Ankit Biswas
Data Scientist
Hyderabad, Telangana, India
Summary
🤩
Rockstar🎓
Top SchoolAnkit Biswas is a data scientist at Microsoft with six years of experience blending deep learning research and practical ML engineering, currently completing a BTech at IIT Roorkee. He focuses on reinforcement learning, computer vision and NLP, and pairs that research curiosity with hands-on web development and production-minded contributions. His open-source work includes concrete enhancements to the widely used Ivy project—adding TensorFlow frontend math functions, PyTorch decorators, and clearer docstring examples—demonstrating attention to both interoperability and developer usability. Prior internships at IISc, BotSupply and Microsoft, plus a short ML engineering stint at Unify, show a pattern of moving research ideas toward deployable systems. Based in Hyderabad, he brings a rare mix of academic rigor (9.16 GPA) and practical tooling experience that accelerates model adoption across frameworks.
7 years of coding experience
Indian Institute of Technology Roorkee
Github Skills (13)
pytorch10
tensorflow10
python10
testing10
numpy9
converter9
machine-learning9
deep-learning9
transcode8
functional-programming8
transpiler8
jax8
ivy7
Programming languages (6)
Github contributions (5)
unifyai/ivy
Jun 2022 - Oct 2022
Convert Machine Learning Code Between Frameworks
Role in this project:
ML Engineer & Test Automation Engineer
ML Engineer & Test Automation EngineerContributions:36 reviews, 7 commits, 36 PRs in 4 months
Contributions summary:Ankit contributed to the Ivy project by adding extensive docstring examples to the `gather` function, enhancing code clarity and usability. They also added and tested TensorFlow frontend functions, specifically focusing on the math submodule by implementing and testing various functions such as `log_sigmoid`, `reduce_max`, `reduce_min`, `reduce_prod`, `reduce_std`, `asinh`, `reduce_sum`, `reduce_variance`, and `scalar_mul`. Furthermore, the user implemented functions for `unsorted_segment_mean`, `unsorted_segment_sqrt_n` and `zero_fraction`. Additionally, the user added frontend array decorator functions to PyTorch.
machine-learningpythontensorflowpytorchnumpy
dsgiitr/RL_StockTrader
Apr 2020 - Apr 2020
Contributions:6 commits in 4 days
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