Wen-Bin Xu (徐文彬)

Email: wenbin.xu@xmu.edu.cn

EDUCATION AND WORKING EXPERIENCE

2025~, Professor, Xiamen University, China

2023-2025, Postdoc Fellow, Lawrence Berkeley National Laboratory, USA

2022~2023, Postdoc Fellow, Fritz‐Haber Institut der Max‐Planck‐Gesellschaft, Germany

2016~2018, Research Associate, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, China

2018-2022, Ph.D., Technical University of Munich, Germany

2013-2016 M. S., China University of Petroleum (East China), China

2009-2013 B.S., China University of Petroleum (East China), China

RESEARCH AREAS

AI for chemistry and catalysis, AI for Science, Energy Storage and Conversion, Computational Chemistry, Material discovery

HONORS AND AWARDS

Nanqiang Young Talents of Xiamen University A (2025)

Energy Research Computing Allocations Process Project, 10,000GPU node hours, Berkeley, U.S.A. (2024)

NESAP for Machine Learning Fellowship, Berkeley, U.S.A. (2023)

Doctoral Degree with Highest Distinction (Summa Cum Laude), Munich, Germany (2022)

Robert Bosch Artificial Intelligence of Things (AIoT) Fellowship, Munich, Germany (2021)

Gauss Centre for Super computing Projects, Munich, Germany (2020)

REPRESENTATIVE PUBLICAATIONS

To date, over 30 SCI papers have been published, including 10 as first author, in top-tier journals such as Nature Comput. Sci.、J. Am. Chem. Soc.、Proc. Natl. Acad. Sci.、Nature Commun., with a total of approximately 2,000 citations.

Google Scholar: https://scholar.google.com/citations?user=tsfKuhkAAAAJ

Wenbin Xu, Karsten Reuter, and Mie Andersen*. Predicting Binding Motifs of Complex Adsorbates Using Machine Learning with a Physics-inspired Graph Representation. Nat. Comput. Sci. 2022, 2, 443–450

Wenbin Xu, Yuri Sanspeur*, Adeesh Kolluru, Bowen Deng, Peter Harrington, Steven Farrell, Karsten Reuter, John R Kitchin*. Spin-informed universal graph neural networks for simulating magnetic ordering. Proc. Natl. Acad. Sci. 2025, 122, 27, e2422973122

Wenbin Xu, Elias Diesen, Tianwei He, Karsten Reuter, Johannes T Margraf*. Discovering high entropy alloy electrocatalysts in vast composition spaces with multi‐objective optimization. J. Am. Chem. Soc. 2024, 146, 11, 7698–7707

Wenbin Xu, Mie Andersen*, and Karsten Reuter. Data‐Driven Descriptor Engineering and Refined Scaling Relations for Predicting Transition Metal Oxide Reactivity. ACS Catal. 2021, 11, 2, 734–742

Yingheng Tang‡*, Wenbin Xu‡*, Jie Cao, Weilu Gao*, Steve Farrell, Benjamin Erichson, Michael W. Mahoney, Andy Nonaka, Zhi Yao*, Matterchat: A multi-modal llm for material science. ArXiv, 2025, arXiv:2502.13107