Hello! My name is Abhijit Gupta, and I am a junior at Yale University, majoring in Computer Science with a certificate in Statistics and Data Science. At Yale, I have conducted research with the Interactive Machines Group, and previously lead the Tech Team for YHack and contributed to the Yale Computer Society and Yale Entrepreneurial Society. I have previously interned with Jane Street, Sentry.io, Gatherly, and RTI International. I will be interning with Jane Street in Summer 2022 and joining full-time in Summer 2023. In my free time, I work on side projects including GitHub Trends and Statbotics.io. Please feel free to reach out!
Abhijit Gupta


During my time at Yale, I have taken two gap semesters to work in industry and further my software skills. In total, I have completed four internships with one upcoming in Summer 2022. I have also published two research papers while at Yale.
  • Quant Trading @ Jane Street (NYC, Summer 2022): Upcoming Internship
  • Software Engineering @ Sentry.io (Remote, Fall 2021): Worked with the Data Team based in San Francisco building ETL pipelines for 100M+ daily messages from the Sentry.io platform. Used Apache Kafka, PySpark, GCS, AirFlow, BigQuery, and DataDog to prototype a batch processing pipeline with increased throughput and scalability.
  • Quant Trading @ Jane Street (NYC, Summer 2021): Attended classes, participated in mock-trading, and worked on two data analysis projects with trading desks. Further details omitted due to IP restrictions.
  • ML Researcher @ Yale IMG Lab (Yale, 2020-21): Built a deep learning pipeline analyzing social group phenomena for human-robot interaction using graph neural networks, improving metrics over state-of-the-art heuristic baselines. Paper available here.
  • Software Engineering @ Gatherly (Remote, Fall 2020): Spearheaded data analytics initiative analyzing 1M+ user actions to extract actionable insights for online event hosts. Implemented an automated payment system using the Stripe API with subscriptions, discounts, and tiered pricing. Used AWS, NodeJS, ReactJS, and Stripe.
  • Data Analyst @ RTI International (Remote, Summer 2020): Designed campus monitoring dashboard to visualize temporal building ocupancy. Implemented automated demand prioritization system for BI team, reducing manual labor by 80%. Used Microsoft SQL Server, Power BI, and Excel.
  • ML Researcher @ Yale LILY Lab (Yale, Fall 2019): Trained machine learning model to classify salient events in 2D physics simulations with 91% accuracy. Contributed to research paper studying implicit physical reasoning in NLP. Paper available here.


I am currently a Junior at Yale University, graduating in May, 2023. I am pursuing a major in Computer Science and a Certificate in Statistics and Data Science.

Relevant coursework

CPSC 223: Data Structures, CPSC 290 Directed Research, CPSC 323: Systems Programming, CPSC 366: Intensive Algorithms, CPSC 452: Deep Learning, CPSC 327: Object Oriented Programming, CPSC 447: Intro to Quantum Computing, CPSC 426: Distributed Systems, MATH 230/231 Vector Calculus and Linear Algebra, MATH 244 Discrete Mathematics, S&DS 230: R Programming.


Yale Interactive Machines Group, YHack Organizing Team, Yale Computer Society, Yale Entrepreneurial Society Team


Recently, I have worked on GitHub Trends, Statbotics.io, Quickbites, research, club projects, and this portfolio website. More details coming soon!