I build things that think — from computer vision systems on EV motorcycles to self-driving perception stacks. Somewhere between embedded hardware and quantum ML.
I’m an Electrical and Computer Engineering student at Cornell with a passion for bridging the gap between hardware constraints and intelligent software.
Currently, I focus on SLAM, sensor fusion, and optimizing neural networks for edge deployment. I enjoy the challenge of making complex algorithms run efficiently on embedded systems.
A computer vision pipeline using YOLOv8 to identify micro-defects in laser welds.
Deep learning model for multi-class classification of pediatric bone fractures.
Using GNNs to predict glass transition temperatures of complex polymers.
Exploring the application of Variational Quantum Circuits (VQCs) for high-dimensional data classification and mapping.
Developing machine learning models to accelerate the discovery of high-performance electrolytes for Li-ion batteries.
Open to research collaborations, internships, and interesting conversations.