Ryan Liu

Ph.D. Student in Physics, Caltech

ryanliu [AT] caltech.edu

Bio

I am a Ph.D. student in Physics at the California Institute of Technology, advised by Hsin-Yuan Huang, and an NSF Graduate Research Fellow. I received my B.A. in Physics and Computer Science from UC Berkeley in 2025 with Highest Distinction in General Scholarship. My research sits at the intersection of machine learning and the physical sciences. I currently work on machine learning decoders for quantum error correction. I have also worked on solver-free operator learning for PDEs, machine learning interatomic potentials [ICML'26] and machine learning for high-energy physics [NeurIPS-W'23a, NeurIPS-W'23b, ACAT].

Publications

From Evaluation to Design: Using Potential Energy Surface Smoothness Metrics to Guide Machine Learning Interatomic Potential Architectures

Ryan Liu, Eric Qu, Toby Kreiman, Sam Blau, Aditi S. Krishnapriyan

ICML'26: International Conference on Machine Learning. 2026.

Paper Code

Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder

Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant

NeurIPS Workshop on Machine Learning and the Physical Sciences. 2023.

Paper Code

Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation

Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant

NeurIPS Workshop on Machine Learning and the Physical Sciences. 2023.

Paper Code

Hierarchical Graph Neural Networks for Particle Track Reconstruction

Ryan Liu, Paolo Calafiura, Steven Farrell, Xiangyang Ju, Daniel Thomas Murnane, Tuan Minh Pham

ACAT: 21st International Workshop on Advanced Computing and Analysis Techniques in Physics Research. 2023.

Paper Code

Honors and Awards

Resume

Full CV in PDF.

Ryan Liu
ryanliu [AT] caltech.edu
Website template by Martin Saveski.