Bio

I am interested in the intersection between computer graphics (CG), large language model (LLM) and scientific machine learning (Sci-ML). Specifically, my goal is to adapt and customize state-of-the-art deep learning methodologies to solve challenging scientific problems.

Positions Held

Doctoral Student

2021 - Present
University of Pennsylvania, Graduate Group of Applied Mathematics and Computational Science

Summer Engineering Associate

Summer 2024
Goldman Sachs, Risk Division
  • Worked on an algorithm to reduce the firm’s value-at-risk (VaR) exposure using minimal number of hedges.
  • Developed uncertainty quantification methods for GenAI based report generation.

Skills & Proficiency

Python

Linux

Large Format Photography