Abhijit Gupta is a Trader at Jane Street and a Yale University Computer Science senior with nine years of experience spanning quantitative trading, software engineering, and machine learning research. He’s shipped production-grade systems at Sentry and Gatherly, built scalable ETL pipelines with Kafka, PySpark, Airflow and BigQuery, and now applies that engineering rigor to trading. Outside work he develops projects like githubtrends.io — where he implemented the Python/FastAPI backend and a BigQuery template to power customizable GitHub profile cards — and maintains statbotics.io and hopscotch.nyc. His research on GNN explainability led to a NeurIPS 2023 paper (D4Explainer), and earlier leadership of a competitive robotics team demonstrates a rare blend of algorithmic depth and hands-on product delivery.
10 years of coding experience
3 years of employment as a software developer
North Carolina School of Science and Mathematics
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Yale University
🚀 Level up your GitHub profile readme with customizable cards including LOC statistics!
Role in this project:
Back-end Developer
Contributions:598 commits, 254 PRs, 423 pushes in 2 years
Contributions summary:Abhijit primarily focused on building the back-end components for a GitHub profile readme generator. They designed and implemented a BigQuery template and wrote core back-end logic using Python and FastAPI for user and repository data retrieval from the GitHub API. The contributions also involved creating API endpoints for fetching user data and integrating external services. The user also added features to create a new system for fetching and processing data.
Contributions:3 PRs, 85 pushes, 6 branches in 1 year 7 months
backend
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