Nathan's Notes
Stanford undergraduate that has been doing machine learning since middle school. Interested in implementing machine learning models from scratch, developing creative hackathon projects, and speeding up model training/inference with FSDP, quantization methods, and low-level architecture design. Check out my blog, Github, LinkedIn, or shoot me an email.
Work History
K-Scale Labs
May 2024 – Present
- Integrated quantization methods into PyTorch by coding at the Python/C++ interface with Pybind for CUDA inference.
- Finetuning model policy with LoRA for inferring inverse kinematics to minimize energy cost/motor overheating, generating data from robot arm PPO, creating new torque-based agent controller, and modifying simulator’s joint articulation physics engine.
Stanford Cardiac MRI Research Group
Sep. 2023 – Present
- Developing deep learning model from scratch with Pytorch and Weights & Biases to find Right Ventricular insertion points for applying American Heart Association Segmentation model on cDTI MRI images. Created annotation system with AWS S3.
Jane Street
Mar. 2024
- One of 100 students selected for quantitative trading training through manual trading games, achieving 1st among all teams.
- Created high-frequency arbitrage trading bots in Electronic Trading Challenge within program’s advanced division.
Education
Stanford University, School of Engineering
Sep. 2023 – May 2026
- Relevant Coursework: Computer Organization & Systems, Polya Problem Solving Seminar, Modern Mathematics: Discrete Methods, Introduction to Probability Theory, Applied Matrix Theory, Machine Learning, Design and Analysis of Algorithms, Deep Learning for Computer Vision, Natural Language Processing with Deep Learning
- Research Conferences: American Physics Society March Meeting, MIT Undergraduate Technology Research Conference, Society of Engineering Science Annual Technical Meeting, Sigma Xi Student Research Conference
Skills
- Languages: Python, Typescript, C/C++, Java, JavaScript, Swift
- Frameworks: React, React Native, Django, NodeJS, Pytorch, TensorFlow
- Technologies: Firebase/Firestore, GCP, AWS, Docker, Git, Redis, Apache Kafka, Electron, XCode, Android Studio, CUDA
- Awards: Google Company Challenge 2nd @ LAHacks, 3x AIME Qualifier, 2x USNCO Finalist (National Top 50), USACO Gold (International Top 2000), 2x USABO Semifinalist (National Top 10%), Coca-Cola Scholarship Finalist