清华大学化学工程系长聘副教授、博导，先进化工材料人工智能北京市重点实验室主任，智能化工研究中心主任，国际合作与交流处副处长，新加坡国立大学荣誉副教授，新一代人工智能国家科技重大专项首席科学家、项目负责人，国家高层次青年人才计划入选者。 带领团队从事AI+能源化工材料的研究，建立了“数据-机理-工程”闭环体系，实现“AI+催化剂及高端聚合物”融合方向的理论和应用创新。 发表论文180余篇，被引15000余次，H-index 72，担任Applied Energy、Green Chemistry等十本国际期刊副主编和编委，获世界化学工程理事会青年学者奖、美国化学会可持续化学与工程讲席奖、Cell Press中国女科学家奖、青年北京学者、侯德榜化工科学技术奖“青年奖”，福布斯中国科技女性50等荣誉，入选全球学者终身学术影响力榜，2024、2025全球高被引学者，连续五年被Elsevier评为全球前2%科学家。
● 教育与工作经历：
2007.08 - 2011.07 清华大学 化学工程系 本科
2011.08 - 2015.07 美国加州大学戴维斯分校 化学工程与控制科学 博士
2015.08 - 2017.07 英国帝国理工学院 过程系统工程中心、未来能源实验室 博士后、硕士生导师
2017.07 - 2021.09 新加坡国立大学 化学工程与生物分子工程 助理教授、独立课题组长、博士生导师
2021.09 - 至今 清华大学化学工程系副教授、独立课题组长（2023.06获长聘）
● 教学工作：
专业必修课《信息科学理论与实践》（32学时，夏季学期）
通识选修课（智能化工交叉方向必修）《人工智能与流程工业导论》（32学时，春季学期）
（入选清华大学优质通识课程建设计划——人工智能专项）
专业限选课（智能化工交叉方向必修）《智能化工》（32学时，春季学期）
研究生专业课、碳中和能力提升课程《工业过程低碳零碳化》（32学时，秋季学期）
实践课程《思政实践》（32学时，夏季学期）
● 主要学术任职：
Applied Energy副主编 (Associate Editor)
Advances in Applied Energy创刊编委、主题主编 (Subject Editor)，
Green Chemistry, Chemical Communications, Sustainable Energy & Fuels顾问编委
Advanced Intelligent Systems国际顾问编委
Computers & Chemical Engineering, Energy Conversion and Management编委
美国化学工程师学会 (AIChE) 高级会员，可持续发展环境领域负责人（Area Chair）
全球华人化工学者学会国际学术委员会委员，国家工信部绿色低碳标识专委会委员
中国化工学会化工大数据与智能设计专委会、女科学家专委会委员，过程模拟与仿真专委会、信息技术应用专委会青年委员，青年工作委员会副秘书长
中国系统工程学会过程系统工程专委会副主任委员
● 代表性论文
[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] 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.
[3] 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.
[4] 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.
[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.
[7] Jiali Li, Haitao Yang*, Lanjing Wang, Nungsiong Lai, Chong Sun, Fuhui Zhou, Qiulei Liu, Wei Wang, Jinghan Li, Chengzhi Hu, Xiaodong Chen*, and Xiaonan Wang*. Computationally intelligent calibration framework for durable soft strain sensors. Nature Communications, 2026, https://doi.org/10.1038/s41467-026-72113-4
[8] Zirui Zhang, Zhihao Wang, Yiwen Liao, Yu Chang, Li Ding*, Guangsheng Luo*, Xiaonan Wang*, and Haihui Wang*. Machine learning–driven discovery of optimal designs for water electrolysis devices. Science Advances, 2026, 12(19), eadz1865.
[6] 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, and Ye Wang*. Atomically dispersed Pd-Mn dual-metal doped CeO2 nanorods for efficient methane oxychlorination, Nature Communications, 2026, 17, 1339.
[9] 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.
[10] Yizhe Chen, Shomik Verma, Kevin P Greenman, Haoyu Yin, Zhihao Wang, Lanjing Wang, Jiali Li*, Rafael Gómez-Bombarelli*, Aron Walsh*, and Xiaonan Wang*. A unified active learning framework for photosensitizer design, Chemical Science, 2026, 17, 916-926.
[11] 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.
[12] 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.
[13] 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.
[14] 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.
[15] 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.
[16] 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.
[17] 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.
[18] 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.
[19] 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.
[20] 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.
[21] 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.
[22] 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.
[23] 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.
[24] 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.
[25] 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.
● 代表性专利和软著
1. 高分子气体分离膜的设计与筛选方法、装置及存储介质，ZL 2024 1 1230657.7
2. 一种针对柔性应变传感器的优化处理方法及装置，ZL 2021 1 1582779.9
3. 一种基于小波变换和深度学习的电池超声信号处理方法、装置及电子设备、存储介质和计算机程序产品，PCT/CN2025/130858
4. 文献信息获取与文献知识图谱的自动构建方法及装置，202510522573.9
5. 用于二氧化碳还原反应的催化剂的筛选方法及装置、电子设备及介质，202411784473.5
软件著作权：
1. 智能材料开发平台（已实现产业转化），2022SR0324372
2. 化工工艺流程智能数字化平台，2026SR0217601
3. 材料智能设计数据平台，2025SR0901370
4. 物质智造工业软件平台，2025SR0900061
5. 能源化学材料知识数据平台，2024SR1486014
6. 主动学习设计分子材料软件，2024SR1652739
7. 二氧化碳捕集利用的人工智能平台，2022SR0324371
8. 碳排放智能分析平台，2022SR0375325
9. 分布感知驱动的主动学习分子性质预测软件，2026SR0684143
● 学术荣誉与奖励：
2025，世界化学工程理事会青年学者奖（WCEC Young Researcher Award）
2024, 青年北京学者
2023, 中国化工学会侯德榜化工科学技术奖“青年奖”
2023, 美国化学会可持续化学与工程讲席奖 ACS Sustainable Chemistry & Engineering Lectureship
2023, 皇家化学会Sustainable Energy & Fuel、美国化学会I&EC Research期刊新锐科学家
2022, 美国化学会James J. Morgan Early Career Award荣誉奖
2022, 福布斯中国科技女性50榜单 （"50 Women In Tech" by Forbes China）
2021, 美国化学工程师学会新加坡杰出青年科学家奖（Young Principal Investigator）
2021, 全球华人化工学者论坛未来化工学者（Future Chemical Engineers Award by GCCES）
2020, Applied Energy 应用能源期刊最佳编委奖
2020, 美国化工学会AIChE期刊未来新星奖（AIChE Future Issue for Rising Star）
● 个人主页：
课题组网页：https://www.smartsystemsengineering.com/
个人主页：https://www.webofscience.com/wos/author/record/T-1102-2017
