Work Experience

  • Amazon, Seattle, WA, USA
    Applied Scientist II Intern, Buyer's Risk Prevention (BRP) · May 2026 – Aug. 2026
    • Working with the Amazon Buyer's Risk Prevention team on LLM agents and buyer fraud.
  • Intuit, Mountain View, CA, USA
    AI Science Intern, QuickBooks AI Science Team · May 2025 – Aug. 2025
    • Optimized the latency of an agentic workflow (LangGraph) through high-fidelity automated prompt optimization.
    • Built an automated evaluation suite to assess LLM response fidelity for insights on large-scale consumer data.
  • Rochester Institute of Technology, Rochester, NY
    Graduate Research Assistant · Aug. 2023 – Present
    • PhD student advised by Prof. Ashiqur R. KhudaBukhsh; research focus on responsible and equitable AI systems.
    • Published in A* venues (ACL, AAAI, IJCAI); research covered by ABC News, CNN, and WIRED.
    • Mentored undergrad students on research through NSF-REU program.

Certificates

Projects

  • Trade-System · Personal Project
    • A local-first quantitative equity research & paper-trading framework in Python — blending my love of maths, optimization, and machine learning. It ships walk-forward & combinatorial-purged cross-validation with mandatory leakage tests, long-horizon forecasters with conformalized price bands, a nonlinear-dynamics layer (Hurst/fractal, entropy, Lyapunov, RMT, LPPLS bubble detection), and Kelly + Hierarchical Risk Parity position sizing.
    • Curious about quant finance? Check it out on GitHub — feedback and stars welcome! 🚀

Hobbies

  • I occasionally play chess at chess.com with a rapid rating around 1600. Ping me for a match 😁
  • I regularly dabble in quantitative puzzles and advanced mathematical problems. I used to contribute to the community at Brilliant.org when it was at its peak (sadly not anymore 😢).
  • I have a keen interest in world cinema, anime, and critique. Here is a compilation of some of my favorite directors to watch internationally.