Personal Information
Education
B.S. Computer Science
Sep 2023 - PresentCalifornia Institute of Technology
- Student Organizations: Executive Director of Hacktech (Caltech's Annual Hackathon), NCAA DIII Varsity Men's Swim & Dive
- Graduate-level Coursework: Large Language Models for Reasoning, Machine Learning & Data Mining, Projects in Machine Learning, Probability Models, Distributed Computing, Bayesian Statistics
- Undergraduate-level Coursework: Data Structures & Algorithms, Mathematical Foundations of Computer Science (Discrete Mathematics), Differential Equations, Probability & Statistics, Software Design, Computer Systems
Experience
AI/ML Intern
Jun 2025 - Sep 2025Apple
- Designed, implemented, and deployed a production-grade LLM inference server from scratch for the Foundation Model Compute (Infra) team, enabling elastic autoscaling on accelerators, improving resource efficiency by 8x on real use-cases across cross-functional teams.
- Contributed to axlearn, Apple's largest open-source deep learning library.
- One of two intern projects from the org selected to present to Apple AI/ML leadership.
Researcher
Oct 2023 - PresentCaltech - Anima AI + Science Lab
- Developing new machine learning architectures capable of zero-shot super-resolution for solving families of Partial Differential Equations (PDEs) with arbitrary geometries.
- Incorporating new loss functions to neural operators (ex. physics losses) to improve training speed and data usage
- Performing ablation studies on neural operator architectures to understand the impact of different components on performance and compare against state-of-the-art models.
- Improving code quality and flexibility of the neural operator repository.
Teaching Assistant
Jan 2025 - Present- CS 2: Programming Methods
- CS 3: Software Design
- CMS/CS/CNS/EE/IDS 155: Machine Learning & Data Mining
- CS/EE/IDS 143: Networks: Algorithms & Architecture
- SA 16: Cooking Basics :)
Software Engineering Intern
Jun - Sep (2021, 2022, 2023, 2024)The MITRE Corporation
- Designed a pipeline leveraging Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) to enhance domain-specific knowledge retrieval and automate the creation of security tests from Security Technical Implementation Guides (STIGs), accelerating security profile delivery by 500%
- Engineered an end-to-end DevSecOps pipeline for Security Automation Framework (SAF) using applications, libraries, and tools created by MITRE and the security community. Hosted pipeline on EC2.
- Automated pipeline for key tasks (hardening, validation, visualization) to inform platform owners of security risks and accelerate capability deployment in development, test, and prod environments by up to 500%
- One of ≈ 5 high school sophomores out of all the (500+) interns selected for the MITRE Internship Program
- Authored the SAF CLI (Command Line Interface), a software that streamlines security automation for IT Systems and DevOps pipelines with over 100,000 downloads by the security community.
- Created and published libraries to normalize outputs from various cybersecurity scanning tools into Heimdall Data Format for government sponsors and commercial partners, accelerating accreditation processes by up to 1000%.
Publications
CAT: Curvature-Adaptive Transformers for Geometry-Aware Learning
Ryan Y. Lin, Siddhartha Ojha, Nicholas Bai
NeurIPS Workshop on Non-Euclidean Foundation Models and Geometric Learning, 2025
Coarse-to-Fine 3D MRI Reconstruction via 3D Neural Operators
Armeet Singh Jatyani, Jiayun Wang, Ryan Y. Lin, Valentin Duruisseaux, Anima Anandkumar
NeurIPS Workshop on Imageomics: Discovering Biological Knowledge from Images Using AI, 2025
Diffusion-Generated Social Graphs Enhance Bot Detection
Alec Laprevotte, Ryan Y. Lin, Siddhartha Ojha
NeurIPS Workshop on New Perspectives in Graph Machine Learning, 2025
Enabling Automatic Differentiation with Mollified Graph Neural Operators
Ryan Y. Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar
Transactions on Machine Learning Research (TMLR), 2025
Strategic Collusion of LLM Agents: Market Division in Multi-Commodity Competitions
Ryan Y. Lin, Siddhartha Ojha, Kevin Cai, Maxwell F. Chen
NeurIPS Workshop on Language Gamification, 2024