Shreyans Jain

Research Fellow at LASR Labs

Bengaluru, Karnataka, India
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Summary

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Shreyans Jain is an interpretability researcher and experienced data scientist with 8+ years building production ML systems—OCR, search, recommendation, and time-series forecasting—out of Bengaluru. He publishes and maintains open-source tooling for visualizing neural network training dynamics (ICLR 2025 blogpost and a public GitHub repo) and contributes to libraries like Minari and AgileRL. His recent independent research includes arXiv work and accessible explainability write-ups that bridge practical model diagnostics with theoretical insights. Previously he delivered analytics and ML solutions across enterprises like GEP, BookMyShow, Hotstar and Fractal, and has applied psychometric frameworks to evaluate LLM behavior in applied settings. A civil-engineering graduate by training, he pairs strong applied engineering chops with a knack for clear visual and experimental communication of model behavior.
code8 years of coding experience
job6 years of employment as a software developer
bookBachelor of Technology (BTech) Civil Engineering, Bachelor of Technology (BTech) Civil Engineering at Malaviya National Institute of Technology Jaipur
bookHigh School Mathematics and Statistics, High School Mathematics and Statistics at Maheshwari Public School
languagesEnglish
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Github Skills (18)

algorithms10
gymnasium10
reinforcement-learning10
datasets10
evolutionary-algorithms9
deep-reinforcement-learning8
hyperparameter-tuning8
multi-agent8
machine-learning8
automl8
pytorch7
hyperparameter-optimization7
huggingface7
deep-learning7
python7

Programming languages (4)

MDXHandlebarsJupyter NotebookPython

Github contributions (5)

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Visualizing Training Dyanmics of a Neural Network
Contributions:3 reviews, 11 PRs, 35 pushes in 11 months
neural-network
shreyansjainn/Minari

May 2023 - Nov 2023

A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities
Contributions:38 pushes, 8 branches in 5 months
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