Mathematics & Economics student at Hamilton College specializing in deep learning architectures and high-performance computing. Passionate about building scalable ML systems and equivariant neural networks.
HPC-Scale Deep Learning Research
Engineering a rotation-invariant Graph Attention Network to evaluate protein quality. Optimizing training performance for 26M parameters on Hamilton's HPC cluster using NVIDIA A100 GPUs. Leveraging PyTorch Geometric to process a dataset of 1M+ structural samples.
Retrieval-Augmented Generation (RAG)
Designed an end-to-end RAG system for academic planning. Implemented automated data ingestion pipelines for course catalogs and syllabi, utilizing Vector Databases and LangChain to provide context-aware course recommendations.
Hamilton College
B.A. Mathematics & Economics
GPA: 3.71 | Class of 2026
Relevant Skills
Deep Learning, Real Analysis, Data Structures, Algorithms, Probability, Econometrics.
Research Assistant
Computer Science Department
Jan 2026 – Present
Developing state-of-the-art GNN architectures for protein reliability assessment under the guidance of CS faculty.