Curriculum Vitae

Ryan Y. Lin

AI Researcher at DRW • Current M.S. CS at Stanford • Caltech B.S. CS

Erdős Number: 3

Education

Sep 2026 — Present

Stanford University

Sep 2023 — Jun 2026

California Institute of Technology (Caltech)

Leadership: Executive Director of Hacktech (Caltech's Premier Annual Hackathon)
Athletics: NCAA Division III Varsity Men's Swimming & Diving athlete (Sprint Freestyle & Butterfly)
Select Graduate-level Coursework: Large Language Models for Reasoning, Machine Learning & Data Mining (CMS 155), Bayesian Statistics, Distributed Computing, Probability Models
Select Undergraduate-level Coursework: Differential Equations, Algorithms & Data Structures, Discrete Mathematics, Software Design, Computer Systems Architecture

Jul 2026 — Present

DRW Holdings

Conducting quantitative machine learning research and modeling high-frequency market dynamics.

Jun 2025 — Sep 2025

Apple (Foundation Model Compute)

Designed, implemented, and deployed a production-grade LLM inference server from scratch for the Foundation Model Compute (Infra) team, enabling elastic autoscaling on accelerators and improving resource efficiency by 8x on real production workloads.
Contributed key performance features to axlearn, Apple's flagship open-source deep learning library.
One of only two intern projects across the entire organization selected to present to Apple AI/ML leadership.

Oct 2023 — Dec 2025

Caltech — Anima AI + Science Lab

Developed new machine learning architectures capable of zero-shot super-resolution for solving families of Partial Differential Equations (PDEs) with arbitrary geometries.
Co-authored 'Enabling Automatic Differentiation with Mollified Graph Neural Operators' (TMLR 2025) and 'Coarse-to-Fine 3D MRI Reconstruction via 3D Neural Operators' (NeurIPS 2025 Workshop).
Incorporated continuous physics loss functions to neural operators to improve training speed and sample efficiency.

Jan 2025 — Apr 2026

California Institute of Technology

Jun — Sep (2021, 2022, 2023, 2024)

The MITRE Corporation

Designed a pipeline leveraging Retrieval-Augmented Generation (RAG) and LLMs to automate security profile creation from STIGs, accelerating delivery by 500%.
Engineered an end-to-end DevSecOps pipeline for the Security Automation Framework (SAF) hosted on AWS EC2.
Authored parts of the SAF CLI used by over 100,000 security practitioners worldwide.