个人简介
Dr Xiaonan Wang is an associate professor and a promising female scientist of Chemical Engineering at Tsinghua University. She is also an adjunct professor in the Department of Chemical and Biomolecular Engineering, National University of Singapore (NUS). She is leading a Smart Systems Engineering research group of more than 20 team members as PI at Tsinghua and NUS. Her team, in close collaboration with the renowned resilience brokers and Imperial College London, has built a systematic planning platform for smart city and engineering development that combines model-based and data-driven approaches for overall economic, environmental and social benefits improvements. She has published more than 70 peer-reviewed journal and conference proceeding papers, chaired more than 10 sessions and delivered more than 30 presentations/invited talks at international conferences and universities on five continents. Besides academic research and teaching, she has led an education series on Artificial Intelligence and Machine Learning in Science & Engineering to disseminate knowledge and public understanding. She has trained more than 1000 PG/UG students with machine learning and optimization techniques. Xiaonan and her students have developed novel machine learning and artificial intelligence technologies applied in biomedical, nano-materials, energy, environment and sustainability related research. She was recognized as an IChemE Global Awards 2017 Young Researcher finalist and several best paper awards at IEEE Conferences. She is also the deputy director of the Accelerated Materials Development programme in Singapore.
研究领域
Expertise
Energy system design and modeling
Control and optimization
Data analytics and AI
Techno-economic analysis
LCA (Life Cycle Assessment)
Methodology
Agent based simulation
Receding horizon optimization
Model predictive control
Game theory equilibrium models
Multi-objective stochastic programming
Computing
Data mining
Control theories
Advanced optimization
Machine/Deep Learning
Decision support systems
Equipment
High performance computers, cloud computing, sensors (Internet-of-things)
(in collaboration with CREATE C4T)
Waste-to-Energy facilities (in collaboration with CREATE E2S2)
近期论文
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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).
Yuan, Xiangzhou, Xiaonan Wang, Binoy Sarkar, and Yong Sik Ok*. "The COVID-19 pandemic necessitates a shift to a plastic circular economy." Nature Reviews Earth & Environment (2021): 1-2.
Chen, Qianyu, Lanyu Li, Clive Chong, and Xiaonan Wang*. "AI Enhanced Soil Management and Smart Farming." Soil Use and Management (2021).
Ashraf, Waqar Muhammad, Ghulam Moeen Uddin, Syed Muhammad Arafat, Jaroslaw Krzywanski, and Xiaonan Wang*. "Strategic-level performance enhancement of a 660 MWe supercritical power plant and emissions reduction by AI approach." Energy Conversion and Management 250 (2021): 114913.
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).
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).
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).
Jing, Rui, Xiaonan Wang*, Yingru Zhao*, Yue Zhou, Jianzhong Wu, and Jianyi Lin*. "Planning urban energy systems adapting to extreme weather." Advances in Applied Energy (2021): 100053.
Tian, Hailin, Xiaonan Wang*, Ee Yang Lim, Jonathan TE Lee, Alvin WL Ee, Jingxin Zhang, and Yen Wah Tong*. "Life cycle assessment of food waste to energy and resources: Centralized and decentralized anaerobic digestion with different downstream biogas utilization." Renewable and Sustainable Energy Reviews 150 (2021): 111489.
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.
Li, Jie, Lanjia Pan, Manu Suvarna, and Xiaonan Wang*. "Machine learning aided supercritical water gasification for H2-rich syngas production with process optimization and catalyst screening." Chemical Engineering Journal (2021): 131285.
Wang, Zhiyuan, Gade Pandu Rangaiah*, and Xiaonan Wang. "Preference Ranking on the Basis of Ideal-Average Distance Method for Multi-Criteria Decision-Making." Industrial & Engineering Chemistry Research (2021).
Liu, Haoyu, Chen Zhang, Hailin Tian, Lanyu Li, Xiaonan Wang*, and Tong Qiu*. "Environmental and techno-economic analyses of bio-jet fuel produced from jatropha and castor oilseeds in China." The International Journal of Life Cycle Assessment (2021): 1-14.
Shittu, Ekundayo*, Abhijai Tibrewala, Swetha Kalla, and Xiaonan Wang. "Meta-Analysis of the Strategies for Self-healing and Resilience in Power Systems." Advances in Applied Energy (2021): 100036.
Wang, Shukun, Lu Zhang, Chao Liu, Zuming Liu, Song Lan, Qibin Li*, and Xiaonan Wang*. "Techno-economic-environmental evaluation of a combined cooling heating and power system for gas turbine waste heat recovery." Energy (2021): 120956.
Liu, Zuming, Shukun Wang, Mei Qi Lim, Markus Kraft, and Xiaonan Wang*. "Game theory-based renewable multi-energy system design and subsidy strategy optimization." Advances in Applied Energy 2 (2021): 100024.
Li, Jie, Weijin Zhang, Tonggui Liu, Lihong Yang, Hailong Li, Haoyi Peng, Shaojian Jiang, Xiaonan Wang*, and Lijian Leng*. "Machine learning aided bio-oil production with high energy recovery and low nitrogen content from hydrothermal liquefaction of biomass with experiment verification." Chemical Engineering Journal (2021): 130649.
Daniel Tan, Manu Suvarna, Yee Shee Tan, Jie Li, and Xiaonan Wang*. "A three-step machine learning framework for energy profiling, activity state prediction and production estimation in smart process manufacturing." Applied Energy (2021).
Mekki-Berrada, Flore, Ren, Zekun, Huang, Tan, ... and Xiaonan Wang*. "Two-step machine learning enables optimized nanoparticle synthesis." npj Computational Materials (2021).
Liu, Xiaoli, Yang Xu, Jiali Li, Xuanwei Ong, Salwa Ali Ibrahim, Tonio Buonassisi, and Xiaonan Wang*. "A robust low data solution: dimension prediction of semiconductor nanorods." Computers & Chemical Engineering (2021): 107315.