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Humans of 5050 C5
5050 C5
Michael Nitzsche
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.
Neal Amin
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.
Joseph Mooney
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).
Zewen Zhang
Apple
leverage data to systematic design battery materials and manufacturing
Chao Cao
Carnegie Mellon University / Boston Dynamics AI Institute
Autonomous mobile robots that are useful in people's daily life
Sulin Liu
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.
Aditya Venkatramani
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.
Nils Burger
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.
Assaf Magen
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.
Jase Gehring
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.
Jason Zhang
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.
Sebastian Kenny
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.
Kwat Medetgul-Ernar
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.
Mariëlle van Kooten
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.
Kyungyong Seong
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.
Anubhav Sinha
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.
Rohan Kumar
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.
Boqiang Tu
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
Vikram Sundar
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.
Matthew Szedlock
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.
Lucien Viala
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.
Muntathar Al-Shimary
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.
Trent Weiss
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.
Ravi Lal
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.
Yang Zhong
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.
Kathleen (Katie) Sicinski
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.
Paul Weitekamp
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.
Simon Roy
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.
Sierra Lore
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.
Zach Rosenthal
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
Dhruva Katrekar
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.
Michael Massen-Hane
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.
Jacob van de Lindt
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.
Sasha Gao
Brushett group at MIT
Marika Ziesack
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.
Stepan Tymoshenko
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.
Nicolas Sawaya
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.
Neel Parikshak
Regeneron, UCSF, UCLA
Generate and leverage large omics data and apply machine learning to identify new therapeutics in neuroscience.
Nelson van de Lindt
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.
Jolyn Gisselberg
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.
Neil Tay
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.
Justin Bult
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.
Jaime Roquero Gimenez
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.
Younhun Kim
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.
Utkarsh Sharma
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.
Karl Krauth
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.
Daniel Moore
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.
Alex Powers
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.
Laura Vasquez Bolanos
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.
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