About me

Currently, I am a Senior Researcher at Microsoft Research, working on AI for Science, with a focus on the intersection of AI with materials and chemistry. Before that, I earned my Ph.D. in computational chemistry from Brown University in 2019 under the supervision of Prof. Brenda Rubenstein, where I focused on developing quantum Monte Carlo algorithms for strongly correlated systems. From 2019 to 2022, I conducted postdoctoral research at UC Berkeley under the guidance of Prof. Teresa Head-Gordon, specializing in interfacial chemistry, microdroplet chemistry, and complex systems. During this time, I pioneered high-precision simulation methods for large-scale reactive systems and theoretical understanding of microdroplet chemistry. My current research interest explores AI-driven large-scale material simulation and design. To date, I have published over 20 papers in prestigious journals such as Nature, J. Am. Chem. Soc., Angew. Chem. Int. Ed., Nat. Mach. Intell., and Nat. Commun..

🔬 Research Interest

AI for Materials: AI-driven material simulation, AI-driven material design, multi-scale simulation, foundation model, etc.

AI for Science: large language model, foundataion model, etc.

🔥 News

• 2025.01: 🎉🎉 Our paper about generative model for inorganic materials design is published on Nature.

📝 Publications

* denotes co-first authors; # denotes corresponding authors

• A generative model for inorganic materials design

  Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Zilong Wang, Aliaksandra Shysheya, Jonathan Crabbé, Shoko Ueda, Roberto Sordillo, Lixin Sun, Jake Smith, Bichlien Nguyen, Hannes Schulz, Sarah Lewis, Chin-Wei Huang, Ziheng Lu, Yichi Zhou, Han Yang, Hongxia Hao, Jielan Li, Chunlei Yang, Wenjie Li, Ryota Tomioka, Tian Xie

  Nature

• Mattersim: A deep learning atomistic model across elements, temperatures and pressures

  Han Yang, Chenxi Hu, Yichi Zhou, Xixian Liu, Yu Shi, Jielan Li, Guanzhi Li, Zekun Chen, Shuizhou Chen, Claudio Zeni, Matthew Horton, Robert Pinsler, Andrew Fowler, Daniel Zügner, Tian Xie, Jake Smith, Lixin Sun, Qian Wang, Lingyu Kong, Chang Liu, Hongxia Hao#, Ziheng Lu

  arxiv | CODE BIB

• Predicting equilibrium distributions for molecular systems with deep learning

  Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu

  Nature Machine Intelligence

• Chemical transformations and transport phenomena at interfaces

  Hongxia Hao, Luis Ruiz Pestana, Jin Qian, Meili Liu, Qiang Xu, Teresa Head‐Gordon

  Wiley Interdisciplinary Reviews: Computational Molecular Science

• Highly altered state of proton transport in acid pools in charged reverse micelles

  Hongxia Hao, Ellen M Adams, Sarah Funke, Gerhard Schwaab, Martina Havenith, Teresa Head-Gordon

  Journal of the American Chemical Society

• Can electric fields drive chemistry for an aqueous microdroplet?

  Hongxia Hao, Itai Leven, Teresa Head-Gordon

  Nature communications

• Proton traffic jam: effect of nanoconfinement and acid concentration on proton hopping mechanism

  Ellen M Adams, Hongxia Hao*, Itai Leven, Maximilian Rüttermann, Hanna Wirtz, Martina Havenith, Teresa Head‐Gordon

  Angewandte Chemie

📖 Education

• 2014.08 - 2019.08, Ph.D. in Chemistry, Brown University.
• 2010.07 - 2014.07, B.S. in Chemistry, Jilin University.