Xiaonan Wang is a tenured Associate Professor and Director of the Beijing Key Laboratory of Artificial Intelligence for Advanced Chemical Engineering Materials, Department of Chemical Engineering, Tsinghua University. She also serves as the Associate Dean of Office of International Affairs at Tsinghua. She received B.Eng. from Tsinghua University in 2011 and PhD from University of California, Davis in 2015. After working as a postdoctoral research associate at Imperial College London, she joined the National University of Singapore (NUS) as an assistant professor since 2017 and later became an adjunct associate professor. She is leading a Smart Systems Engineering research group at NUS and Tsinghua and also the director of the Intelligent Chemical Engineering Research Centre. She has published more than 180 peer-reviewed papers and 3 book chapters, with > 14,700 citations and H index 71. She is an associate editor of Applied Energy and npj Thermal Science and Engineering etc. an editorial board member of Green Chemistry, Chem Commun etc., recognized as a Clarivate Highly Cited Researcher, World’s Top 2% Scientists, Cell Press Women Scientist Award, Young Beijing Scholar, ACS Sustainable Chemistry and Engineering Lectureship, 50 Women in Tech by Forbes China etc.

2007.09 - 2011.07 B.Sc, Department of Chemical Engineering, Tsinghua University

2011.08 - 2015.07 Ph.D, Department of Chemical Engineering, Minor in Control Science, University of California, Davis, USA

2015.08 - 2017.07 Postdoctoral Scholar and Lecturer, Department of Chemical Engineering, Energy Futures Program, Imperial College London

2017.07 - 2021.09 Assistant Professor, Adjunct Associate Professor, Department of Chemical and Biomolecular Engineering, National University of Singapore (NUS)

2021.09 - Present Associate Professor, Department of Chemical Engineering, Tsinghua University

AI for Science, Process Systems Engineering, Scientific Foundation Models, Sustainable Energy Systems, Carbon Neutrality

[1] Jun Yin, Honghao Chen, Jiangjie Qiu, Wentao Li, Peng He, Jiali Li, IA Karimi, Xiaocheng Lan, Tiefeng Wang, and Xiaonan Wang*. SurFF: a foundation model for surface exposure and morphology across intermetallic crystals, Nature Computational Science, 2025, 5, 782-792.

[2] Honghao Chen, Jun Yin, Jiali Li, and Xiaonan Wang*. Theoretical high-throughput screening of single-atom CO₂ electroreduction catalysts to methanol using active learning, Engineering, 2025, 52, 172-182.

[3] Jie Su, Jiali Li, Na Guo, Xinnan Peng, Jun Yin, Jiahao Wang, Pin Lyu, Zhiyao Luo, Koen Mouthaan, Jishan Wu, Chun Zhang*, Xiaonan Wang*, and Jiong Lu*. Intelligent synthesis of magnetic nanographenes via chemist-intuited atomic robotic probe, Nature Synthesis, 2024, 3, 466-476.

[4] Haitao Yang, Jiali Li, Kai Zhuo Lim, Chuanji Pan, Tien Van Truong, Qian Wang, Kerui Li, Shuo Li, Xiao Xiao, Meng Ding, Tianle Chen, Xiaoli Liu, Qian Xie, Pablo Valdivia y. Alvarado, Xiaonan Wang*, and Po-Yen Chen*. Automatic strain sensor design via active learning and data augmentation for soft machines, Nature Machine Intelligence, 2022, 4, 84-94.

[5] Jiali Li, Mykola Telychko, Jun Yin, Yixin Zhu, Guangwu Li, Shaotang Song, Haitao Yang, Jing Li, Jishan Wu, Jiong Lu*, and Xiaonan Wang*. Machine vision automated chiral molecule detection and classification in molecular imaging, Journal of the American Chemical Society, 2021, 143, 10177-10188.

Other papers:

[1] Yaoyao Han, Fangwei Wu, Kai Zhao, Cong Hao, Zhenling Sun, Hui Li, Yunhui Liu, Shuyi Li, Kang Cheng*, Fanfei Sun*, Xiaonan Wang*, Shanying Hu, Weizheng Weng, Shuai Wang, Qinghong Zhang & Ye Wang*。Atomically dispersed Pd-Mn dual-metal doped CeO₂ nanorods for efficient methane oxychlorination, Nature Communications, 2026, 17, 1339.

[2] Guo Tian, Honghao Chen, Runyu Jiang, Chenxi Zhang, Xi Lu, Xiaonan Wang*, and Fei Wei*. A dual-engine artificial intelligence framework accelerates sustainable aviation fuel component synthesis, Journal of the American Chemical Society, 2026, 148, 9879-9891.

[3] Yizhe Chen, Shomik Verma, Kevin P Greenman, Haoyu Yin, Zhihao Wang, Lanjing Wang, Jiali Li*, Rafael Gómez-Bombarelli*, Aron Walsh*, Xiaonan Wang*. A unified active learning framework for photosensitizer design, Chemical Science, 2026, 17, 916-926.

[4] Xia Ling, Yixin Zhu, Min Li, Zongliang Xie, Lei Cao, Wentao Song, Dandan Wang, Duo Mao, Xiaonan Wang*, and Bin Liu*. A closed-loop hybrid discovery system of Type I photosensitizers for hypoxic tumor therapy, Advanced Science, 2026, 13, e15103.

[5] Hou Hei Lam, Jiangjie Qiu, Xiuyuan Hu, Wentao Li, Fankun Zeng, Siwei Fu, Hao Zhang, and Xiaonan Wang*. CycleChemist: a dual-pronged machine learning framework for organic photovoltaic discovery, Proceedings of the AAAI Conference on Artificial Intelligence, 2026, 40, 38799-38807.

[6] Kai Zhao, Yijun Li, Xiting Peng, Chi Wang, Yi Shen Tew, Hang Fu, Xiaonan Wang*, Shanying Hu. Artificial intelligence-driven framework for science-policy interface on global plastic life cycle environmental impacts, Nexus, 2026, 3, 100116.

[7] Wentao Li, Yijun Li, Qi Lei, Zemeng Wang, Xiaonan Wang*. PolyRL: reinforcement learning-guided polymer generation for multi-objective polymer discovery, Digital Discovery, 2026, 5, 266-276.

[8] Hongliang Xin*, John R. Kitchin*, Núria López*, Neil M. Schweitzer*, Nongnuch Artrith, Fanglin Che, Lars C. Grabow, G. T. Kasun Kalhara Gunasooriya, Heather J. Kulik, Teodoro Laino, Hao Li, Suljo Linic, Andrew J. Medford, Randall J. Meyer, Jiayu Peng, Cory Phillips, Jin Qian, Long Qi, Wendy J. Shaw, Zachary W. Ulissi, Siwen Wang, and Xiaonan Wang. Roadmap for transforming heterogeneous catalysis with artificial intelligence, Nature Catalysis, 2026, 1-10.

[9] Honghao Chen, Hongxuan Liu, Yishen Tew, Xiaotian Ren, Xiaojin Tang, and Xiaonan Wang*. Distilling knowledge from catalysis literature with long-context large language model agents, ACS Catalysis, 2025, 15, 18244-18254.

[10] Hong Liu, Haoyu Yin, Guangshuo Liao, Dabing Li, Meng Wu, Xiang Qi, Yang Li, Haocheng Yuan, Dengfeng Yu, Fangyi Chen, Jianrong Zeng, Yujun Zhang, Mingxue Tang, Xiaonan Wang*, Yaoyu Ren*, Li-Zhen Fan*, and Ce-Wen Nan*. Rare-earth-free chloride solid electrolytes with high ionic conductivity for all-solid-state lithium batteries, ACS Applied Materials & Interfaces, 2025, 17, 64570-64580.

[11] Yin, Jun, Wentao Li, Honghao Chen, Jiangjie Qiu, Huasheng Feng, Xiangya Xu, Qiuyan Jin, and Xiaonan Wang*. CaTS: Toward Scalable and Efficient Transition State Screening for Catalyst Discovery. ACS Catalysis, 2025, 15, 15754-15764.

[12] Zhihao Wang, Wentao Li, Siying Wang, and Xiaonan Wang*. The Future of Catalysis: Applying Graph Neural Networks for Intelligent Catalyst Design, Wiley Interdisciplinary Reviews: Computational Molecular Science, 2025, 15, e70010.

[13] Yaotian Yang, Hao Xiong, Zirong Wu, Z Luo, Xiao Chen*, Xiaonan Wang*, and Fei Wei. Deep Learning-Enabled STEM Imaging for Precise Single-Molecule Identification in Zeolite Structures, Advanced Science, 2025, 12, 2408629.

[14] Xinqi Yao, Yinan Li, Zhiling Guo, Xinhai Yu*, Xiaonan Wang*, and Shan-Tung Tu. Powering base stations with green methanol derived from distributed renewable energy, International Journal of Hydrogen Energy, 2025, 99, 504-516.

[15] Hongxuan Liu, Haoyu Yin, Zhiyao Luo, and Xiaonan Wang*. Integrating chemistry knowledge in large language models via prompt engineering, Synthetic and Systems Biotechnology, 2025, 10, 23.

[16] Xiaohu Ge, Jun Yin, Zhouhong Ren, Kelin Yan, Yundao Jing, Yueqiang Cao*, Nina Fei, Xi Liu*, Xiaonan Wang*, Xinggui Zhou, Liwei Chen, Weikang Yuan, Xuezhi Duan*. Atomic Design of Alkyne Semihydrogenation Catalysts via Active Learning, Journal of the American Chemical Society, 2024, 146(7): 4993-5004.

[17] Guangtai Zheng, Shuyuan Zhang, Linghang Meng, Sui Zhang*, and Xiaonan Wang*. Machine Learning‐Guided Design and Synthesis of Eco‐Friendly Poly (ethylene oxide) Membranes for High‐Efficacy CO2/N2 Separation. Advanced Functional Materials, 2024, 34(51): 2410075.

[18] Haoyu Yin, Muzi Xu, Zhiyao Luo, Xiaotian Bi, Jiali Li, Sui Zhang* and Xiaonan Wang*. (2024). Machine learning for membrane design and discovery. Green Energy & Environment, 2024, 9, 54-70.

[19] Honghao Chen, Yingzhe Zheng, Jiali Li, Lanyu Li, and Xiaonan Wang*. AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS), ACS Nano, 2023, 17, 9763-9792.

[20] Jun Yin, Jiali Li, Iftekhar A. Karimi*, and Xiaonan Wang*. Generalized reactor neural ODE for dynamic reaction process modeling with physical interpretability. Chemical Engineering Journal, 2023, 452, 139487.

[21] Kedar Hippalgaonkar*, Qianxiao Li, Xiaonan Wang, John W Fisher III, James Kirkpatrick, and Tonio Buonassisi*. Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics, Nature Reviews Materials, 2023, 8, 241-260.

[22] Yingzhe Zheng, Tianyi Zhao, Xiaonan Wang*, and Zhe Wu*. Online learning-based predictive control of crystallization processes under batch-to-batch parametric drift, AIChE Journal, 2022, 68, e17815.

[23] Lanjing Wang, Honghao Chen, L Yang, Jiali Li, Y Li, and Xiaonan Wang*. Single-atom catalysts property prediction via Supervised and Self-Supervised pre-training models, Chemical Engineering Journal, 2024, 487, 150626.

[24] Qi Lei, Lanyu Li, Honghao Chen, and Xiaonan Wang*. Emerging Directions for Carbon Capture Technologies: A Synergy of High-Throughput Theoretical Calculations and Machine Learning, Environmental Science and Technology, 2023, 57, 17189-17200.

[25] Nung Siong Lai, Yi Shen Tew, Xialin Zhong, Jun Yin, Jiali Li, Binhang Yan, and Xiaonan Wang*. Artificial intelligence (AI) workflow for catalyst design and optimization, Industrial & Engineering Chemistry Research, 2023, 62, 17835-17848.

[26] Xiaonan Wang*, Jie Li, Yingzhe Zheng, and Jiali Li. Smart systems engineering contributing to an intelligent carbon-neutral future: opportunities, challenges, and prospects. Frontiers of Chemical Science and Engineering, 2022, 16, no. 6: 1023-1029.

[27] Shidang Xu, Jiali Li, Pengfei Cai, Xiaoli Liu, Bin Liu, and Xiaonan Wang*. Self-improving photosensitizer discovery system via Bayesian search with first-principle simulations, Journal of the American Chemical Society, 2021, 143, 19769-19777.

[28] Flore Mekki-Berrada, Zekun Ren, Tan Huang, Wai Kuan Wong, Fang Zheng, Jiaxun Xie, Isaac Parker Siyu Tian, Senthilnath Jayavelu, Zackaria Mahfoud, Daniil Bash, Kedar Hippalgaonkar, Saif Khan, Tonio Buonassisi, Qianxiao Li, and Xiaonan Wang*. Two-step machine learning enables optimized nanoparticle synthesis, npj Computational Materials, 2021, 7, 55.

[29] Liu, Zuming, Mei Qi Lim, Markus Kraft, and Xiaonan Wang*. "Simultaneous design and operation optimization of renewable combined cooling heating and power systems." AIChE Journal, 2020, 66, 12: e17039.

[30] Suvarna, Manu, Ken Shaun Yap, Wentao Yang, Jun Li, Yen Ting Ng, and Xiaonan Wang*. "Cyber-physical production systems for data-driven, decentralized, and secure manufacturing—A perspective." Engineering, 2021, 9, 1212-1223.

2025 World Chemical Engineering Council (WCEC) Young Researcher Award

2024-2025 Clarivate Highly Cited Researcher

2025 U40 Talent Program, Ministry of Education, China

2021-2025 World’s Top 2% Scientists, published in Mendeley Data from Elsevier

2024 Young Beijing Scholar

2023 ACS Sustainable Chemistry & Engineering Lectureship award

2023 I &EC Research Class of Influential Researchers

2023 James J. Morgan Award Early Career Award (Honorable Mention)

2022 “50 Women in Tech” list by Forbes China

2021 Future Chemical Engineers Award by Global Chinese Chemical Engineering Symposium (GCCES)

2021 AIChE-SLS Outstanding Young Principal Investigator Award

https://www.smartsystemsengineering.com/

Google Scholar: https://scholar.google.es/citations?hl=en&user=dCJWe6gAAAAJ

ORCID: 0000-0001-9775-2417

Scopus Author ID: 56166894600

ResearcherID: T-1102-2017

Associate Editor/Editorial board member of Applied Energy.

Subject editor/Editorial board member of Advances in Applied Energy.

Young Editorial board member ACS ES&T Engineering, Green Energy & Environment, Chinese Journal of Chemical Engineering, Environmental Science and Ecotechnology.

Editorial board member of Computers & Chemical Engineering, Energy Conversion and Management, and Chemical Communications, Green Chemistry, Advanced Intelligent Systems, Chemical Communications, Sustainable Energy & Fuel, Energy Conversion and Management.