CV

My resume as a PDF

Education

Ph.D in Computer Science, University of Illinois at Urbana Champaign, Dec 2025 (expected)
M.S. in Computational Science and Engineering, Harvard University, 2020
B.S. (with Honors) in Computer Science & Applied and Computational Mathematics, California Institute of Technology, 2016

Work Experience

Permanent Positions

July 2016 - July 2018: Strat in Global Liquidity Products at Goldman Sachs
- Modeled forward looking funding requirements as required by Federal Reserves’s Comprehensive Capital Analysis and Review process (CCAR) and the consequences to Funds Transfer Pricing (FTP) management.
- Implemented various aspect of FTP framework to incentive prudent spot and contingent liquidity risk management
- Systematizing and automatic calculation and evaluation of internal liquidity metrics
- Repo pricing under various liquidity and funding constraints.

Industry Internships

Summer 2024: Applied Science Intern at Vijil
- Implemented a general pipeline for optimizing benchmark evaluations for large LLM benchmark (DecodingTrust, OpenLLM, etc) to give an accurate estimate of trust of an LLM more efficiently
Summer 2023: Machine Learning PhD Intern at Instacart
- Initiated and developed a more personalized payment authorization amount per user with $10MM estimated impact
- Built a framework a generic contextual bandit process to perform automatic feature selection and mining through existing experiments for heterogeneous treatment effect
Summer 2022: Applied Research Intern at Snap = * Developed a POC on joint user segmentation and retention modeling for subgroup analysis
- Provided Meaningful insights on user content preferences that tend to correlate higher retention
Summer 2020: Software Engineering Intern at Papaya
- Implemented a generic payment tool to automatically make web payments without human intervention
Summer 2019: Intern at Terrafuse AI
- Developed market design for wildfire risk for commercialization of high resolution climate forecasting

Publications

Algorithmic Collective Action with Two Collectives

Designing Fair Systems for Consumers to Exploit Personalized Pricing

Karan, A., Balepur, N., & Sundaram, H. (2024). Designing Fair Systems for Consumers to Exploit Personalized Pricing. arXiv preprint arXiv:2409.02777

Your Browsing History May Cost You: A Framework for Discovering Differential Pricing in Non-Transparent Markets

Karan, A., Balepur, N., & Sundaram, H. (2023, June). Your Browsing History May Cost You: A Framework for Discovering Differential Pricing in Non-Transparent Markets. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (pp. 717-735).