About me!

I’m a master’s student in Computer Science at Purdue University, specializing in Machine Learning and Systems, after earning my bachelor’s in Computer Science with a concentration in Systems Software. I build resource-efficient ML systems across large-scale graph learning, distributed data pipelines, and model serving.

My current research focuses on efficient serving systems for real-time interactive and omni-modal models, particularly streaming inference, KV-cache management, and Mixture-of-Experts (MoE) serving. Most recently, I completed a Summer 2026 Software Engineer internship in ML Infrastructure at LinkedIn, where I worked on anomaly detection across graph, GPU-memory, inference, and Spark/Flyte workloads at large scale. Previously, I built creator-platform systems at FoodFluence AI, AI-agent memory infrastructure at Samsung SDS, and platform and security tooling at TwinSketch.

I believe in mastering systems by teaching them. I served as an Undergraduate Teaching Assistant for five consecutive semesters, mentoring over 600 students in Systems Programming, C Programming, Information Systems, and Object-Oriented Programming. I also served as the Internal Outreach Lead for Purdue Hack the Future, where I planned events and supported members.

Beyond tech, I stay active through leetcoding lifting and playing soccer. I love watching/attending Purdue men’s basketball games and I’m a massive Braden Smith (🐐) fan—I was locked in for every game of this year’s March Madness run. Boiler Up!