About Me

I’m a data scientist and machine learning researcher with a M.S. in Electrical and Computer Engineering from Northeastern University, where my work focused on explainability and interpretability in deep learning, with applications in computer vision. My research has covered topics ranging from robustness analysis of model explainers to geometry-based person re-identification, and has been published at AISTATS and AVSS.

During both undergrad and during my PhD program, I worked on applied computer vision problems including real-time object detection deployed on embedded hardware, and concealed-object detection for a security screening project. This work sits at the intersection of two things I care about: building models that perform well in production, and building models whose decisions can be understood and trusted.

Outside of research, I build full-stack machine learning systems end-to-end. My most recent project is a cross-domain recommendation engine built on a Plackett-Luce listwise ranking model, with a production-style FastAPI and PostgreSQL backend and a React Native frontend — work that’s given me hands-on experience with the full lifecycle of shipping ML models, from data pipeline to deployment.