Shital Shah
Principal Research Engineer at Microsoft
Sammamish, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolShital Shah is a Principal Research Engineer at Microsoft Research’s AI Frontiers Lab with 13+ years driving applied deep learning, reinforcement learning, computer vision and autonomous vehicle research into production-ready systems. Based in Sammamish, WA, he blends a long Microsoft engineering career—from senior developer to principal research roles—with hands-on open-source contributions such as work on microsoft/tensorwatch for ML debugging and visualization. His profile shows active engagement with the research community (Google Scholar) and practical tooling (GitHub, StackOverflow), reflecting a rare mix of academic rigor and production engineering. Not obvious from his title: he also contributes to public knowledge via Wikipedia edits and technical threads on Twitter, signaling a commitment to community-facing technical communication.
13 years of coding experience
21 years of employment as a software developer
Bachelor's Degree Electrical Engineering, Bachelor's Degree Electrical Engineering at University of MumbaiDiploma in Engineering Industrial Electronics, Diploma in Engineering Industrial Electronics at VES Polytechnic
Stackoverflow
65,868reputation
62.7mreached
340answers
40questions
pytorch
top-1%
cuda
top-5%
matplotlib
top-1%
debugging
top-5%
pandas
top-5%
gpu
top-5%
Github Skills (64)
algorithm10
data-visualizations10
pytorch10
javascript10
docker10
python10
matplotlib10
windows10
machine-learning10
data-visualisation10
cross-platform10
virtual-machine10
inheritance10
lodash10
deep-learning10
Programming languages (12)
Github contributions (5)
microsoft/tensorwatch
May 2019 - Jan 2021
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Role in this project:
ML Engineer
ML EngineerContributions:97 commits, 13 PRs, 54 pushes in 1 year 8 months
Contributions summary:Shital contributed to the development and improvement of machine learning models within the repository. Their commits include creating streams to observe variables during training and analysis, specifically focusing on plotting batch loss, analyzing training data and adding features to the logging and visualization pipeline. The commits also focus on the application of the model using a Lazy Logging approach, and the integration of tools.
pythonsciencedata-sciencemachinelearningpython-machine-learning
sytelus/CryptoJS
Nov 2013 - May 2018
Contributions:12 commits, 3 PRs, 3 pushes in 4 years 6 months
securecryptographycryptographichostedjavascript
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