About Me

I am currently a graduate student at Carnegie Mellon University in the MSML program. I graduated from the Georgia Institute of Technology with a bachelor’s degree in Computer Science in May 2025. My current research interests include efficient training and inference, parallelization schemes, hardware-aware algorithm design, and geometric deep learning. Much of my past work has related to solving problems in these areas using PyTorch, TensorFlow, and CUDA.

At GT, I was fortunate to be advised by Prof. Victor Fung at the Fung Group, where I broadly worked on pre-training strategies for large-scale foundation graph neural networks for applications to materials chemistry. Until May 2024, I also worked under Prof. Ye Zhao and Max Asselmeier at the Laboratory for Intelligent Decision and Autonomous Robots, where I investigated deep reinforcement learning approaches for decentralized multi-robot collision avoidance and navigation.

I interned at Millennium Management in Miami as a machine learning engineer this summer and worked on evaluating agents on text2SQL-like tasks. In 2024, I interned at Amazon as a software engineer, where I developed a secure micro-frontend using TypeScript and the AWS CDK to enable on-calls to inspect and refresh employee data caches. Before Amazon, I interned as a machine learning engineer at EXL Service, where I developed end-to-end document processing solutions for medical and insurance documents and worked on adapting techniques for few-shot learning to document image classification and custom named entity recognition. I have also worked at M2IOT Solutions, an Industrial IoT startup, as a software engineering intern and at the Indian Institute of Technology Roorkee as a research intern.