Education
Harvard University
2027 — 2028
Harvard University
2024 — 2028
Undergraduate technical coursework:
- CS 50: Intro to CS
- CS 61: Systems Programming
- CS 120: Algorithms
- CS 1810: Machine Learning
- AM 226: [Graduate] Computational Neuroscience
- MIT 18.337: Parallel Computing and Scientific ML
- Math 21a: Multivariable Calculus
- Math 21b: Linear Algebra
- Math 55b: Honors Topology, Real Analysis, and Complex Analysis
- Math 123: Algebra II - Theory of Rings and Fields
- Math 155R: Combinatorics
- Stat 110: Probability
- Stat 111: Statistical Inference
Professional Experience
Software Engineering Intern at Newline Interactive
June 2025 – August 2025 • Dallas, TX
- Created internal RAG chatbot to assist IT team using OpenAI embeddings, ChromaDB, and semantic search to deliver contextually-accurate responses with under 1s query latency and 90+% accuracy on benchmarks
- Architected full-stack chatbot features, employing a React frontend and scalable PostgreSQL-based backend for logging 1k+ chat sessions and 10k+ feedback entries
- Engineered AI-based OCR pipeline to SAP, parsing purchase order PDFs into an SAP-readable payload, transmitting them to SAP via a secure REST endpoint, and reducing manual data entry time by 85%
Software Engineering Intern at Alibre, LLC
May 2025 – June 2025 • Remote
- Engineered end-to-end design pipeline, leveraging Stable Diffusion with custom text-to-image prompts to synthesize images for downstream CAD workflows
- Wrote code for PNG-to-SVG conversion using Pillow, OpenCV, and NumPy to detect contours, and enforce creation of non-self-intersecting B´ezier paths for successful extrusion
- Employed simplification algorithm to render input images of up to 1024x1024 resolution in under 3s
Researcher at Madsen lab, Boston Children's Hospital
January 2025 - May 2025 • Boston, MA
- Developed a machine learning pipeline prototype to predict seizure onset localization strength by integrating electrode spatial data and patient clinical metadata
- Created graph embeddings using node2vec to capture local and global patterns in directed graphs representing networks of Granger causality
- Trained a PyTorch-based GNN, with performance benchmarked against a random forest baseline
Awards and Honors
Mathematics:
- AIME: Qualified x2
Other:
- Scripps National Spelling Bee: Participant (2017, 2018), Champion (2019), Highest written test score (2019)
- National Academic Quiz Tournaments (Quiz Bowl): Small School Nationals champion (2024), High School Nationals runner-up (2024), Intercollegiate Nationals DII champion (2025)