Xu Wenbin
Professional Title: Professor
Department: Energy Storage
Office: A412
TEL:
Email: wenbin.xu@xmu.edu.cn
Research Area: AI for chemistry and catalysis, AI for Science, Energy Storage and Conversion, Computational Chemistry, Material discovery
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
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.、Nature Mach. Intell.、J. Am. Chem. Soc.、Proc. Natl. Acad. Sci.、Nature Commun., with a total of 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
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. Nat. Mach. Intell. 2026, 8, 588-601
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