Welcome to my personal website

I am a Ph.D. candidate in Mechanical Engineering at the University of Connecticut, where I work in the Reliability Engineering and Informatics Laboratory. My research focuses on data-driven diagnostics and lifetime prediction for lithium-ion batteries, combining physics-based modeling with machine learning.

My work aims to improve how battery degradation is diagnosed and predicted using early-cycle data. I develop models that estimate battery capacity trajectories, identify degradation mechanisms, and quantify uncertainty in predictions.

Research Interests

• Battery degradation diagnostics
• Scientific machine learning
• Probabilistic modeling and uncertainty quantification
• Data-driven reliability engineering
• Optimization and parameter estimation

In addition to modeling work, I design and conduct battery aging experiments and contribute open datasets and code for the research community.

I previously interned at MathWorks, where I developed battery feature-extraction workflows, anomaly detection prototypes, and machine learning pipelines for battery analytics.