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Charmi Chokshi
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Charmi Chokshi
Experience

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Internships

Research Engineer Intern

Amazon Web Services (AWS AI) Vancouver, Canada
Duration: May 2022 – November 2022
Work done:
Model-based False Annotation Detection: Developed Metric-based and Gradient-based optimization techniques for doing Loss Analysis to flag noisy labelled data. Improved the teams’ Data Quality by 3% and Transformer-based Table Structure Prediction model’s Test Accuracy by 1%.
Built an end-to-end Annotation Correction Tool to update mis-annotations with ML-assisted features.

Machine Learning Intern

Logistixian Technologies Pvt Ltd (
Shipmnts.com
⁠
), India
Duration: January 2019 – June 2019
Work done:
Document Group Classification: Built an optimized and lightweight NLP model for classifying page into 250+ categories followed by page grouping module that completely discarded manual page-tagging task of users.
Developed low DPI document enhancement module, and multi-pass OCR for improvising character recognition.

Research Trainee

Indian Space Research Organisation (
ISRO
⁠
), India
Duration: May 2018 – August 2018
Work done:
Worked on the pipeline of Smart-cities mission of India to segment low-resolution satellite-imagery into urban and non-urban areas.
Unsupervised Semantic Segmentation: Trained an Encoder-decoder model with parallel depth-wise separable CNNs using TensorFlow & Keras on GPU.
Implemented Region Growing algorithm with progressive threshold and parallel processing for post-processingMachine Learning Intern.

Research Intern

⁠
CheckIt
⁠
, India
Duration: May – August 2017, 2018
Work done:
Artificial Generation of Images: Worked on Unsupervised Deep Convolutional GAN and Conditional GAN for generating artificial OMR Sheets for increasing training set.
Image Classification: Automated the OMR-Sheet checking process by implementing image registration techniques followed by CNN having human-level accuracy.

Intern

Office of the Academic Registrar, Ahmedabad University
Duration: January – June 2018
Work done:
Documented the SDLC process of the in-house ERP system.
Reduce the new user on-boarding time by 40% via producing video materials.

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