Som Naik

Background in operations research, applied mathematics, and statistics. I build scalable models for complex, high-dimensional problems, including optimizing billion-dollar supply chains, supporting multimillion-dollar SEC investigations, and conducting quantitative research.

Currently building AI-native trading tech @ Point72


Selected Work

Gameo

Natural-language search platform for discovering mobile games, powered by LLM-based semantic understanding. Includes a custom recommendation and monetization engine that boosts creator visibility through prioritized ad plans.

see site →
Columbia Optimization Projects

Graduate coursework projects including eliminating childcare deserts through integer programming and a Travelling Salesman implementation with advanced heuristics.

see paper 1→ see paper 2→
TIPS ETF Risk Model

Technical paper co-authored with Dr. James Glimm developing an ETF risk model for Treasury Inflation Protected Securities using proprietary ARMA-GARCH and heavy-tail methods. Presented at Stony Brook's PhD Quant Finance webinar alongside guests from Goldman Sachs, Morgan Stanley, and Renaissance Technologies.

see publication →

Education

Columbia University

Fu Foundation School of Engineering & Applied Science

M.S. Operations Research

Stony Brook University

College of Engineering and Applied Science

B.S. Applied Math & Statistics

B.S. Financial Info Systems

Presidential Scholarship · Outstanding Achievement Award · AMS Reseach Award · Dean's List

Certification(s)

Machine Learning Specialization

Stanford Online