aging brain. By developing splice-sequencing technology and an ML-driven computational biology approach, we are building the first atlas of brain splicing across the lifespan that will power our target detection platform. By applying my organoid screening platform and in vivo preclinical models, we will improve neural health and develop our lead candidate - a antisense oligonucleotide drug modifier of neurometabolism. We are aiming for first in man clinical trials within 5 years.
I’ve spent the last 16 years studying medicine and neurobiology through my physician scientist training. My work in RNA processing the nervous system and development of organoid technology has lead to publications in nature, cell, science, nature medicine, neuron and nature neuroscience and patents from Stanford and the Salk Institute. This company idea has been honed over this time and is the culmination of my scientific obsessions and drive to improve brain health, prevent disease, and challenge conventional biomedical wisdom around what is possible.
My biggest current risk is lack of time with my full time faculty position at Stanford. I am leaving next month to stop dreaming and start building as full time founder. Next is honing the clinical stage strategy and mapping an FDA approval plan that will guide our efforts. I will actively fundraise to continue supporting my current bioinformatics tram that is transitioning from academia. Concurrently I will establish a lab and develop technology for our first patents around splicing sensitive RNA sequencing. The bioinformatics team will begin lead candidate identification efforts with our available data while we obtain aging and disease brain samples to generate proprietary data.
Joseph
Mooney
Cambridge, MA
Postdoctoral Associate
I develop low-cost decentralized water technologies, using the moisture in the air and sustainable heat (solar waste or waste) to produce this water. We can operate in the most arid of climates in either a passive or active manner. I see myself building a device to be ready for pilot in the next year, looking for immediate funding to incorporate, establishing myself in a climate tech hub, hiring my first employee, and developing a plan for the pilot. I would envision my first customer within the agriculture space (small-scale crops or hydroponics).
I have worked with researchers to demonstrate record water uptake performance with our materials. I have developed three technologies/ devices (two passive and one active, and two at different scales), tested two on the roof of MIT and show record amounts of water produced, and tested one device in the driest non-polar desert on Earth (the Atacama desert) and also shown record amounts of water produced. Our next mission is to fabricate it at a larger scale. I have done the geospatial mapping of weather data to show a country's need for the technology. I have also tried to build myself as an entrepreneur by attending internal accelerators.
There is a market validation risk (i will test a full scale device and couple it to a small set up driven by the customer), there is a risk in making our device autonomous and powered by a small PV (this will be de-risked by running a device for 2-weeks off the grid and recording data), there is risk in securing funding (I will start approaching investors, working with academic collaborators and attending start-up competitions to generate funding), there is risk in terms of my current visa expiring in February 2025 (once I secure the funding I will apply for a GEIR visa in UMass or something similar, I will also apply for a green card EB1-12, if I cannot get a visa on time I will convert to a H1-B research specialist in my lab) and funding would help support spin out and a visa, there is a risk in not convincing the customers/ investors (I would love to work with 50 years to build myself to communicate the technology most effectively and do due diligence in identifying that first paying customer).
Zewen
Zhang
Mountain View
Apple
leverage data to systematic design battery materials and manufacturing
understand the gap between data-driven insights and experimental results
Chao
Cao
Boston
Carnegie Mellon University / Boston Dynamics AI Institute
Autonomous mobile robots that are useful in people's daily life
Building a physical robot and surveying people on how the robot could be useful
Talk to potential customers and users to determine if there is an actual need and market for the robot.
Sulin
Liu
Boston/New York
MIT
I work on AI and its applications for science domain. My vision is to build AI tools designed to accelerate the screening and proposal of new drug/material development, using the idea of AI agent interacting with multiple AI models.
A novel AI method and experimented it on standard image/text benchmarks.
Figure out its best use case for science discovery and the best product-market fit.
Aditya
Venkatramani
Boston
Harvard University
I am building a device to measure tissues' RNA/ DNA/ protein content at single-cell resolution with genome-scale sensitivity. My vision is to enable the creation the usage of genomic data to understand organs and organisms in their native or abnormal states.
I have built a proof-of-concept machine that can measure RNA content with high spatial resolution and with the promise of high genomic-scale sensitivity. It also has the promise of scaling up the number of cells we can measure but that is yet to be demonstrated.
On the scientific front, I am working on scaling up to make sure this will work better than existing tools in the market. On the spin-out front, I am working on figuring out ways around IP conflicts. I am also exploring avenues outside of building a device company such as thinking about applications in precision medicine or working with tissue banks. This is very much work in progress and want to try to stay true to my bigger vision.
Nils
Burger
Boston, MA
Chouchani Lab, Dana-Farber Cancer Institute and Harvard Medical School. Previously, Murphy Lab at the University of Cambridge, UK
Sleep is a major determinant of longevity and protective against metabolic, cardiovascular, and age-related diseases. However, little is known about the molecular mechanisms underlying sleep. I propose that metabolic adaptations during sleep regulate cellular functions and thereby convey health promoting and pro-longevity effects. Defining the metabolic principles of sleep will provide us with a unique therapeutic handle which we can leverage to develop a new class of therapeutics to target and activate the pro-health mechanisms of sleep. Harnessing sleep will revolutionize the way we age.
I have recently completed my work to generate a global atlas mapping the evolutionary trajectory of all 260.000 human protein cysteines across close to 3000 species. I further enriched the dataset with structural data and additional information to establish a unique profile for each cysteine which informs on their reactivity and regulatory potential. I am currently working full time to identify cysteine targets that correlate with requirement for sleep across species, which will be subsequently validated to identify their functional role in mediating the health promoting effects of sleep. Following biological validation, covalent drug screens will be performed for high value cysteine targets aiming at the development of potent and selective modulators of target pathways.
The first critical step will be to identify regulatory cysteine targets which correlate with the requirement for sleep. Alternatively, conserved cysteines (independent of sleep requirement) might be differentially regulated depending on sleep requirement which would necessitate in vivo studies to identify regulatory signatures in form of cysteine modifications, which is substantially more laborious.
Next, in vivo work in rodent models will be required to establish sleep dependent regulation of identified targets.
Further validations will need generation of mutant animals.
Assaf
Magen
San Diego, CA
Voyant Bio
I want to build a system to enable every cancer patient (and beyond) to reach a cure instead of prolonging lifespan in just a few months with current treatments.
I have done research in the immuno-oncology space and developed a prototype platform to discover how immune cells talk and drive response or resistance to current therapies.
Partner with clinics to get patient tissue
Complement the team with advisors and early employees on the diagnostic/therapeutic R&D and commercialization
Generate additional validation/discovery data
Lay the foundations for partnering/selling to healthcare insurance or pharma companies
Raise dilutive and non-dilutive funding
Jase
Gehring
Berkeley, CA
Streets Lab, UC Berkeley (previous Latent Labs, Arcadia Science, UW, Caltech, UC Berkeley)
I develop advanced technology to make discoveries in biology. I have always seen biology as a data-limited field, and now I'm looking to combine generative modeling with high-throughput and pooled experiments, using cutting-edge data and modeling to bring new therapies into existence.
I'm implementing and modifying deep generative models for protein design. I have developed advanced experimental and computational methods for single-cell and spatial genomics, and I am currently developing a next-generation spatial genomics method that could screen computationally designed biologics at scale. I am exploring application areas for biologics, but I have not yet settled on a target disease or therapy. I have crossed off small molecule therapeutics in favor of proteins, and I'm focusing in on a viable screening and development cycle for designed protein therapeutics.
1. Establish computational pipeline for protein design
2. Proof of concept experiments for next-generation spatial omics
3. Hone in on target disease and therapeutic strategy
4. Integration: articulate a development cycle that applies generative modeling and laboratory screening to the chosen therapeutic area
Jason
Zhang
Boston, MA
PhD Candidate in Biological Engineering at MIT
My research is focused on HIV vaccines and cancer immunotherapy. I wish to build cutting-edge biotechnologies that harness our immune system to improve human health.
I have done extensive market and background research and put together a pitching deck.
I will talk with more expertise in various fields to gauge people's interest and skepticism.
Sebastian
Kenny
Seattle
Baker Lab, Institute for Protein Design
I design proteins to perform novel functions that our current therapeutic strategies can't achieve. I envision a world where no diseases are not treatable.
I have shown proof of principles the therapeutic strategy I am trying to commercialize
I filed the patent for this strategy through the university's tech commercialization office. I am planning to develop the business model and start the licensing process during the 5050 program timeline.
Kwat
Medetgul-Ernar
Stanford & Teton Valley, Wydaho (WY + ID)
Stanford MD-PhD Program with PhD in Biophysics at Mark Davis Lab
Translate our new blood test into the clinic, establishing the new common blood test.
Developed it and tested it across multiple immune conditions
I want to attend as many 50Y events as I can and learn as much. I want to ship this test for everyday people (immune health, inflammation, and other nonclinical uses) so that I can start selling if I need to - and gather data.
Mariëlle
van Kooten
Palo Alto, CA
Stanford University
I am on a mission to reboot the human powerplant. Advances in omics measurements, mRNA technology and genome engineering offer unprecedented precision and potential to deliver specific genetic instructions to cells to restore or enhance function. I am an engineer, and these cutting-edge tools make it possible to directly target and repair mitochondrial dysfunction, offering a real opportunity to redefine human health span and lifespan.
Structure: We set out to build Powerhouse Biology as a Focused Research Organization, a concept that we applaud but one that is simultaneously complex to achieve in a controllable manner – the concept heavily depends on philanthropy - and to build up in a milestone-based approach. Therefore, I recently pivoted and am now shaping Powerhouse Biology into a to-be commercial entity. Science: The initial aim was to move the mtDNA into the nuclear genome. Since, I have shaped this aim into concise and commercially exciting milestones and in R&D, focus on these milestones. Viability: I am currently focusing on generating IP.
I am currently focusing on generating IP, which on a day to day basis involves research and making good decisions in research. In addition, I want to further explore a plan B re IP should the science not work out, settle on a co-founder, and shape the business case.
Kyungyong
Seong
Berkeley, California
Ksenia Krasileva lab at the University of California, Berkeley
Immunotherapy in plants! Pathogens evolve faster than plants, and the probability of disease increase in mono-cultural agricultural sites in every season. Current technology requires five to ten years to identify functional plant immune receptors in nature. These immune receptors can be compromised within a few years by pathogen evolution in the fields.
My work aims to bypass long immune receptor screening process and to rapidly design synthetic receptors with our own hands that can recognize evolving pathogens in the field. If successful, durable genetic resistance will be feasible, as it is difficult for pathogens to overcome resistance when there are many functional immune receptors! Durable resistance means extended lifetime of elite crops, improved quality and shelf life of plants, and more opportunities to enhance other traits. This advancement will be important as we will need to deal with global warming and rapid changes in pathogen pressure in fields.
The entire goal of the project can be divided into three steps: 1) selecting disease-causing molecules to design my immune receptors for, 2) building a workflow for immune receptor design and 3) expanding to diverse plant-pathogen systems and scaling up.
In one of my publications (Seong et al., 2023, Nat. Microbiology), I used protein structures predicted with AlphaFold and revealed an important evolutionary pattern of how pathogens evolve their disease-causing molecules. Pathogens preferentially rely on a certain group of pathogen molecules to cause diseases, and they can be important targets for immune receptor design.
In a recent preprint (Seong et al., 2024), I redesigned an existing immune receptor to recover its compromised function and allow it to recognize mutated disease-causing molecules. Unlike traditional approaches that rely on experimentally determined structures, I was able to engineer the receptor only relying on simple molecular biology and computational modeling. This was really a great opportunity to think about protein design, molecular biology and modeling. I believe if I were to tackle similar problems, I would be much faster knocking them down.
Unfortunately, I am teaching from 12 to 5 on Monday, Wednesday and Thursday this semester. It is a bit tricky to make meaningful progress in my current situation. Still, I plan to test my engineered mutants in a homologous system (wheat) and transgenic plants in the field to validate their functions.
I am setting up a pipeline to try more difficult immune receptor design challenges. I have a group of pathogen molecules, the cognate immune receptors of which are unknown. I am completely re-designing the receptors to recognize those molecules. I am hoping to complete computational design before the end of October and get preliminary data by the end of November.
If works, this technique will be extremely powerful and really revolutionize the field of plant immunity.
Anubhav
Sinha
Boston
Ed Boyden Lab, MIT
My goal is to systematically map the involvement of the peripheral nervous system in nearly every disease, and to design novel therapeutics that target this missing puzzle piece of human biology.
I am landscaping the state of the field across diseases (1) to identify novel disease areas where there should be an interaction that hasn't been discovered yet; and (2) to identify classes of mechanisms that are shared across diseases, to be able to clearly articulate what a bioplatform company would work on.
My major focus is on continuing to work on scientific landscaping and to iterate on bioplatform concepts, to see what might be possible right now, and what might be possible in the near-future.
My goal in the next few months is to have: (1) a comprehensive map of the literature that identifies all of the known science, with a clear articulation of value (e.g. targeting this mechanism in disease XYZ is ##% important); (2) scientific hypotheses about future science/new opportunities; and (3) concrete bioplatform concepts connected to (1) and (2), and mapping out what would need to be true to realize each platform.
Rohan
Kumar
New Haven, CT
CS PhD @ Yale working on quantum computing, advised by Yongshan Ding. Fully funded by an NSF fellowship. Prev. @UChicago (Undergrad), Oxford Physics (Research), and Super.tech (Quantum Computing startup now acquired by Infleqtion). Will be @MIT in Spring 2025, working on ML for quantum computing.
Compute is our most valuable resource, yet we haven't fundamentally changed how we compute since classical computers. Every tech breakthrough in history has relied on binary computation. While this consistency enabled rapid growth, energy expenditure is soaring and will provably become problematic for important tasks (incl. ML). As humankind advances, we'll dedicate an ever-increasing share of our energy to compute. We urgently need new computational methods that offer fundamental efficiencies for current and future problems.
Quantum computing presents a promising solution to this challenge. However, quantum bits (qubits) are much more prone to noise, both in magnitude and complexity, than their classical counterparts. Two broad classes of solutions to this problem have emerged: Quantum Error Mitigation (QEM), which seeks to extract useful information from noisy quantum computers, and Quantum Error Correction (QEC), which aims to use extra qubits to correct errors as they occur. QEM alone is likely not powerful enough to achieve quantum advantage, and while QEC will likely enable fault-tolerant quantum computing in the long term, practical QEC is decades away. However, there is likely a rich set of techniques in the intersection of QEM and QEC that could enable quantum advantage on practical tasks within the next few years. This is what I work on - i.e., blending QEM and QEC techniques to overcome the limitations of both paradigms and achieve near-term quantum advantage.
My goal is to build a software suite to enable the device-tailored application of these techniques to real quantum systems, enabling both quantum hardware and quantum applications developers to accelerate the practicality of their work.
I'm leading multiple projects on the topic I described above. That being said, I am still at a very early stage in terms of (1) research/potential IP and (2) figuring out how to commercialize it. My approach to quantum software is based on my work at Super.tech, which also built a quantum software stack relating purely to QEM techniques and subsequently got acquired. I have not iterated more on that fundamental idea in relation to todays' quantum industry and my own niche.
My plan is to focus solely on the fundamental research and de-risking the technology for now. Maybe that will change after 5050.
Boqiang
Tu
Boston
MIT
We are building a transformative technology that measures protein activity in ultra-high throughput, which enables AI-driven engineering of next-generation therapeutics and industrial enzymes
We have designed and tested the core components of this technology. We were able to generate millions of data points, train ML models for denoising and show how our data can improve protein function prediction.
We are going to leverage the data we have and millions more data points to be generated in the next month to engineer TEV protease to specifically recognize an arbitrary substrate. This will allow us to demonstrate the broad utility of this technology in protease engineering.
Vikram
Sundar
Boston
Sculpting Evolution Lab (Kevin Esvelt), MIT
(for all of these questions, read Bo's answers as well for context.)
We aim to make protein engineering easy by combining large quantities of data generated by novel high-throughput assays and the most high-powered machine learning available today. This will allow us to engineer very specific proteins like proteases that can cut arbitrary sequences very accurately, which would profoundly impact the fields of biomanufacturing and medicine. We are also thinking about applications like gene editors and other enzymes to which our platforms can be easily extended.
We have developed a novel high-throughput assay DHARMA that measures protein fitness, and a novel Bayesian denoising technique called FLIGHTED to denoise the output of a DHARMA assay. Combining these, we have measured the fitness of large datasets of TEV protease variants as a first step towards engineering TEV protease.
Scientifically, we want to show that we can engineer TEV protease successfully to cut a different substrate. Ideally, we would like to also demonstrate specificity and that TEV protease can be engineered to cut an arbitrary substrate (i.e. without experimental data specific to the given substrate).
Matthew
Szedlock
Stanford University (Palo Alto, CA)
Zheng Lab, Stanford University (PhD student). Previously worked at Soaring Co (drone startup based in Southern California) as a lead mechanical engineer. BS in Mechanical Engineering from Caltech.
I currently work on developing methods to make lithium-ion battery recycling cleaner, more efficient, and more economically feasible through combustion-based pyrometallurgy. By using parts of battery cathodes as in situ reductants, we can more effectively recover precious materials such as lithium and cobalt without harmful carbon additives and reduce the need for toxic solvents. My goal is to help create a future where lithium-ion batteries are part of a fully circular economy which reduces our reliance on mining precious metals and makes electric vehicles and other forms of stationary energy storage far more affordable. I hope that this will help accelerate the green transition and unlock a number of other technologies which are currently unprofitable or supply-chain limited.
During my PhD, I have worked on characterizing and developing a process that uses aluminum as an in-situ reductant to improve the recoverability of lithium, cobalt, nickel, and other precious metals. This method takes a fraction of a second and the reaction itself is self-sustaining with significant heat release which shows promise for repeatability at larger scales. Through methods including XPS and XRD, I have shown that we can reliably reduce the oxidation state of our precious metals which makes them more leachable in organic solvents compared to untreated cathode powders. Our recovery rates are currently in the 80-90% range and our method requires fewer pretreatment steps compared to standard commercial processes with less carbon emissions.
My plan for the next few months is to fully develop the processes needed to replicate this method at scale and to ensure that it reaches commercial-grade repeatability. I also want to conduct a thorough techno-economic analysis of my process and compare it to existing industrial methods to fully quantify the competitive advantage. Finally, I would like to transition from lab-scale experiments towards breaking down larger scale batteries and applying this method to see how well it can perform with battery scraps and other recyclable lithium-ion batteries.
Lucien
Viala
Boston
Tesla, Imperial College
I currently work in aerodynamics at Tesla, shaping the vehicles of tomorrow to be the most efficient on the road.
I have a vision of a world where scientific and engineering progress is faster, bolder and solves important problems benefiting everyone. I hope we get to the point where anyone has the chance to contribute their ideas and solutions.
I have done some iterating within Tesla.
I’ve been working with another engineer at Tesla on applying ML techniques, called Neural Operators, to aerodynamics data in 3D. This aim being to replace traditional simulation methods, which are computationally very costly, by much faster ML methods (speed up of ~10000x). We have a very preliminary tool that shows promise but needs a lot of work to scale.
I have designed and led an experimental proof of concept to validate the potential for active aerodynamic elements on road vehicles (passenger, vans, truck trailers) as a drag reduction method. The aim is to use moving surfaces , like flaps, to increase the efficiency of a vehicle beyond what regular shape optimization can offer. First results are encouraging but a lot more work is needed to implement this system on vehicles in production.
I have plans to keep iterating and refining technically the experiments I mentioned in the last question. These efforts are all within Tesla however.
I need to do some work on my end to land on a promising concept that I want to pursue and understand the commercial aspect of these concepts.
All I currently have are technically promising ideas, but they are somewhat disjointed and have not been fleshed out commercially.
Muntathar
Al-Shimary
University of California Berkeley
Doudna and Savage Labs UC Berkeley
Bacteriophages are in a constant arms race with the bacteria they prey upon, leading to the evolution of creative and novel enzymatic functions. Many of biotechnology’s most essential proteins have been sourced from bacteriophages; however, these proteins typically come from the most well-studied phages. Despite this, there exists a vast, unexplored diversity of proteins within other phages that has yet to be tapped.
Two major barriers hinder this exploration: the first is the bioinformatic discovery and isolation of these phages, and the second is the ability to study them in high-throughput—or in some cases, any throughput—systems. To overcome these challenges, we have developed a method for high-throughput characterization of phage genomes, regardless of whether they are ssDNA, dsDNA, ssRNA, dsRNA, or even form novel structures to conceal their genomes. By targeting phage genes at the RNA level, we have opened up a new frontier for phage characterization and gene discovery.
Our primary focus so far has been on the development and refinement of the tool and pipeline. We have expanded the range of targeted phages and demonstrated that we can effectively target the full spectrum of bacteriophage encoding strategies—something no other tool can claim. Through this process, we have gained a clear understanding of where the tool excels and where it falls short, enabling us to create efficient workflows.
I must admit that, at this stage, my work sometimes feels like a hammer searching for a nail. While its applications in academia are clear to me, I am still uncertain about how it could be leveraged for profit. In the field of phage antimicrobials, our tool stands out as the only one capable of identifying which genes in a phage might prevent it from infecting a specific target strain, assuming the inhibition is due to a bacterially encoded system. This capability could significantly enhance the design of phage cocktails.
However, assuming the tool isn’t the main focus of a company, I am particularly excited about the potential to discover commercially relevant ligases and DNA modification enzymes through bioinformatic workflows. These discoveries could then be validated using our tool or through other more direct protein-focused experiments.
Trent
Weiss
Cambridge, MA
MIT, Brushett Lab PhD Candidate (5th year)
My work focuses on developing advanced lithium-ion battery cell architectures that address many of the current limitations in such battery technology. Rather than relying solely on new materials, our approach leverages an engineering perspective to overcome fundamental issues related to mass and thermal transport. This strategy has the promise of enhancing both the performance and lifespan of lithium-ion batteries, making them more effective and reliable.
Our goal is to accelerate and expand the adoption of energy storage solutions for electric vehicles and grid applications while unlocking new possibilities for battery use in sectors like trucking and drones. We envision a future where energy is more sustainable, accessible, and reliable, with solutions that seamlessly integrate into modern infrastructure to create a more resilient and adaptable energy ecosystem.
We have made strong progress in both scientific and commercial de-risking of our battery technology. Initially, we focused on developing and validating the core principles of our engineering approach. This involved extensive research to model heat and mass transfer within our battery cells, as well as conducting system-level and technoeconomic analyses to confirm the commercial validity of our solution.
We have since transitioned into exploring different materials and assembly techniques to design alternative cell architectures. Our goal has been to find a balance between methods that leverage existing infrastructure and those that optimize performance. Currently, we are using existing methods with minor modifications to enable rapid prototyping and to develop a minimum viable product (MVP) that demonstrates our technology’s capabilities in real-world applications.
On the commercial side, we have engaged with potential industry partners and stakeholders to better understand market needs and refine our value proposition. This includes discussions with battery manufacturers, electric vehicle companies, and grid storage providers to identify specific pain points that our technology could address. These conversations have guided us in prioritizing features and applications for which our approach offers the greatest value.
Our next critical step in de-risking our technology is to finalize an initial design and conduct associated testing to demonstrate its performance in real-world conditions. This will involve lab testing and characterization, and may include advanced simulations to create a feedback loop for interpreting experimental data and optimizing the design.
Simultaneously, we plan to identify our most viable beachhead market and potential strategic partners. Engaging with these partners will help us gain insights into specific use cases, regulatory requirements, and integration challenges, allowing us to refine our product roadmap accordingly.
Once we successfully demonstrate the technology experimentally, we will look to procure initial funding to support further R&D and begin scaling efforts. This will include raising seed investment and applying for grants that align with our mission.
Ravi
Lal
Pasadena, CA
Currently I am a graduate student in the Arnold lab at Caltech. Previously I performed an internship at Google X. I performed undergraduate research in the Keasling lab at UC Berkeley.
I am a PhD student in the Arnold lab at Caltech working on the evolution of enzymes to improve their capability to perform synthetically challenging chemical transformations. My research currently is most focused on the development of wet lab protocols which generate protein sequence-function data efficiently for integration with machine learning methods which could be used to accelerate the directed evolution process. I hope that this research and any subsequent research that I perform will play a part in the growth of the bioeconomy. I envision a future where many of humanities chemical needs have been made more sustainable as our understanding and ability to control biological systems improves.
So far we have worked on projects in the Arnold lab involving the use of novel machine learning methods for the acceleration of biocatalysis-focused protein engineering. We are focused on learning the bounds of these processes during our time here. Some areas we have crossed off are de novo protein design, antibody engineering, and projects which are solely based in the dry lab. We have also done a cursory evaluation of current biotechnology companies to evaluate where there are opportunities in the bioengineering space.
Our plan for the next few months is to utilize our engineering methods and expertise to arrive at a marketable product which will benefit society by providing greener methods for chemical synthesis. A secondary goal of ours is to ensure that the product we develop serves the needs of the chemical community by providing access to more sustainable and robust catalysts. One de-risking step we plan to take is to talk to potential customers to help us arrive at a desirable product.
Yang
Zhong
Cambridge, MA
Device Research Lab (led by Evelyn Wang), MIT
The current water infrastructure is unsustainable – it contributes 2% of global greenhouse gas emissions, and yet 80% of wastewater is discharged untreated due to a lack of cost-effective solutions, posing a serious threat to our environment and health. I want to fill this gap by turning wastewater into freshwater, clean energy, and fertilizer, transforming the existing water infrastructure.
My research at MIT focuses on a membrane-based, low-temperature distillation technology platform for efficient liquid-vapor separation, applicable water, ammonia, and methane. Leveraging my expertise, I want to develop a scalable unit that converts wastewater and carbon dioxide into increased electricity, heat, and fertilizer, while producing freshwater. I have done some preliminary market and technoeconomic analysis to validate this idea.
I aim to develop a more comprehensive TEA model to validate my hypothesis and identify key cost drivers; I plan to apply for several small grants to support validation at the component level and demonstrate proof of concept for full system integration; Additionally, I’m seeking a technical co-founder with expertise in water treatment or a business co-founder with industry experience.
Kathleen (Katie)
Sicinski
Pasadena, CA
I received my PhD in Chemistry from Tufts University in 2021. My thesis focused on developing novel chemical methods to enhance the metabolic stability of therapeutic peptides in the GLP-1 peptide family, which includes hormones like Ozempic. This work resulted in a start-up company Velum, Inc founded by my PhD advisor Prof. Krishna Kumar. During my PhD, I had the privilege of representing Velum at the Tufts University $100k New Ventures Competition, where we secured 3rd place. After my PhD, I worked as a scientist for a start-up biotech company, PepGen, Inc. At PepGen, I saw the company go from series C fundraising to its initial public offering in 2022 and advanced into clinical trials for the treatment of Duchenne muscular dystrophy. I was responsible for transitioning laboratory operations from Oxford, UK to Boston, MA and discovering new bioconjugation methods for delivery of therapeutic oligonucleotides into target cells. I then moved in 2022 to my current position at California Institute of Technology as a NIH Ruth L. Kirschstein NRSA Postdoctoral Fellow in the lab of Prof. Frances Arnold. In my current position, I utilize the powerful tools of directed evolution for protein engineering and apply machine learning methods to accelerate wet-lab discoveries. This is where I met my current co-founder, Ravi Lal. We have been working together to fast-track the iterative process of protein engineering by incorporating machine learning and high throughput analytical tools to deliver sustainable biocatalysts for the synthesis of molecules.
My current work in the Arnold lab focuses on evolving and engineering enzymes to transform low-cost chemical feedstocks into a variety of valuable synthetic building blocks. Throughout my project, I have streamlined the protein engineering process by integrating machine learning methods, enabling faster evolution of biocatalysts while reducing resource consumption. My ultimate vision is to see biocatalysts become the standard in chemical synthesis. I aim to make these engineered enzymes more accessible so that chemists can easily transition to greener, more sustainable alternatives to traditional chemical synthesis.
So far we (Ravi and I) have worked on projects in the Arnold lab involving the use of novel machine learning methods for the acceleration of biocatalysis-focused protein engineering. We are interested in learning the bounds of these processes during our time here. Some areas we have crossed off are de novo protein design, antibody engineering, and projects which are solely based in the dry lab. We have also done a cursory evaluation of current biotechnology companies to evaluate where there are opportunities in the bioengineering space.
Our plan for the next few months is to utilize our engineering methods and expertise to arrive at a marketable product which will benefit society by providing greener methods for chemical synthesis. A secondary goal of ours is to ensure that the product we develop serves the needs of the chemical community by providing access to more sustainable and robust catalysts. One de-risking step we plan to take is to talk to potential customers to help us arrive at a desirable product.
Paul
Weitekamp
Los Angeles
SpaceX
The product I envision is a low cost and high cycle efficiency Compressed CO2 energy storage system for the grid that is deployable at scale.
I'm just getting started. I've researched prior art and talked with friends familiar with this industry.
The footprint and site availability of this technology must improve in order to achieve higher market penetration. The key enabler for this is to re-invent the low pressure storage part of this system. My plan to de-risk this idea is to attack the biggest threats to viability that cost the least first (fail fast and cheaply). It is important to push the technology and market forward simultaneously. There's no point in building new technology if nobody is going to buy it.
Simon
Roy
Quebec City, QC, Canada
Former Tesla and Lyft embedded systems engineer. Currently independent.
I build robots and electric powertrains. We are facing major issues such as labour shortage and carbon emissions, where these technologies can help. I'm exploring various sectors where there are urgent needs and viable business models.
I crossed off a couple of ideas in power electronics and micromobility after running customer interviews, which (after looking back) were great solutions applied to weak problems. I'm attacking from a different angle and starting with actual big problems.
This is what I'm currently doing:
1- Start from major problems: labour shortage, carbon emissions, urban logistics, etc.
2- Brainstorm and poke holes in how things are currently being done to solve those problems
3- Identify the intersection points between these problems and my specific expertise to maximize founder-problem-market fit
4- Line up 20-25 customer interviews and/or field experts to assess the viability of a business plan surrounding the solution
5- Iterate from 2-4 until a fit is found
This is where I'm at.
These are the next steps after a fit is identified
6- Identify hypotheses to derisk and design simple experiments
Sierra
Lore
San Francisco
Buck Institute for Research on Aging
I am currently working on biology of aging research to better understand the current state of the longevity field and the current challenges of extending healthy lifespan. My vision of the world is to to see significant maximum healthy lifespan extension (at least 50%) to reduce suffering and give people more time to spend with loved ones.
I have explored many areas within aging research (ex/ mitochondrial dysfunction, genomic instability, reprogramming) and the current paths to clinic or available technologies. While I now believe that these interventions may one day help slow down aging in aged individuals or may help as a preventative intervention in young people, it seems incredibly unlikely that they will be effective at reversing damage and significantly extending healthy lifespan in individuals who are already aged. I have become increasingly passionate about replacement as an aging intervention since it can solve issues such as extracellular damage, delivery mechanisms, and irreversible DNA damage that would otherwise not be possible to fix with any other single technology or intervention.
I would like to carry out some proof of concept experiments to prove that replacement will extend lifespan and have rejuvenation effects on the brain as we would expect based on results from heterochronic parabiosis-type experiments. I also would like to continue meeting with PIs and experts in the field as well as publish an academic review on replacement in aging (I have finished the manuscript draft but still need to submit to journal) because I want to hear as much feedback as possible on why this would not work and find ways to de-risk.
Zach
Rosenthal
SF
Birdwood Therapeutics
New induced proximity modalities, beyond degraders, will revolutionize medicine. I aim to develop those modalities and unlock the ability to discover small molecule inducers of proximity through high-throughput screening
At Birdwood, we've built a team of scientific advisors and will pursue two complementary discovery platforms. Our first discovery platform enables DEL (DNA encoded library) screening to be applied for the discovery of small molecule inducers of proximity. This strategy will: - improve upon the efficiency of DEL screening to identify 'weak' (high µM) hits which could be key starting points for molecular glue discovery campaigns; - enable discovery of molecular glues for target pairs for which no known binder starting points are known; - enable screening in cellular lysates, more accurately recapitulating protein states and associational complexes; - not require protein immobilization, frequently employed in DEL enrichment screens, which may interfere with protein folding; - can detect small molecules that facilitate interactions between two proteins through intermediates. Our second platform, in collaboration with Cora Biosciences, will enable us to rapidly profile the binding kinetics for hundreds of thousands (and eventually, millions) of compounds simultaneously - a medicinal chemist's dream. This platform will supercharge drug discovery by enabling SAR studies at a scale previously unthinkable (data generation throughput > 10^6 improved). We're in the process of leasing lab space and will be ready to begin to de-risk our approach ASAP.
(see previous Q for our specific assay goals) We are planning to lease lab space to establish key elements of our platform. The first important de-risking of our technology is to show that it can be used to discover already known inducers of proximity. To accomplish this, we will use the well-studied FK506-FKBP12/FRB system (and analogs of FK506 with various kinetic/thermodynamic properties) to optimize important parameters of our technology. After showing that our technology can be used to discover already known small molecule inducers of proximity, we then plan to show that it can be used in an entirely novel context. We are still trying to figure out the best first 'test' case, but I want to go for the gold: I'd like to discover small molecules that can induce proximity between nuclear import receptors (NIRs) and proteins whose mislocalization to the cytosol causes disease (e.g., TDP-43 in many neurodegenerative diseases, FUS in FTD/ALS). These compounds can be thought of as 'molecular hitchhikers' - they cause a target protein to 'hitchhike' on the nuclear import receptor, returning them to the nucleus (and removing them from cytosolic aggregates) where they can then perform their intended function.
Dhruva
Katrekar
Mountain View
Currently at Arc Institute. Previously Shape Therapeutics and UC San Diego.
My vision is to make life-saving medications accessible to everyone via the creation of innovative, affordable therapeutic options. I feel like the gut microbiome can be specifically altered to produce such low cost therapeutics directly within a human.
We've gone through 2-3 rounds of iterations to identify the most achievable POC and are currently conducting scientific de-risking through experiments. I'm eager to learn how to approach commercial de-risking next.
In the coming months, the goal is to advance our scientific de-risking efforts and achieve POC. At the same time, we aim to conduct a thorough freedom-to-operate analysis and look into regulatory de-risking.
Michael
Massen-Hane
Boston, MA
MIT
I'm a Postdoctoral Associate working on new carbon dioxide capture systems that have the potential to be widely and inexpensively deployed. I'm working towards decarbonizing our power generation and industrial sectors to secure a safer and sustainable planet for future generations.
For the last 3 years, I've been analysing and developing multiple electrochemical-based carbon capture technologies in the lab at MIT. One key technology I've been working on, specifically targeted at capturing point source CO2 emissions, has been demonstrated in the lab for over 100 hours, at approx. 50 grams of CO2 per day, and with a technoeconomic assessment that puts the technology on par with the best commercially available systems. We've since made improvements to that technology, making the systems even more competitive.
As an extension to the >100-hour run already performed, I am currently determining the longer-term stability of the process when exposed to known industrial contaminants. This experimental work is being done in parallel with developing a technoeconomic model that includes parameters which account for replacing components if/when those contaminants impact them.
Jacob
van de Lindt
Boston
MIT
I aim to build a company that substantially helps reduce the emissions of the maritime industry, as well as works towards ocean sustainability causes. The key technology piece is utilizing over fifty years of engineering excellence in the fission industry, as well as its new advances, and combining these with recent breakthroughs in fusion energy technology to produce a fleet of fission-fusion hybrid powered cargo container ships. This combination of technologies would play to the strengths of each: lowering the risk/physics requirements of the fusion plasma, while at the same time potentially reducing the nuclear waste of the fission system, and enhancing its overall safety.
Since a year ago, I have been working on developing the idea further in my hours outside of research with extensive modeling of the hybrid system in OpenMC, an open-source neutronics code, and plan to publish some of the results found there. In addition, for a term project I studied the economics of pure fission used in commercial shipping, and wrote a report detailing the economic advantages over alternative low-emission fuel. I took a graduate class in the marine engineering department called “marine propulsion” – going over the engineering and design of ship engines and related constraints. I was a TA and group lead for Dennis Whyte’s fusion design class at MIT for a fission-fusion nuclear waste burning tokomak, leading the fusion core design sub-team with another grad student. In a previous iteration of that same class, I was a co-author on a design publication.
I plan to aggressively improve my OpenMC model to include time-dependent analysis of the hybrid system so that lifetime reactor analysis can be done, as well as begin to build out other needed software modeling capabilities so that the concept can be refined further into a comprehensive initial design point. In addition to OpenMC, I plan to also take a deeper dive into the requirements of the fusion subsystem I have in mind. Besides engineering, I also plan to gain a deeper understanding of the regulatory burdens of this idea, and what form the partnerships would look like between my company, ship owners, and large Korean shipyards that build container ships, as well as considering what crew additions would be required (engineering, radiation, safety, security, etc.).
Sasha
Gao
Boston
Brushett group at MIT
Marika
Ziesack
Boston
Current: Senior Scientist at Wyss Institute at Harvard University; Past: CTO at Circe Bioscience Inc.
I'm exploring the concept of refinery-inspired biomanufacturing, centered on three key ideas: using C1 feedstock from waste sources, super-charged bioprocessing to convert feedstock into products, and a biological downstream approach for waste-free purification. I'm also focused on partnership models and strategies for rapid revenue generation. This approach aims to create a sustainable, efficient system for producing sustainable materials from low-cost, waste-derived inputs.
On the tech side, I have built a high-level process model, written a few small grant proposals and will soon begin wet lab research funded by Wyss. On the biz side, I have had conversations with a few mid-size companies relevant to the idea; one of them is currently in NDA stage with Wyss. I've also met up and discussed my idea with two ARPA-E program directors and a few investors. I started a draft pitch deck.
Biz: Develop clear business strategy; identify initial partners (MOUs?); build team
Tech: demonstrate novel fermentation process at lab scale, build and validate TEA, generate IP, scale and provide initial product specs
Funding: make pitch; build funding strategy (dilutive/ non-dilutive); raise first round
Stepan
Tymoshenko
Sacramento, California
Mammoth Biosciences Inc., ex-Zymergen, PhD and post-doc from EPFL and University of Geneva (Switzerland)
With my co-founder, we want to turbo-charge cell-free production by providing abundant and cost-effective energy substrates. Our success will be a paradigm shift in making biomolecules. Our energy substrates will enable cell-free systems to compete with inherently less efficient fermentation. Our innovation is the key to cost-effective enzymatic production of DNA, RNA, proteins, other high-value biomolecules, and biopolymers without growing biomass.
Through iterations of literature and patent searches as well as talking to industry experts, we zeroed in on our initial product and an enzymatic path to producing it. We performed techno-economic analysis to estimate COGS at different scales of production and key variables that affect the COGS. We have planned the initial proof-of-concept experiment to assess known unknowns, and potentially discover unknown unknowns.
In the next few months, we plan to execute lean PoC experiments to assess known unknowns and, possibly, discover some unknown unknowns. Subject to the availability of additional funds we will expedite the progress towards establishing a minimal viable process to make grams of the product and validate our downstream processing approach. We then will share the product samples with select early adopters who can readily use it in their cell-free systems and share their initial feedback on our product's utility. Based on the feedback we'll iterate on our production and downstream processing to 1) improve production yield; 2) scale up production volume; and 3) improve product compatibility with the customer processes.
Nicolas
Sawaya
San Francisco
Azulene Labs (previous: Intel Labs; Harvard @Aspuru-Guzik group)
I want to increase the accuracy of chemical/materials property prediction by 10-50x. I have strong theoretical reasons for believing this is possible. This would greatly reduce R&D costs, as it would allow us to entirely replace many laboratory experiments.
I have founded the company, developed most of the theory, and written some of the code. I have done some consulting work through my startup. I've applied to an ARPA-E grant jointly with another startup.
My big priorities are:
- get to certain MVP milestones
- raise an Angel round (already started)
- purchase significant amounts of computer hardware
- make my first hire
Neel
Parikshak
New York City Area
Regeneron, UCSF, UCLA
Generate and leverage large omics data and apply machine learning to identify new therapeutics in neuroscience.
Evaluated competitive landscape, established some proof of concept with existing data from prior work, explored therapeutic indications and feasibility of future clinical trials.
Establish a strategy that maximizes probability of near term successes while setting a foundation for future discovery and differentiation from competition. Delineate experiments, analyses, IP strategy, and necessary funding for next 1-2 years in collaboration with co-founder.
Nelson
van de Lindt
Bend, OR
NuScale Power, Elementl
I want to reshape heavy polluting industries through the use of high capacity renewable energy sources to reduce emissions. My goal is to build an energy abundant and secure future while not sacrificing efficiency or the environment.
To achieve this goal I have worked in the energy industry specifically Nuclear. Additionally I have begun techno economic analysis of a nuclear design.
Continue an optimization tool in Python that will allow for the optimal reactor design to be constrained on economic variables. Additionally, I will look into conflicts with my current contract.
Jolyn
Gisselberg
Foster City, CA
Currently working on the startup, but previously at Google X and Stanford.
My cofounder and I believe we can fundamentally change how biochemicals are made by unlocking cell-free production. We are developing a unique way to produce energy substrates which is potentially orders of magnitude cheaper then current market rates. This is the missing key needed for synthesizing biomolecules at scale without needing to rely on cells.
We have talked to people in the industry and have completed a techno-economic analysis to make sure there is a solid business strategy behind our idea. We’re at the stage where we’ve planned out initial POC experiments and excited to get into the lab!
Our next major step is to get into the lab and complete our POC experiments to identify and solve any issues with our plan. Our major blockers are access to lab space and equipment. With additional capital we plan on expanding our POC work to make a minimal viable product that we can start distributing to early partners for feedback.
Neil
Tay
San Francisco
UCSF
I develop molecular technologies that enable high throughput studies of the human immune system. I seek to combine these technologies and computational approaches to greatly expand our understanding of the immune system and create novel immunotherapies and cures for diseases like cancer and autoimmunity.
I've developed two technologies--one that enables tracking of cell interactions and another that allows high throughput discovery of antigen and antigen receptors. Much effort has been put into validating and scaling these technologies to the levels needed to achieve the applications I envision.
My plan is to continue optimizing and scaling these technologies and in parallel, start to execute various proof of concepts in potential target areas using the platforms to evaluate feasibility.
Justin
Bult
Fremont, CA
Currently work at Tesla in Cell Manufacturing. I previously worked at Corning Glass, Dow Chemical, National Renewable Energy Laboratory, and NASA MSFC.
To build a lasting company that can build hard tech to improve the energy landscape in North America. The battery industry is dominated by the APAC region and for North American companies to succeed they require disruptive approaches that will work through scaling. I intend to provide that technology and approach.
I have build process prototypes and flow sheets for the technoeconomic analysis of preferred battery manufacturing design. Over 10 design iterations on process that did not yield acceptable manufacturability have been shelved.
The next step is to identify a suitable industrial location to work on design iterations and to accelerate creation of mock demonstrators, process flow video/fly throughs, intellectual property, and working prototypes.
Jaime
Roquero Gimenez
San Francisco
Just quit my job at Adela Bio to focus on building.
I hope that multi-cancer early detection becomes one day reality. As of now, the diagnostics industry has failed. I am approaching this from a first-principles approach, working backwards from what a final product should look like. This means using ML at the right places in the product development, and using PCR as the lab workhorse. I am building a computational pipeline to prototype this idea in the most lean way.
I have an end-to-end compbio pipeline that searches for highly specific sequences in a reference-free context, using biological insights on early cancer development to prevent overfitting as much as possible. I have run several experiments leading to candidate cancer-specific sequences, though there's still a long way to go to confirm these findings in-silico before moving to actual PCR.
I think there is enormous amounts of publicly available data to corroborate multiple times over whether a particular sequence is indeed cancer specific. Also, I want those sequences to have documented cancer-related properties, to be shared across multiple species, and harbor some specific patterns that are created through a clear biological process (like alternative splicing). I want to avoid the trap of moving directly into wet-lab testing without having sufficiently de-risked in silico. I think that in a couple months I will know whether I have a robust candidate that makes sense to test in a lab, or whether this whole approach is just not working.
Younhun
Kim
Boston, MA
Current: Mass General Brigham (Previous: MIT)
I currently work on genomics-related computational/statistical methods for the microbiome. I think that the microbiome is a large missing link in our understanding of health. I want to build algorithms (with or without AI) to understand it better and design non-invasive treatments for some of humankind's persistent ailments.
At MGB we've been working towards a general large-scale understanding of the microbiome -- meaning trying to understand the system as a whole, and working towards predicting emergent behavior that is only possible with an entire microbiome instead of a small, selective culture. For a while now, my working partner Utkarsh Sharma and I have been discussing the untapped potential of combining both genomic and "non-genomic" studies, which we understand as being the missing ingredient in our analysis pipeline.
We want to implement a model that we've dubbed "microbial general intelligence". Even if the end-to-end pipeline (using this model, to translate a microbiome sample into a disease-curing pill) requires more R&D (e.g. clinical trials), the model itself will be of significant interest due to its ability to predict outcomes of microbe-oriented treatments for selective diseases, such as FMT for C.diff.
Utkarsh
Sharma
Cambridge, MA
Postdoc at Mass General Brigham (Brigham and Women's Hospital))
One (bad) way to program a computer is by changing the melting point of copper wires or doping of silicon transistors. In contrast, high level intervention via programming languages offers robust, precision control and prevents unintended side-effects. Medicine needs to move in the same direction-- precise, high-level interventions that do not bypass the checks and balances of the human system.
The (gut-)microbiome holds this potential, and consequently for the first time we see the promise of a true cure for many chronic ailments. We are building Microbial General Intelligence (MGI), an AI that will understand the microbiome with context, allowing the development of microbiome therapeutics.
We have shown that despite its immense complexity, the microbiome can indeed be predicted and controlled. In our academic work, we have built state-of-the-art models that predict the future behavior of the gut-microbiome. We have also invented a technology that profiles the impact of the microbiome on the host cheaply and noninvasively [patent filing in progress].
Over the next few months, we want to train our AI models to predict microbiome dynamics in a few-shot manner. We have made blueprints for a few potential custom architectures by gluing together LLMs with our own pieces, and we want to train them on the large amounts of publicly available data that traditional microbiologists cannot leverage. This will help us 1. precisely understand the scaling of our models, which will refine our timeline for our first therapeutic and 2. understand how to make our models generalizable in order to apply to other de-risking industries like animal husbandry and over-the-counter personalized supplements.
Further, we want to explore the market for a Microbial AGI in drug-discovery. Our expectation is that since our AI will be able to understand microbial interactions from genetic information, it will form a cheap and scalable precursor to wet-lab experiments for therapeutic design.
Karl
Krauth
Palo Alto, CA
Currently a postdoc at Stanford University in a microfluidics lab, previously I did my PhD in machine learning at UC Berkeley.
In 20 years, microfluidics will be as impactful as the microprocessor. General-purpose microfluidic chips will be running in every biotech lab, generating petabytes of data to power the next generation of AI models, leading to exponential progress in therapeutics research.
As a first step toward this vision, I’m creating a programmable microfluidic device that can measure 100 million protein-protein interactions in a single experiment, which will be 1 million times cheaper to run than contemporary methods. I’m planning to use this device to provide large-scale datasets for pharmaceutical companies and to train my own machine learning models to guide protein design.
I've designed and manufactured the device and shown that it works at a small scale.
I've run simulations to estimate the experimental cost of a full-scale assay ($5000 for 100 million protein-protein interactions).
Finally, I've built up hardware and software infrastructure that allows me to iterate much more quickly than with traditional microfluidic workflows.
A key step in the assay is tagging proteins using a technique called cDNA display. I’m currently working on increasing the yield of this step so more proteins end up getting tagged during the reaction. I’m also scaling up the size of my protein library for a large-scale proof of concept run.
Daniel
Moore
Costa Mesa, CA
Currently at Anduril Industries, and have been for a few years. Before that I was at an EV startup, and doing prototype engineering for Fiat Chrysler before that.
My work thus far has been disruptive to the US Military Industrial Complex, but the moonshot I see is to build opportunity to build an American Tech Company that democratizes rugged, cutting edge hardware.
I’ve benefited and developed a network of people who believe in me and can support me, as well as a catalogue problems I know I can solve. These problems include rugged edge compute, networking, radio capability, as well as other simpler and more complex products. I’ve also put my heart into 3+ years of experience at Anduril, bringing 13 products to fruition in that time frame.
I’m planning on developing a market map for my ideas, finding two to three more cofounders in addition to the one I have found already. From there we will need to develop a pitch deck, do a hackathon together to understand team chemistry, and decide what our first steps as a company will be. That’s just scratching the surface, but if I sound like I know what I’m doing, I don’t.
Alex
Powers
Palo Alto
Stanford (I just finished PhD from Stanford, I still do research there)
My vision is to use the 3D dynamic structures of proteins to rationally design safer, smarter drugs. Most drugs work by binding to proteins like a key fitting into a lock. Thanks to incredible advances just in the last few years, we can now rapidly determine the 3D structures of almost any protein. But these structures are still just static snapshots of very complex, dynamic systems; my work goes a step further, leveraging protein flexibility and motion to uncover hidden opportunities for drug design. For example, we might discover a drug binding pocket that only appears when a protein changes shape in response to particular cellular signals. To do this, I’ve been developing new computational tools, that combine atomic physics simulations and AI. By targeting more specific protein states and discovering concealed drug binding pockets, we can unlock best-in-class medicines that are more precise and effective, with fewer side effects even for well-studied targets. One of my current areas of focus is to create less addictive pain medications with minimal side effects for long-term chronic pain treatment, which could transform patient care for a very common condition.
Towards safer chronic pain treatment, we discovered a promising lead compound targeting the cannabinoid receptor that’s progressed to animal studies. While cannabinoids are safer than opioids, compounds like THC come with mind-altering side effects that limit practical, daily use. My research used dynamic simulations and AI tools to probe these receptors at the atomic level, leading to the discovery of a hidden binding pocket. By rationally engineering new molecules using these insights, we created a lead molecule with 30x fewer side effects in mouse studies, while being more potent for treating inflammatory pain than THC. This is a pretty big deal, because the computational, rational strategy led to a new approach and insights that no one expected at such a well-studied receptor protein. Stanford and WashU submitted a provisional patent, and we are working on revisions for our publication (in Nature, a top journal).
I also developed state-of-the-art technology and computational tools that could extend this strategy to other receptors and challenges. In our internal benchmarking, these tools are also faster and more efficient that current virtual screening tools with a wide range of applications (being resource constrained in academia forced me to innovate). Stanford filed a provisional patent on some of this technology and a publication is in preparation.
(1) Speak to more medical/pharma experts to assess how promising this cannabinoid drug is for patients. Is it truly solving an unmet medical need? Obviously, I presently believe it will, but I’m not a medical doctor and might not be seeing all the factors.
(2) Reach out to Pharma and academic labs, to see if they would sign up for partnerships to test/apply our new drug design technology. Is this a widely applicable technology that I could get contracts for right now?
(3) Simultaneously with above, get the 2 papers published so scientific evidence is concrete and public – basically free advertising and credibility. This could realistically be done in 1-2 months.
(4) Finally, present a convincing plan to stakeholders for licensing / optioning one or both of these inventions before anyone else does.
Laura
Vasquez Bolanos
San Francisco
Loyal longevity startup, formerly Cornell, UCSD bioengineering
I want to build an intervention that slows down reproductive organ aging and extends our reproductive window. Givings us more time to decide on whether to build a family, build a company or anything else our heart’s desire as lifespans continue to lengthen. I believe there are a few different paths to this goal, some longer than others, I would like to optimize for the quickest path to approval. This may look like leveraging accelerated regulatory pathways, different primary/secondary endpoints, and/or repurposing existing drug and safety profiles.
High level, my hypothesis for aging is that it is cumulative and the earlier you intervene the better, while down the line I believe reversal may be feasible, to generate a positive impact on human longevity now, we should investigate timing with repurposed drugs. My focus has zoned in on reproductive longevity, I have been investigating various repurposed drugs and the intersection of these with existing literature in the area of reproductive organ biology. However I am not sold that oral administration is the best route largely due to timing. Focusing on the decline of the ovarian reserve in women, I believe to have a meaningful impact on maintaining fertility is to intervene earlier closer to the age of 20. As you can imagine, a systemic intervention could prove troublesome, with the brain fully developing by the age of 25 and bone density setting around the age of 30, earlier interventions could possibly risk disrupting the body’s continued maturation. This is where I think localized administration, intravaginaly could prove key for women. Contraception is a great example with far fewer side effects with intravaginal or intrauterine administration.
On the note of contraception, something else that has crossed my mind, is combing this intervention with contraception. Rational being that, in theory, one would think that contraception should delay ovarian reserve decrease because it is preventing women from ovulating, however, what we have learned from studying contraception in women, is that this is not true. Contraception prevents the release of eggs, but does not prevent the recruitment of primordial follicles and the maturation and atresia of those follicles. Then if you paired contraception with a drug that is capable preventing the recruitment of primordial follicles and maturation of those follicles then the ovarian reserve should be able to be maintained and not experience the same level of decrease as we age.
I have been able to talk to other researchers in the space to see how they’re thinking about this space and what technology is at the frontier (specifically in the ovarian and testes exosome space, which is very high potential but high technical complexity.)
Will admit the following is a bit of stream of consciousness to jot down what I am thinking of.
I need to figure out what is the best way to test the local administration, is it an organoid model of the ovary or a mouse/rat in-vivo study to screen the top few candidates.
I’d like to take advantage of the 5052b FDA pathway of repurposing drugs, but given the different route of administration there likely are additional preclinical safety study needed (ie. Rabbit vagina sensitivity/irritation is the gold standard to the FDA) at what point do I screen this in case it’s a kill?
My intervention has to be exceptionally safe, ensuring it is not hurting women’s fertility, my guess is chronic use and pupping studies in mice or equiv. May be needed. Or along this line, how long of a study is needed at bare min to observe a positive impact on ovarian reserve? Based on the rapamycin menopause study, within 12 weeks there was a positive impact, could likely use similar primary and secondary endpoints. This is part of the reason I think it would be interesting to pair with population of contraceptive users, because they do not want to be pregnant but they would likely not be opposed to taking something that protects their fertility, which allows the risk of having a child on X intervention to be mitigated.
Gina
El Nesr
Bay Area, CA
Stanford University
I’m a rising fourth year biophysics PhD Candidate at Stanford University working at the intersection of deep learning x enzyme design, with a broader interest in biological solutions for climate change and human sustainability. My research at the moment involves developing methods for designing new-to-nature enzymes for functions and reactions that currently do not exist; and if they do exist, making them more efficient.
Right now, I have built a lot of the methods involved for developing these biologics: building ML methods to predict protein dynamics, developing algorithms for metal binding, and experimental tests for metal binding. What's left? Putting them together for a proof-of-concept enzyme!
Right now, I am completing a series of experiments to test whether my models do indeed bind the metal they are designed for. Per my PhD, I am doing Zinc. Next, I need to move the model to incorporate other metals including but not limited to Copper, Cobalt, Nickel, and Lead. Next would be testing those proteins out. Over the last two weeks, I have figured out a pipeline and assay to easily test for their binding. For building an enzyme, I am finishing model training for prediction of dynamics and with my collaborator (and maybe future co-founder?) we will test a proof of concept protein there. Over the next couple months, I will need to pick an enzyme to design and merge the two models together. Then I would experimentally test it!
Norh
Asmare
Atlanta, GA
Biomedical Microsystems Lab @ Georgia Tech
I want to transform therapeutic cell manufacturing testing from a labor-intensive, fragmented science into an autonomous, massively scalable manufacturing workflow
My co-founder and I have raised almost $500k to de-risk the technology, build a POC device and launch customer discovery campaigns. We've secured agreements to run validation studies with 2 academic labs. Commercial partnerships will be initiated once validation studies are completed favorably.
- Run platform with engineered cells from academic partners
- Continue running customer discovery to identify their pain points in manufacturing and beyond
- Create low volume production run, qualify platforms in preparation for deployments with commercial partners
Chad
Wilson
Boston
MIT
Solutions to water scarcity
Developed TRL 5 devices for water production from air
Find out if my tech is worth commercially pursuing.
5050 cohort 5 form
First name
Last name
Where are you based
Your current affiliation
Describe your work and the vision you want to build in this world
Who is someone you look up to who inspires you and what about them inspires you
What are some areas outside of your research that you re curious about
Picture we can use for the cohort directory
Random fact about you
1
Michael
Nitzsche
Cambridge, MA
Hatton Research Group - Massachusetts Institute of Technology
My work is in electrochemically driven carbon capture for decarbonizing heavy industry, and I am hoping to start a company to mitigate hard-to-abate emissions. I'm passionate about sustainability and the environment, and my career goal is to maximize my negative carbon footprint.
I really admire Bill Gates, in that he has leveraged his wealth and influence to try to make wide-reaching positive impacts ranging from climate to healthcare.
I really enjoy learning about ecology and the natural world
I can juggle!
2
Neal
Amin
San Francisco
Stanford University (for now!) I’m leaving to go full time on founding Collage Biosciences later this year.
I am developing RNA splice-modifying therapeutics for neurodegeneration and the aging brain. By developing splice-sequencing technology and an ML-driven computational biology approach, we are building the first atlas of brain splicing across the lifespan that will power our target detection platform. By applying my organoid screening platform and in vivo preclinical models, we will improve neural health and develop our lead candidate - a antisense oligonucleotide drug modifier of neurometabolism. We are aiming for first in man clinical trials within 5 years.
My father and brother- both are very unique in how they interact with the world, are distinctly individual, and have strong sense of community and are effective community builders (yet in very different ways!)
Design, economics, music theory, psychology (I am a psychiatrist though my research isn’t specifically focused here).
I’m learning to sail! I can lake sail now and want to sail in the bay
3
Joseph
Mooney
Cambridge, MA
Postdoctoral Associate
I develop low-cost decentralized water technologies, using the moisture in the air and sustainable heat (solar waste or waste) to produce this water. We can operate in the most arid of climates in either a passive or active manner. I see myself building a device to be ready for pilot in the next year, looking for immediate funding to incorporate, establishing myself in a climate tech hub, hiring my first employee, and developing a plan for the pilot. I would envision my first customer within the agriculture space (small-scale crops or hydroponics).
As much as one can look to the stars for inspiration, I tend to look very close to home for this answer. I would choose my mother and grandfather for this. Both grew up in very challenging areas for growth in rural Ireland and in the north of Ireland during our internal troubles. My grandfather didn't have much formal education, yet he knew and utilized what he was good at: working with his hands and his ability to maintain strong connections. He started a sweet shop, which evolved into a gas station and then an auto shop. Even with crippling arthritis, he kept working because he had a passion for his work and his family. On my mother's side, she has worked and lived through very challenging times; being 21 and the head of a hospital ward, held at gunpoint, caught in the crossfire, and seeing some gruesome things, she will always see the light. This has led to lives being saved, I getting stopped by my mother when we're walking in the city to be told that she saved that person's life or someone close to them. Often, in entrepreneurship, the repercussions of making mistakes might mean more time to execute, less money, and less impact, but for someone like my mother, it could be the difference between life and death. Having a mindset like hers as I navigate my career will certainly lead to a better chance of success and impacting people's lives.
I would say producing energy off grid and reduction of bi-products to generate fuel.
I love photography and I've solo travelled to Iran with no cell phone service.
4
Zewen
Zhang
Mountain View
Apple
leverage data to systematic design battery materials and manufacturing
Lebron James. His discipline and persistency
Sport psychology
love playing tennis
5
Chao
Cao
Boston
Carnegie Mellon University / Boston Dynamics AI Institute
Autonomous mobile robots that are useful in people's daily life
Steve Jobs: the attention to detail and user experience.
Manufacturing/Radar Technologies/Marketing/Recommendation System
I like seafood
6
Sulin
Liu
Boston/New York
MIT
I work on AI and its applications for science domain. My vision is to build AI tools designed to accelerate the screening and proposal of new drug/material development, using the idea of AI agent interacting with multiple AI models.
Steve Jobs, for iPhone and Fei-Fei Li who creates ImageNet
urban planning, quantum mechanics, making espresso
I love to practice long-boarding once in a while
7
Aditya
Venkatramani
Boston
Harvard University
I am building a device to measure tissues' RNA/ DNA/ protein content at single-cell resolution with genome-scale sensitivity. My vision is to enable the creation the usage of genomic data to understand organs and organisms in their native or abnormal states.
Several people, maybe not singularly though! One example would be my PhD advisor, Misha Lukin. Characteristics that inspire me are people who are fearless, creative, think deeply about problems, kind to others, and have a strong narrative about what they do.
A lot actually! I've myself jumped fields from quantum physics to genomics. I am curious about neuroscience, emergent phenomena in biology, geology, various aspects of climate, quantum algorithms, philosophy of knowledge ...
I love climbing mountains!
8
Nils
Burger
Boston, MA
Chouchani Lab, Dana-Farber Cancer Institute and Harvard Medical School. Previously, Murphy Lab at the University of Cambridge, UK
Sleep is a major determinant of longevity and protective against metabolic, cardiovascular, and age-related diseases. However, little is known about the molecular mechanisms underlying sleep. I propose that metabolic adaptations during sleep regulate cellular functions and thereby convey health promoting and pro-longevity effects. Defining the metabolic principles of sleep will provide us with a unique therapeutic handle which we can leverage to develop a new class of therapeutics to target and activate the pro-health mechanisms of sleep. Harnessing sleep will revolutionize the way we age.
My mentors in the academic field inspire me, all of them very successful professors at Harvard and Cambridge and in addition founders of startups which are on a successful trajectory. They manage to do what they love, they do exceptional research and likewise they manage to transform their findings and ideas into companies that can have real impact.
I find the current AI boom fascinating and I can't get enough of learning about more exciting areas where AI will change the planet and our lives
I learned Hungarian and speak it fluently although it is not useful very often.
9
Assaf
Magen
San Diego, CA
Voyant Bio
I want to build a system to enable every cancer patient (and beyond) to reach a cure instead of prolonging lifespan in just a few months with current treatments.
I'm inspired by Scott Phoenix and his work in the deep tech/"AGI" in a space where most misunderstand the capabilities of general "AI".
Wildlife/plant ecosystem sustainability
Avid cacti grower
10
Jase
Gehring
Berkeley, CA
Streets Lab, UC Berkeley (previous Latent Labs, Arcadia Science, UW, Caltech, UC Berkeley)
I develop advanced technology to make discoveries in biology. I have always seen biology as a data-limited field, and now I'm looking to combine generative modeling with high-throughput and pooled experiments, using cutting-edge data and modeling to bring new therapies into existence.
Carolyn Bertozzi. She starts with a deep, intuitive understanding of chemistry, then applies to an area that she is learning all the time (biology). She is always looking for deeper impact by commercializing her inventions and bringing her discoveries to patients and industry. She supports scientists across the spectrum, and especially supports new startups by serving as an advisor and attracting interest and funding. Carolyn is simply f***ing awesome.
I love being outside in nature and I take advantage of living in Northern California. I'm learning to play guitar, and I'm nurturing a long-held interest in woodworking
I've grown thousands of plants. As a kid my first biology experiment was secretly crossing my mom's tulips. In high school I worked in a greenhouse, speaking only Spanish with my immigrant co-workers. Then in college I helped perform one of the first large-scale surveys of the plant root microbiome. Still have my green thumb :)
11
Jason
Zhang
Boston, MA
PhD Candidate in Biological Engineering at MIT
My research is focused on HIV vaccines and cancer immunotherapy. I wish to build cutting-edge biotechnologies that harness our immune system to improve human health.
My research mentor Darrell Irvine because his passion for doing good science is so pure and genuine. I also look up to his creativity in harnessing immunology to accomplish novel therapies.
Machine learning and agriculture
I was on an Indian Bollywood fusion dance team in college, and we competed in and won national tournaments.
12
Sebastian
Kenny
Seattle
Baker Lab, Institute for Protein Design
I design proteins to perform novel functions that our current therapeutic strategies can't achieve. I envision a world where no diseases are not treatable.
My mother - she knows the importance of networking and being kind. Whenever she needs something done beyond her area of expertise, she knows who to contact and get advise and support from. Through all the connections she has built, everything becomes possible.
The food industry
I got to know 110 out of the 116 bus drivers in the Greater Lafayette, Indiana area during my first semester at Purdue. They've invited me for all the holidays ever since.
13
Kwat
Medetgul-Ernar
Stanford & Teton Valley, Wydaho (WY + ID)
Stanford MD-PhD Program with PhD in Biophysics at Mark Davis Lab
Translate our new blood test into the clinic, establishing the new common blood test.
Elon Musk. Dyson. Paul Graham. etc. They built.
Fitness.
I own a jiujitsu gym :) MountJJ.com
14
Mariëlle
van Kooten
Palo Alto, CA
Stanford University
I am on a mission to reboot the human powerplant. Advances in omics measurements, mRNA technology and genome engineering offer unprecedented precision and potential to deliver specific genetic instructions to cells to restore or enhance function. I am an engineer, and these cutting-edge tools make it possible to directly target and repair mitochondrial dysfunction, offering a real opportunity to redefine human health span and lifespan.
I learn from people who show persistence and tenacity while given options to opt-out
Human hibernation, although this arguably strongly relates to mitochondria. Space exploration, from the research, machine, human body, and cultural perspective.
I love Karl the fog
15
Kyungyong
Seong
Berkeley, California
Ksenia Krasileva lab at the University of California, Berkeley
Immunotherapy in plants! Pathogens evolve faster than plants, and the probability of disease increase in mono-cultural agricultural sites in every season. Current technology requires five to ten years to identify functional plant immune receptors in nature. These immune receptors can be compromised within a few years by pathogen evolution in the fields.
My work aims to bypass long immune receptor screening process and to rapidly design synthetic receptors with our own hands that can recognize evolving pathogens in the field. If successful, durable genetic resistance will be feasible, as it is difficult for pathogens to overcome resistance when there are many functional immune receptors! Durable resistance means extended lifetime of elite crops, improved quality and shelf life of plants, and more opportunities to enhance other traits. This advancement will be important as we will need to deal with global warming and rapid changes in pathogen pressure in fields.
For many years, I have not been looking up to or inspired by someone. Of course, there are great people out there in the world, who can be inspiration of my daily life. I have been pushing myself quite hard without any changes to encounter those people. I hope to find someone during the workshops!
Robotics and mechanical engineering - I am curious about automation process. Machine learning - I will build my own models once I have enough data. Astronomy and planetary science - for fun, but also, will we be able grow plants in mars and moon?
I have many different English names that I use when picking up coffee: Jordan, Kyle, James, and so on.
16
Anubhav
Sinha
Boston
Ed Boyden Lab, MIT
My goal is to systematically map the involvement of the peripheral nervous system in nearly every disease, and to design novel therapeutics that target this missing puzzle piece of human biology.
David Altshuler is someone I look up to, because he knew the right time to jump ship from an amazingly successful academic career to CSO at Vertex to put science to use to cure disease in humans. I am inspired by the strategic thinking in knowing when to transition and focus on human impact.
Another example is the comedian Conan O'Brien, who built an amazing team around him that has worked together on multiple shows over decades. I am inspired by the ability to build a team and work with that team over decades to accomplish something great, and hope to one day lead such a team.
Honestly, almost anything science/engineering-y.
When I was a toddler, I was bitten by a monkey in a zoo!
17
Rohan
Kumar
New Haven, CT
CS PhD @ Yale working on quantum computing, advised by Yongshan Ding. Fully funded by an NSF fellowship. Prev. @UChicago (Undergrad), Oxford Physics (Research), and Super.tech (Quantum Computing startup now acquired by Infleqtion). Will be @MIT in Spring 2025, working on ML for quantum computing.
Compute is our most valuable resource, yet we haven't fundamentally changed how we compute since classical computers. Every tech breakthrough in history has relied on binary computation. While this consistency enabled rapid growth, energy expenditure is soaring and will provably become problematic for important tasks (incl. ML). As humankind advances, we'll dedicate an ever-increasing share of our energy to compute. We urgently need new computational methods that offer fundamental efficiencies for current and future problems.
Quantum computing presents a promising solution to this challenge. However, quantum bits (qubits) are much more prone to noise, both in magnitude and complexity, than their classical counterparts. Two broad classes of solutions to this problem have emerged: Quantum Error Mitigation (QEM), which seeks to extract useful information from noisy quantum computers, and Quantum Error Correction (QEC), which aims to use extra qubits to correct errors as they occur. QEM alone is likely not powerful enough to achieve quantum advantage, and while QEC will likely enable fault-tolerant quantum computing in the long term, practical QEC is decades away. However, there is likely a rich set of techniques in the intersection of QEM and QEC that could enable quantum advantage on practical tasks within the next few years. This is what I work on - i.e., blending QEM and QEC techniques to overcome the limitations of both paradigms and achieve near-term quantum advantage.
My goal is to build a software suite to enable the device-tailored application of these techniques to real quantum systems, enabling both quantum hardware and quantum applications developers to accelerate the practicality of their work.
One of the people who introduced me to quantum computing is Pranav Gokhale, the CEO and Co-Founder of Super.tech (the quantum software company I worked at as an undergrad). He was the fastest CS PhD in the history of UChicago and produced a ton of commercializable research. He then built Super.tech and led a lean team of people to deliver a product that led to partnerships with government agencies and large corporations in the span of less than two years. He gave me the agency to contribute significantly to Super.tech and I am incredibly grateful to him for his mentorship.
Pranav is thoughtful and fast, in that order. He executes and leads super effectively, but he's always clear about what his over-arching vision is, and that is a powerful thing. I know this because every time I asked him why things were done a certain way, he had a super articulate answer, admitted where there were aspects of his reasoning that were tenuous/based on assumption, and invited me to share a different way of thinking. At the same time, he moved lightning-fast, especially for a first-time founder.
I love jazz and play the alto saxophone (though not as often as I'd like).
I have pet a wild pangolin (very rare).
18
Boqiang
Tu
Boston
MIT
We are building a transformative technology that measures protein activity in ultra-high throughput, which enables AI-driven engineering of next-generation therapeutics and industrial enzymes
Elon Musk is one of them. I like his persistent enthusiasm in building technologies with substantial long-term impacts. He stays focused under tremendous amount of stress from many sources. I also like how he made X the largest free speech platform which could hugely benefit our democracy in the long run. I would also like to focus on long-term vision and create net positive social impacts
Longevity, brain-computer interface, space exploration
I lived in Alaska for 4 years!
19
Vikram
Sundar
Boston
Sculpting Evolution Lab (Kevin Esvelt), MIT
(for all of these questions, read Bo's answers as well for context.)
We aim to make protein engineering easy by combining large quantities of data generated by novel high-throughput assays and the most high-powered machine learning available today. This will allow us to engineer very specific proteins like proteases that can cut arbitrary sequences very accurately, which would profoundly impact the fields of biomanufacturing and medicine. We are also thinking about applications like gene editors and other enzymes to which our platforms can be easily extended.
Deep tech/underexplored solutions for climate change, pandemic prevention
I'm an avid classical pianist! Check my YouTube if you want to see my performances.
20
Matthew
Szedlock
Stanford University (Palo Alto, CA)
Zheng Lab, Stanford University (PhD student). Previously worked at Soaring Co (drone startup based in Southern California) as a lead mechanical engineer. BS in Mechanical Engineering from Caltech.
I currently work on developing methods to make lithium-ion battery recycling cleaner, more efficient, and more economically feasible through combustion-based pyrometallurgy. By using parts of battery cathodes as in situ reductants, we can more effectively recover precious materials such as lithium and cobalt without harmful carbon additives and reduce the need for toxic solvents. My goal is to help create a future where lithium-ion batteries are part of a fully circular economy which reduces our reliance on mining precious metals and makes electric vehicles and other forms of stationary energy storage far more affordable. I hope that this will help accelerate the green transition and unlock a number of other technologies which are currently unprofitable or supply-chain limited.
Someone I look up to is my dad. He originally inspired me to continue my education with a PhD despite not having an extensive technical background and has worked his whole life to provide me with the opportunities that I've been afforded. My dad has a really strong work ethic and stoic outlook on life which inspires me to maintain the same even-keel approach to my future career and when life gets more stressful.
I'm very interested in biotech, especially from a materials standpoint. I'm also curious about the aerospace industry, robotics, and 3D-printing.
I'm a huge baseball fan, and have been playing the game almost my entire life.
21
Lucien
Viala
Boston
Tesla, Imperial College
I currently work in aerodynamics at Tesla, shaping the vehicles of tomorrow to be the most efficient on the road.
I have a vision of a world where scientific and engineering progress is faster, bolder and solves important problems benefiting everyone. I hope we get to the point where anyone has the chance to contribute their ideas and solutions.
I’m inspired about Elon Musk as an entrepreneur and engineering visionary. Despite his character flaws, his ability to have a vision of the future, and no matter the difficulty, materialize the vision into reality is impressive.
His ability to take technical risks and have them pay off is unrivaled.
His ability build and steer an organization from vision to product is a skill that I look up to.
There are few more gifted deep-tech entrepreneurs than him.
Robotics and applied AI for robotics, policy for a prosperous future (economy, energy, construction, taxation etc…), Energy, the future of compute, genetics… You’ll be hard pressed to find something I am not curious about.
Depending on which test, I can ace or immediately fail a color blindness test. Eye doctors are left clueless.
22
Muntathar
Al-Shimary
University of California Berkeley
Doudna and Savage Labs UC Berkeley
Bacteriophages are in a constant arms race with the bacteria they prey upon, leading to the evolution of creative and novel enzymatic functions. Many of biotechnology’s most essential proteins have been sourced from bacteriophages; however, these proteins typically come from the most well-studied phages. Despite this, there exists a vast, unexplored diversity of proteins within other phages that has yet to be tapped.
Two major barriers hinder this exploration: the first is the bioinformatic discovery and isolation of these phages, and the second is the ability to study them in high-throughput—or in some cases, any throughput—systems. To overcome these challenges, we have developed a method for high-throughput characterization of phage genomes, regardless of whether they are ssDNA, dsDNA, ssRNA, dsRNA, or even form novel structures to conceal their genomes. By targeting phage genes at the RNA level, we have opened up a new frontier for phage characterization and gene discovery.
I am by no means religious and not a fan of sports, but as a fellow Kentucky native, I have to say that Muhammad Ali stands out to me as an extraordinary figure. Ali is defined by a few exceptional qualities: courage and conviction, charisma, resilience, and determination.
Ali was a man of deep principles, willing to make significant sacrifices for what he believed in. His refusal to be drafted into the Vietnam War, citing his religious beliefs and opposition to the conflict, led to his being stripped of his boxing titles and a five-year ban from the sport at the peak of his career. This stance, though highly controversial at the time, later earned him widespread respect as a symbol of resistance and integrity. What makes this even more remarkable is that, as a famous figure, he wouldn’t have been on the front lines; his role would have been largely symbolic. Yet, he was willing to throw everything away for his principles, showing a level of commitment that is truly inspiring.
Ali was also a brilliant communicator and self-promoter. He understood that people are drawn to narratives, stakes, and above all, entertainment. His poems and speeches are still iconic today for these reasons. He knew how to captivate an audience, turning his press conferences and interviews into events in their own right. His ability to weave words into powerful messages was unparalleled, making him a master of both the spoken word and the sporting arena.
After losing his titles and being out of the ring for five years, Ali made a meteoric return, displaying incredible resilience and determination. His comeback, culminating in regaining the heavyweight title, is one of the greatest stories in sports history and a testament to his unyielding spirit.
But above all, what I respect most about Muhammad Ali is how he used his platform. His contributions to social justice and civil rights are often overlooked. As one of the most visible Muslims in the United States, his words carried immense weight. After 9/11, Ali spoke out against violence and bigotry, urging understanding and peace in a time of heightened tension. His commitment to using his influence for good, whether advocating for civil rights or promoting humanitarian causes, is a legacy that transcends boxing and continues to inspire people around the world.
It depends on what you mean. I'm curious about an exceptionally wide range of topics. Scientifically, I'm interested in neuroscience and the emergent properties of consciousness, protein evolution and the acquisition of domains through evolutionary history, creating protein allostery, genetic engineering in broad terms, the genetics of fungi and slime molds, DNA origami, and protein discovery.
I am banned from entering Kuwait on the charge of witchcraft
23
Trent
Weiss
Cambridge, MA
MIT, Brushett Lab PhD Candidate (5th year)
My work focuses on developing advanced lithium-ion battery cell architectures that address many of the current limitations in such battery technology. Rather than relying solely on new materials, our approach leverages an engineering perspective to overcome fundamental issues related to mass and thermal transport. This strategy has the promise of enhancing both the performance and lifespan of lithium-ion batteries, making them more effective and reliable.
Our goal is to accelerate and expand the adoption of energy storage solutions for electric vehicles and grid applications while unlocking new possibilities for battery use in sectors like trucking and drones. We envision a future where energy is more sustainable, accessible, and reliable, with solutions that seamlessly integrate into modern infrastructure to create a more resilient and adaptable energy ecosystem.
In the entrepreneurial sphere I look up to Elon Musk for his relentless drive to push the boundaries of what’s possible tackle some of the world’s most complex challenges. I’m inspired by how he built multiple companies that not only revolutionized their respective industries but also fundamentally changed the way we think about sustainable energy, transportation, and space exploration.
What inspires me most is his willingness to take risks and his unwavering commitment to his vision, even in the face of significant skepticism, criticism, and setbacks. He is able to balance bold, long-term thinking with practical execution. His focus on first principles thinking—breaking down complex problems to their most basic elements and building up solutions from there—is a mindset I try to apply in my own work. He challenges established norms and reinvents them, demonstrating a unique approach to problem-solving and innovation.
While my focus is on electrochemistry and batteries, I'm broadly interested in any technologies/areas focused on the climate
I have a twin sister
24
Ravi
Lal
Pasadena, CA
Currently I am a graduate student in the Arnold lab at Caltech. Previously I performed an internship at Google X. I performed undergraduate research in the Keasling lab at UC Berkeley.
I am a PhD student in the Arnold lab at Caltech working on the evolution of enzymes to improve their capability to perform synthetically challenging chemical transformations. My research currently is most focused on the development of wet lab protocols which generate protein sequence-function data efficiently for integration with machine learning methods which could be used to accelerate the directed evolution process. I hope that this research and any subsequent research that I perform will play a part in the growth of the bioeconomy. I envision a future where many of humanities chemical needs have been made more sustainable as our understanding and ability to control biological systems improves.
The person I look up to the most is my father. He is an engineer as well and growing up with him I learned the importance of the thinking about unorthodox solutions to humanities problems. He also taught me the importance of preserving our planet and that it’s our job to come up with the ideas to keep it healthy. I have seen him work as an academic, a program manager at DARPA, and an entrepreneur, helping me to see that you can be productive in many different areas throughout your life.
I am curious about drug discovery, laboratory automation, and the application of recent breakthroughs in analytical chemistry.
I once accidentally hiked up to the highest point in Joshua Tree.
25
Yang
Zhong
Cambridge, MA
Device Research Lab (led by Evelyn Wang), MIT
The current water infrastructure is unsustainable – it contributes 2% of global greenhouse gas emissions, and yet 80% of wastewater is discharged untreated due to a lack of cost-effective solutions, posing a serious threat to our environment and health. I want to fill this gap by turning wastewater into freshwater, clean energy, and fertilizer, transforming the existing water infrastructure.
Elon Musk. As an engineer and physicist by training, I appreciate his first principles thinking.
Building, biomass utilization, carbon capture, AI
In addition to the PhD that I expect to receive later this year, I have two bachelor degrees and two master degrees.
26
Kathleen (Katie)
Sicinski
Pasadena, CA
I received my PhD in Chemistry from Tufts University in 2021. My thesis focused on developing novel chemical methods to enhance the metabolic stability of therapeutic peptides in the GLP-1 peptide family, which includes hormones like Ozempic. This work resulted in a start-up company Velum, Inc founded by my PhD advisor Prof. Krishna Kumar. During my PhD, I had the privilege of representing Velum at the Tufts University $100k New Ventures Competition, where we secured 3rd place. After my PhD, I worked as a scientist for a start-up biotech company, PepGen, Inc. At PepGen, I saw the company go from series C fundraising to its initial public offering in 2022 and advanced into clinical trials for the treatment of Duchenne muscular dystrophy. I was responsible for transitioning laboratory operations from Oxford, UK to Boston, MA and discovering new bioconjugation methods for delivery of therapeutic oligonucleotides into target cells. I then moved in 2022 to my current position at California Institute of Technology as a NIH Ruth L. Kirschstein NRSA Postdoctoral Fellow in the lab of Prof. Frances Arnold. In my current position, I utilize the powerful tools of directed evolution for protein engineering and apply machine learning methods to accelerate wet-lab discoveries. This is where I met my current co-founder, Ravi Lal. We have been working together to fast-track the iterative process of protein engineering by incorporating machine learning and high throughput analytical tools to deliver sustainable biocatalysts for the synthesis of molecules.
My current work in the Arnold lab focuses on evolving and engineering enzymes to transform low-cost chemical feedstocks into a variety of valuable synthetic building blocks. Throughout my project, I have streamlined the protein engineering process by integrating machine learning methods, enabling faster evolution of biocatalysts while reducing resource consumption. My ultimate vision is to see biocatalysts become the standard in chemical synthesis. I aim to make these engineered enzymes more accessible so that chemists can easily transition to greener, more sustainable alternatives to traditional chemical synthesis.
I look up to my current postdoctoral mentor, Prof. Frances Arnold. I am impressed with her management style, efficiency, vision, and what she has accomplished despite hardships in her personal life. I am inspired by Tina Boville, an alumna of the Arnold lab, who successfully founded Aralez based on her postdoctoral work at Caltech. Watching her and her company grow has been an inspiration, affirming that it is possible to be a successful female entrepreneur in a deep tech start-up.
I am interesting in learning about the financial aspects of starting a company and/or investing in others.
I am a yoga teacher! :-)
27
Paul
Weitekamp
Los Angeles
SpaceX
The product I envision is a low cost and high cycle efficiency Compressed CO2 energy storage system for the grid that is deployable at scale.
After working for Elon, I've always been very impressed by his ability to attract and retain top engineering talent.
Aerospace, grid energy storage, engine and pump design, Artificial Intelligence, and Nuclear Reactors
I was voted biggest risk taker in High School
28
Simon
Roy
Quebec City, QC, Canada
Former Tesla and Lyft embedded systems engineer. Currently independent.
I build robots and electric powertrains. We are facing major issues such as labour shortage and carbon emissions, where these technologies can help. I'm exploring various sectors where there are urgent needs and viable business models.
I'm obviously biased for Elon Musk :-D
His grit and rationale mind.
Psychology, investing and space!
I cycled across the USA during the summer before my masters. I do crazy things when I'm bored.
29
Sierra
Lore
San Francisco
Buck Institute for Research on Aging
I am currently working on biology of aging research to better understand the current state of the longevity field and the current challenges of extending healthy lifespan. My vision of the world is to to see significant maximum healthy lifespan extension (at least 50%) to reduce suffering and give people more time to spend with loved ones.
I look up to each of my parents in different ways. My mom in terms of how to treat people and what to value in life and my dad in terms of believing anything is possible and making it happen. I am really grateful to have grown up with them both as role models.
neurotech (specifically fUS BCI and spine-computer interfaces) and space exploration
I love making homemade ice cream (salt and straw inspired flavors)!
30
Zach
Rosenthal
SF
Birdwood Therapeutics
New induced proximity modalities, beyond degraders, will revolutionize medicine. I aim to develop those modalities and unlock the ability to discover small molecule inducers of proximity through high-throughput screening
- Josh Boger, founder and former CEO of Vertex Pharmaceuticals. The entire world - including established professors at prestigious universities, leaders of pharmaceutical companies, etc. - thought what he wanted to do (structure-based drug design) was impossible. Even Boger's team had their doubts in the early days!! No one believed in him. But he was right. And now virtually all of drug discovery is done this way. I'm inspired by his resolve & commitment to his vision in the face of overwhelming "consensus" against his ideas.
I'm reminded of this Derek Lowe blog post - https://www.science.org/content/blog-post/so-tell-me-about-idea-yours-again - "everything seems impossible until it is done...."
- computational approaches for generative small molecule/protein discovery; - immunology/immuno-oncology; (sort of related to my research but sort of not) aging/longevity biology
I played poker semi-professionally throughout college/for two years after I graduated
31
Dhruva
Katrekar
Mountain View
Currently at Arc Institute. Previously Shape Therapeutics and UC San Diego.
My vision is to make life-saving medications accessible to everyone via the creation of innovative, affordable therapeutic options. I feel like the gut microbiome can be specifically altered to produce such low cost therapeutics directly within a human.
I deeply admire my grandfather. Starting with very little in his childhood, he became an engineer and supported a large family. He had a remarkable ability to get things done, regardless of how daunting they seemed. What I most respect about him is his optimistic attitude, his curiosity, and his continuous pursuit of knowledge well into his late 80s.
Climate tech, psychology, history
As an alternative career path, I would like to be an Antarctic explorer or a professional tennis player.
32
Michael
Massen-Hane
Boston, MA
MIT
I'm a Postdoctoral Associate working on new carbon dioxide capture systems that have the potential to be widely and inexpensively deployed. I'm working towards decarbonizing our power generation and industrial sectors to secure a safer and sustainable planet for future generations.
Dr. Robert Zubrin is someone I look up to and am inspired by. He saw an issue with the way NASA had planned human space exploration in the 90s, and designed and partially derisked an alternative concept which was cheaper and would land boots on Mars more quickly. His plans inspired and have been adopted by SpaceX in their Mars ambitions, and through The Mars Society, has recruited several to the cause of propelling human space exploration. I appreciate the clarity of his vision, and the effectiveness with which he is able to communicate it and inspire others.
I am interested in the pursuit of deploying human settlements on Mars and ultimately terraforming the planet for human habitation. This curiosity drove me towards chemical engineering, a knowledge set that enables planet level transformation.
I've never broken a bone.
33
Jacob
van de Lindt
Boston
MIT
I aim to build a company that substantially helps reduce the emissions of the maritime industry, as well as works towards ocean sustainability causes. The key technology piece is utilizing over fifty years of engineering excellence in the fission industry, as well as its new advances, and combining these with recent breakthroughs in fusion energy technology to produce a fleet of fission-fusion hybrid powered cargo container ships. This combination of technologies would play to the strengths of each: lowering the risk/physics requirements of the fusion plasma, while at the same time potentially reducing the nuclear waste of the fission system, and enhancing its overall safety.
I really look up to Bob Mumgaard, the founder of Commonwealth Fusion Systems. He graduated from the same program I am in a decade prior to when I will, and launched a fusion company that has secured over a billion dollars in funding. His ability to go from graduate student to founder/CEO and see it through a massive period of growth are all skills and achievements I hope to recreate in my own venture.
Yes! I'd love to interact with people interested in biotechnology and aerospace. Both are fields with similar requirements in terms of risks and engineering difficulty.
I am a second degree black belt in taekwondo
34
Sasha
Gao
Boston
Brushett group at MIT
I look up to my mom, a successful business women in China. She is always so determined and dedicated to her work.
Developing soft skills (leadership, influence skills, public speaking, etc.). I'm also very into skiing and piano and always seek to become better.
I hate chocolate and I am afraid of dogs.
35
Marika
Ziesack
Boston
Current: Senior Scientist at Wyss Institute at Harvard University; Past: CTO at Circe Bioscience Inc.
I'm exploring the concept of refinery-inspired biomanufacturing, centered on three key ideas: using C1 feedstock from waste sources, super-charged bioprocessing to convert feedstock into products, and a biological downstream approach for waste-free purification. I'm also focused on partnership models and strategies for rapid revenue generation. This approach aims to create a sustainable, efficient system for producing sustainable materials from low-cost, waste-derived inputs.
I look up to Shreya Dave from Via Separations. She built a deep tech business from scratch with a lot of grit. She included excellent investors on her team while also taking advantage of non-dilutive funding. She seems to have a great relationship with her team and is willing to share her experiences with other founders.
Sports (Taekwon-Do, running, rock climbing), wine (I plan to retire on a bio-enhanced vineyard, ask me about it ;)), languages (currently learning french and spanish)
I am an Alien of Extraordinary Ability
36
Stepan
Tymoshenko
Sacramento, California
Mammoth Biosciences Inc., ex-Zymergen, PhD and post-doc from EPFL and University of Geneva (Switzerland)
With my co-founder, we want to turbo-charge cell-free production by providing abundant and cost-effective energy substrates. Our success will be a paradigm shift in making biomolecules. Our energy substrates will enable cell-free systems to compete with inherently less efficient fermentation. Our innovation is the key to cost-effective enzymatic production of DNA, RNA, proteins, other high-value biomolecules, and biopolymers without growing biomass.
Elon Musk, the controversies of his personality aside, is an inspirational example for me. His professional path of status quo disruptor and the ability to engage/motivate people to achieve the "impossible" is most fascinating.
Biophysics, space travel, and underwater ecosystems
I speak 4 languages, neither of them perfectly
37
Nicolas
Sawaya
San Francisco
Azulene Labs (previous: Intel Labs; Harvard @Aspuru-Guzik group)
I want to increase the accuracy of chemical/materials property prediction by 10-50x. I have strong theoretical reasons for believing this is possible. This would greatly reduce R&D costs, as it would allow us to entirely replace many laboratory experiments.
Marie Curie, Christopher Hitchens, Richard Feynman, Bill McKibben. They were/are stubborn & independent thinkers.
Climate policy; electrification of the grid; decarbonizing heavy industry.
I have a (very small) collection of old or rare--oldest is a medical book from 1660.
38
Neel
Parikshak
New York City Area
Regeneron, UCSF, UCLA
Generate and leverage large omics data and apply machine learning to identify new therapeutics in neuroscience.
Jeff Bezos. I find his early life background, conviction for his vision, ability to execute, and the company culture he created all very inspiring.
Pure mathematics, science fiction, food science
Just had 2nd kid! A few weeks ago
39
Nelson
van de Lindt
Bend, OR
NuScale Power, Elementl
I want to reshape heavy polluting industries through the use of high capacity renewable energy sources to reduce emissions. My goal is to build an energy abundant and secure future while not sacrificing efficiency or the environment.
My brother inspires me. His constant belief that we can change the world together has been a constant influence on my own successes since I was 7 and has led me to double majoring and now attending Harvard Business School.
The integration of tech into our startup. Specifically, how we can leverage a software product in the earlier stages.
I have a second degree black belt in taekwondo
40
Jolyn
Gisselberg
Foster City, CA
Currently working on the startup, but previously at Google X and Stanford.
My cofounder and I believe we can fundamentally change how biochemicals are made by unlocking cell-free production. We are developing a unique way to produce energy substrates which is potentially orders of magnitude cheaper then current market rates. This is the missing key needed for synthesizing biomolecules at scale without needing to rely on cells.
I tend to look up to scientists. When thinking about getting science out into the world I really look up to people like Jennifer Doudna who was able to see beyond the basic science her team was doing and think how their research could be applied more broadly, transforming so many fields at once.
I'm really exciting to see how people are thinking about AI beyond protein modeling.
I make stained glass in my spare time.
41
Neil
Tay
San Francisco
UCSF
I develop molecular technologies that enable high throughput studies of the human immune system. I seek to combine these technologies and computational approaches to greatly expand our understanding of the immune system and create novel immunotherapies and cures for diseases like cancer and autoimmunity.
Albert Einstein. With nothing more than his mind he changed the way we view the world in multiple ways and that is nothing short of incredible.
Physics, astrophysics, and space travel.
I probably would be a physicist in an alternate timeline.
42
Justin
Bult
Fremont, CA
Currently work at Tesla in Cell Manufacturing. I previously worked at Corning Glass, Dow Chemical, National Renewable Energy Laboratory, and NASA MSFC.
To build a lasting company that can build hard tech to improve the energy landscape in North America. The battery industry is dominated by the APAC region and for North American companies to succeed they require disruptive approaches that will work through scaling. I intend to provide that technology and approach.
I admire those who struggle, do not give up, do not complain, and persevere.
governmental structures
I really enjoy cowboy boots, but I'm not from Texas.
43
Jaime
Roquero Gimenez
San Francisco
Just quit my job at Adela Bio to focus on building.
I hope that multi-cancer early detection becomes one day reality. As of now, the diagnostics industry has failed. I am approaching this from a first-principles approach, working backwards from what a final product should look like. This means using ML at the right places in the product development, and using PCR as the lab workhorse. I am building a computational pipeline to prototype this idea in the most lean way.
I have a couple close examples of people that do not give up. No matter whether it is big or small, they do things thoroughly even if they face long odds. Sometimes I get easily discouraged, and their example pushes me to keep working and exploring.
I am curious about the local history.
I recently got into making my own jam. I may one day start a (non-VC-backed) jam preparation venture if I get tired of fitting stats models.
44
Younhun
Kim
Boston, MA
Current: Mass General Brigham (Previous: MIT)
I currently work on genomics-related computational/statistical methods for the microbiome. I think that the microbiome is a large missing link in our understanding of health. I want to build algorithms (with or without AI) to understand it better and design non-invasive treatments for some of humankind's persistent ailments.
My parents inspire me the most. We are an immigrant family, and to have seen them work hard over the years instills in me the value of escaping my comfort zone and taking risks.
1. Biological/Bacterial engineering, 2. Multi-agent systems in robotics, 3. Statistics and math that hasn't yet made their way into practice, but show promise, 4. anything related to tackling the impending climate crisis. 5. STEM-oriented outreach opportunities
My wife and I got married last year. We went to South Korea for our honeymoon!
45
Utkarsh
Sharma
Cambridge, MA
Postdoc at Mass General Brigham (Brigham and Women's Hospital))
One (bad) way to program a computer is by changing the melting point of copper wires or doping of silicon transistors. In contrast, high level intervention via programming languages offers robust, precision control and prevents unintended side-effects. Medicine needs to move in the same direction-- precise, high-level interventions that do not bypass the checks and balances of the human system.
The (gut-)microbiome holds this potential, and consequently for the first time we see the promise of a true cure for many chronic ailments. We are building Microbial General Intelligence (MGI), an AI that will understand the microbiome with context, allowing the development of microbiome therapeutics.
I admire Gautama the Buddha because after practicing intense austerities, he had the humility and sense to choose a very simple solution when he came across it, even though it meant acknowledging that he had been wrong all along.
I also admire the work of Elon Musk in the sense that he picked seemingly impossible projects, but through vision and commitment he showed the world a new reality.
solutions for climate change; urban and rural planning for our large population; solutions for overhauling our bloated financial system; human psychology and its pitfalls; pure math and the nature of numbers; the nature of reality.
After my PhD I took a year off and went to India to live in a ashram and meditate. I also did some farming during that time.
46
47
Karl
Krauth
Palo Alto, CA
Currently a postdoc at Stanford University in a microfluidics lab, previously I did my PhD in machine learning at UC Berkeley.
In 20 years, microfluidics will be as impactful as the microprocessor. General-purpose microfluidic chips will be running in every biotech lab, generating petabytes of data to power the next generation of AI models, leading to exponential progress in therapeutics research.
As a first step toward this vision, I’m creating a programmable microfluidic device that can measure 100 million protein-protein interactions in a single experiment, which will be 1 million times cheaper to run than contemporary methods. I’m planning to use this device to provide large-scale datasets for pharmaceutical companies and to train my own machine learning models to guide protein design.
Robert Noyce: the co-inventor of the integrated circuit and co-founder of intel. He was both a skilled technologist and a talented entrepreneur who was able to mobilise the entire semiconductor industry to cooperate for a better future.
He was also earnestly curious about all fields of human endeavour and took delight in learning, which I really value.
Right now I'm particularly curious about mechanical engineering/manufacturing, chemistry, optics, and computer graphics.
My full name is so long it regularly crashes the check-in system at airports.
48
Daniel
Moore
Costa Mesa, CA
Currently at Anduril Industries, and have been for a few years. Before that I was at an EV startup, and doing prototype engineering for Fiat Chrysler before that.
My work thus far has been disruptive to the US Military Industrial Complex, but the moonshot I see is to build opportunity to build an American Tech Company that democratizes rugged, cutting edge hardware.
My late Uncle inspires me. He passed away this August. He was a kind person, incredibly humble, never gave up on his dreams, and chose to excel at his field, which was General Surgery. Those are nice things to say, but he is someone who inspires me to work hard and do it for the good of society, and to keep fighting to improve the human condition, rather than to simply improve my own life.
For areas of study, I’m curious about Biology, Mathematics, and Applied Physics (think Fusion or Quantum Computing)
I’ve won two sailing championships as a captain, and I’ve received a trophy in an international yacht race!
49
Alex
Powers
Palo Alto
Stanford (I just finished PhD from Stanford, I still do research there)
My vision is to use the 3D dynamic structures of proteins to rationally design safer, smarter drugs. Most drugs work by binding to proteins like a key fitting into a lock. Thanks to incredible advances just in the last few years, we can now rapidly determine the 3D structures of almost any protein. But these structures are still just static snapshots of very complex, dynamic systems; my work goes a step further, leveraging protein flexibility and motion to uncover hidden opportunities for drug design. For example, we might discover a drug binding pocket that only appears when a protein changes shape in response to particular cellular signals. To do this, I’ve been developing new computational tools, that combine atomic physics simulations and AI. By targeting more specific protein states and discovering concealed drug binding pockets, we can unlock best-in-class medicines that are more precise and effective, with fewer side effects even for well-studied targets. One of my current areas of focus is to create less addictive pain medications with minimal side effects for long-term chronic pain treatment, which could transform patient care for a very common condition.
Carolyn Bertozzi – professor at Stanford, nobel prize winner (also first out LGBT nobel prize winner). She’s an amazing scientist and entrepreneur but also a natural leader who inspires and guides everyone around her. She also strives to have a real tangible impact on the world during her lifetime, using chemistry and engineering to improve human health.
Gene editing, neurodegenerative diseases, microbiome, microfluidics, robotics, educational technology, productivity
I enjoy oil painting and pencil drawing. I once thought I would go to art school.
50
Laura
Vasquez Bolanos
San Francisco
Loyal longevity startup, formerly Cornell, UCSD bioengineering
I want to build an intervention that slows down reproductive organ aging and extends our reproductive window. Givings us more time to decide on whether to build a family, build a company or anything else our heart’s desire as lifespans continue to lengthen. I believe there are a few different paths to this goal, some longer than others, I would like to optimize for the quickest path to approval. This may look like leveraging accelerated regulatory pathways, different primary/secondary endpoints, and/or repurposing existing drug and safety profiles.
Celine, CEO of loyal, inspires me day in and out, I love working for her and watching her build Loyal. The solo founder is a grind and she manages so much uncertainty with pure confidence, not necessarily in having the answers for everything but in being confidence she can figure it out however need be. Being a young woman in biotech in the valley is not easy and she goes out and raises like an absolute pro pushing us forward at all times. Also about 9 months ago she told me she thought I would make a great founder, so that really empowered me to view myself in a similar way. Since then I can tell how my own shift in my own believe has changed and I am excited to continue growing into that reality.
I am curious by psychedelic therapeutics and our understanding of the brain. I wonder sometimes if we’ll figure out how to hack our subconsciousness and the future of Pharma is less small molecules and more regeneration by targeting the right region in the brain to heal yourself. Also curious to see the rate of biology learnings as AI progresses and what data collection is going to be key for that as well.
i love love lovveeee cooking, a wide range of ethnic cuisines including colombian
51
Gina
El Nesr
Bay Area, CA
Stanford University
I’m a rising fourth year biophysics PhD Candidate at Stanford University working at the intersection of deep learning x enzyme design, with a broader interest in biological solutions for climate change and human sustainability. My research at the moment involves developing methods for designing new-to-nature enzymes for functions and reactions that currently do not exist; and if they do exist, making them more efficient.
Besides my parents, I look up to the Arab women who are slowly paving the path and setting an example for minorities in the Middle East founding companies. Rana El Kaliouby comes to mind. She's a powerful woman who turned her PhD into a company, and has since become more than just a founder for a lot of people.
Everything; but specifically climate, sustainability
I'm a national level olympic weightlifter! I can back squat 365lb and front squat 285lb.
52
Norh
Asmare
Atlanta, GA
Biomedical Microsystems Lab @ Georgia Tech
I want to transform therapeutic cell manufacturing testing from a labor-intensive, fragmented science into an autonomous, massively scalable manufacturing workflow
Not necessarily someone I look up to, but a former colleague (10+ years ago) who had traits I admire to this day. He was so consumed with his work, always innovating new and elegant ways to build things. Few people can suggest changes to his work since it was often so complete and well thought out. After our team spent 2+ days non-stop fixing a bug for an important investor demo, while the rest of us were overcome with relief, he was only interested in how we managed to fix it, with absolutely no change in his demeanor. An intense focus undisturbed by neither impending doom nor euphoria.
Soccer tactics.
I play guitar 🤘
53
Chad
Wilson
Boston
MIT
Solutions to water scarcity
finance
I compete gymnastics
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