- Developed machine learning models predicting chip defect densities to reduce product failures and returns- Designed various models with unique architecture tailored to chip layout- Deployed the optimal model using Snowflake, DBT, and SQL for evaluating defect densities across various chips

Machine Learning research for high energy physics using natural language processing techniques

Developed machine learning models and algorithms for antibody design, using reinforcement learning and natural language processing techniques

Developed and lead a mobile development project using SwiftUI and Google Maps API

Research on electrostatic properties of viruses, specifically SARS-CoV2, as well as research on surface tension of different fluids