Prof. Dianhui Wang, China University of Mining and Technology

王殿辉教授，中国矿业大学

He graduated from Northeastern University, majoring in industrial automation, with a Ph.D. degree in engineering in March 1995, and worked as a postdoctoral researcher at Nanyang Technological University, Singapore, from September 1995 to August 1997, as a researcher at the Department of Computing, The Hong Kong Polytechnic University, from June 1998 to June 2001, and as a Reader at the Department of Computer Science and Information Technology, La Trobe University, Australia, from July 2001 to December 2020, teaching and researching in artificial intelligence. University Reader in the Department of Computer Science and Information Technology, teaching and researching in Artificial Intelligence. Since 2017, he has been a part-time foreign special professor and doctoral supervisor in the State Key Laboratory of Integrated Automation for Process Industry at Northeastern University, and formally joined the Artificial Intelligence Research Institute of China University of Mining and Technology (CUMT) in July 2021, where he has been the first director of the AI Research Institute, a professor of the second grade, and a doctoral supervisor. To address the complex industrial data modeling problem, Prof. Wang Dianhui created the deep stochastic configuration machine learning theory in 2017, and owns the Australian Science and Technology Innovation Patent, on the basis of which he founded the Research Center for Stochastic Configuration Machines at China University of Mining and Technology (CUMT) in 2021 and served as the Research Center. Machines" at China University of Mining and Technology in 2021 and is the director of the Research Center for Stochastic Configuration Machines. This stochastic learning model has been widely recognized and is having a positive impact in academia and industry. Prof. Wang is currently a senior member of IEEE, the editor-in-chief of Industrial Artificial Intelligence (Springer Nature Publisher), and the editor-in-chief of IEEE Transactions on Fuzzy Systems, IEEE Transactions on Cybernetics, and IEEE Transactions on Cybernetics, and the editor-in-chief of IEEE Transactions on Cybernetics. IEEE Transactions on Fuzzy Systems", "IEEE Transactions on Cybernetics", "Information Sciences" and other international academic journals, is currently responsible for the Ministry of Science and Technology, "2030 Artificial Intelligence Fundamentals" major projects (subject leader), published more than 240 academic articles, edited by the "Springer Lecture Notes on AI". Springer Lecture Notes on AI", edited 2 volumes of special issue on "Neural Networks Stochastic Learning Algorithms" and 1 volume of special issue on "Industrial Artificial Intelligence" in Information Sciences. He has edited two volumes of special issue on "Stochastic Learning Algorithms for Neural Networks" and one volume of special issue on "Industrial Artificial Intelligence" in Information Sciences. Research Interests: deep stochastic configuration machine learning theory and application; industrial big data modeling theory and its application in intelligent sensing technology.

1995年3月毕业于东北大学工业自动化专业，获工学博士学位。1995年9月-1997年8月在新加坡南洋理工大学做博士后研究工作，1998年6月至2001年6月在香港理工大学计算学系做研究员，2001年7月-2020年12月在澳大利亚La Trobe University 计算机科学与信息技术系Reader，从事人工智能方面的教学与科研工作。自2017年以来，兼职东北大学流程工业综合自动化国家重点实验室外籍特聘教授、博士生导师， 2021年7月正式入职中国矿业大学人工智能研究院，并任AI研究院第一任院长、二级教授、博士生导师。针对复杂工业数据建模问题，王殿辉教授于2017年创建深度随机配置机器学习理论，并拥有澳大利亚科技创新专利，在此基础上于2021年在中国矿业大学创建《随机配置机器学习研究中心, Research Center for Stochastic Configuration Machines》并任研究中心主任。目前这一随机学习模型在学术界和工业界得到了广泛认同并正在产生积极影响。王殿辉教授现IEEE高级会员，2022年创刊国际学术杂志《Industrial Artificial Intelligence》 (Springer Nature Publisher)并任主编，同时任《IEEE Transactions on Fuzzy Systems》, 《IEEE Transactions on Cybernetics》, 《Information Sciences》等国际学术期刊副主编，目前承担科技部《2030人工智能基础》重大项目研究（课题负责人），发表学术文章240余篇，主编“Springer Lecture Notes on AI” 一部，在国际著名期刊《Information Sciences》编辑“神经网络随机学习算法”特刊2卷、“工业人工智能”特刊1卷。