Yinan Huang

Ph.D. student, Machine Learning, Georgia Institute of Technology Phone: +1 919-699-2352 E-mail: yhuang903@gatech.edu Address: 12th Floor, Coda Building, 756 W Peachtree St NW, Atlanta, GA 30308

About

I am a third-year Ph.D. student in Machine Learning at Georgia Tech, supervised by Prof. Pan Li. I am broadly interested in AI for science (developing data-driven methods for accelerating scientific discovery) and Science of AI (understanding the foundations and principles that govern modern AI systems). My current research is focused on

• geometric deep learning: machine learning on graph/structured data, equivariant neural networks.

• generative models: diffusion models and flow matching, and their applications in scientific forecasting and control.

• trustworthy AI: privacy-preserving deep learning.

Prior to that, I earned my M.S. degree in ECE at Duke University and B.S. degree in Physics at Sun Yat-sen University. I also spent one year as a research intern at Peking University, supervised by Prof. Muhan Zhang.

Selected Publications

• Differentially Private Relational Learning with Entity-level Privacy Guarantees
  Yinan Huang*, Haoteng Yin*, Eli Chien, Rongzhe Wei, Pan Li
  NeurIPS 2025

• What Are Good Positional Encodings for Directed Graphs?
  Yinan Huang, Haoyu Wang, Pan Li.
  ICLR2025

• On the Stability of Expressive Positional Encodings for Graphs
  Yinan Huang*, William Lu*, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li
  ICLR 2024

• Boosting the Cycle Counting Power of Graph Neural Networks with I2-GNNs
  Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang
  ICLR 2023

• 3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design
  Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang
  ICML 2022 (Oral).