王笑楠，北京凯发K8娱乐平台招商官方网站化工系长聘副教授、博导，智能化工研究中心主任🥏，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，美国化学工程师学会 (AIChE) 可持续发展领域主席。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🧓🏻。在Nat. Mach. Intell.🛰、Nat. Synth.、J. Am. Chem. Soc.📟、AIChE J等期刊发表学术论文180余篇，包括15篇ESI高被引论文⚗️，被引一万余次，H-index 59🏊🏻🏌️。担任Applied Energy等十本国际期刊副主编和编委，获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，新加坡杰出青年首席研究员奖、英国皇家学会国际交流奖等奖项。入选全球学者终身学术影响力榜，2024全球高被引学者，连续四年被Elsevier评为全球前2% 顶尖科学家。
●教育与工作经历👩👩👦👦：
2007.08~2011.07 北京凯发K8娱乐平台招商官方网站 凯发娱乐 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🫸🏽、博士生导师
2021.09~至今 凯发娱乐副教授（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）
专业限修课（智能化工交叉方向必修）《智能化工》（32学时，春季学期）
通识选修课《人工智能与流程工业导论》（32学时📮，春季学期）
（入选北京凯发K8娱乐平台招商官方网站优质通识课程建设计划——人工智能专项）
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👮🏻♀️：
国际期刊应用能源Applied Energy编委、副主编 (Associate Editor)🥚，Advances in Applied Energy（IF 13.0） 创刊编委、主题主编 (Subject Editor)，Advanced Intelligent Systems🤙🏽🙎🏽，Sustainable Energy & Fuel，Chemical Communications顾问委员会
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
●代表性论文/专利/著作：
[1] 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.
[2] Zheng, Guangtai, 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.
[3] 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.
[4] 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(1), 54-70.
[5] Yuan, Xiangzhou, Manu Suvarna, JY Lim, Javier Pérez-Ramírez, Xiaonan Wang* and Yong Sik Ok*. Active Learning-Based Guided Synthesis of Engineered Biochar for CO2 Capture. Environmental Science & Technology, 2024, 58(15), 6628-6636.
[6] Honghao Chen; Yingzhe Zheng; Jiali Li; Lanyu Li; Xiaonan Wang*; AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS), ACS Nano, 2023, 17(11): 9763-9792.
[7] Nung Siong Lai; Yi Shen Tew; Xialin Zhong; Jun Yin; Jiali Li; Binhang Yan; Xiaonan Wang*. Artificial Intelligence (AI) Workflow for Catalyst Design and Optimization, Industrial & Engineering Chemistry Research, 2023, 62(43): 17835-17848.
[8] Park, Musik, Zhiyuan Wang, Lanyu Li, and Xiaonan Wang*. Multi-objective building energy system optimization considering EV infrastructure. Applied Energy, 2023, 332, 120504.
[9] Tiankai Chen, Jiali Li, Pengfei Cai, Qiaofeng Yao, Zekun Ren, Yixin Zhu, Saif Khan, Jianping Xie*, Xiaonan Wang* ; Identification of chemical compositions from “featureless” optical absorption spectra: Machine learning predictions and experimental validations, Nano Research, 2023, 16: 4188-4196.
[10] Yin, Jun, 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.
[11] Yang, Haitao, Jiali Li, Kai Zhuo Lim, Chuanji Pan, Tien Van Truong, ..., Xiaonan Wang* and Po-Yen Chen*. Automatic strain sensor design via active learning and data augmentation for soft machines. Nature Machine Intelligence, 2022, 4, no. 1: 84-94.
[12] Xu, Shidang, Xiaoli Liu, Pengfei Cai, Jiali Li, Xiaonan Wang*, and Bin Liu*. "Machine‐Learning‐Assisted Accurate Prediction of Molecular Optical Properties upon Aggregation." Advanced Science, 2022, 9, no. 2: 2101074.
[13] Jian Guan; Tan Huang; Wei Liu; Fan Feng; Susilo Japip; Jiali Li; Xiaonan Wang*; and Sui Zhang*. Design and prediction of metal organic framework-based mixed matrix membranes for CO2 capture via machine learning, Cell Reports Physical Science, 2022, 3: 100864
[14] 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.
[15] Xu, Shidang, 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, no. 47: 19769-19777.
[16] Yuan, Xiangzhou, Manu Suvarna, Sean Low, Pavani Dulanja Dissanayake, Ki Bong Lee, Jie Li, Xiaonan Wang*, and Yong Sik Ok*. "Applied Machine Learning for Prediction of CO2 Adsorption on Biomass Waste-Derived Porous Carbons." Environmental Science & Technology, 2021, 55, no. 17: 11925-11936.
[17] 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 7, no. 9 (2021): 1212-1223. (cover article)
[18] Li, Yinan, Song Lan, Morten Ryberg, Javier Pérez-Ramírez*, and Xiaonan Wang*. "A quantitative roadmap for China towards carbon neutrality in 2060 using methanol and ammonia as energy carriers." iScience 24, no. 6 (2021): 102513.
[19] Li, Jiali, Mykola Telychko, Jun Yin, Yixin Zhu,..., Jiong Lu*, and Xiaonan Wang*. "Machine vision automated chiral molecule detection and classification in molecular imaging. Journal of the American Chemical Society, 2021, 143, no. 27: 10177-10188.
[20] 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, no. 12: e17039.
●学术荣誉与奖励🟧：
2024, 入选“青年北京学者”（北京市重要人才项目🏗🧔🏽♂️，与“北京学者”相衔接）
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👩🏻🏫💇🏼、Energy & Fuel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, AIChE新加坡杰出青年首席研究员奖（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
2018, 英国皇家协会国际交流奖
2017, 国际化学工程师学会全球奖(IChemE) 青年研究员（决赛入围名单）
2015, 加州大学戴维斯分校工程学院最佳博士论文提名奖
2014, IEEE全美控制大会最佳报告奖
● 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
