Keynote Speakers
Prof. Chao Zuo, Nanjing University of Science and Technology
左超教授，南京理工大学
Biography:
Dr. Chao Zuo is a professor in optical engineering, Nanjing University of Science and Technology (NJUST), China. He leads the Smart Computational Imaging Laboratory (SCILab: www.scilaboratory.com) at the School of Electronic and Optical Engineering, NJUST, and is also the founder and director of the Smart Computational Imaging Research Institute of NJUST. He has long been engaged in the development of novel Computational Optical Imaging and Measurement technologies, with a focus on Phase Measuring Imaging Metrology such as Holographic Interferometric Microscopy, Noninterferometic Quantitative Phase Imaging (QPI), Fringe Projection Profilometry (FPP), and Structured Illumination Microscopy (SIM). He has authored > 200 peer-reviewed publications in prestigious journals (e.g., Light, Optica, Adv. Photon.) with over 12,000 citations. These researches have been featured on journal cover over 20 times and highlighted by Nature, Light. Sci. Appl., SPIE Newsroom, CLP Newsroom, and Optica Image of the Week. He is a Clarivate Highly Cited Researcher and a Fellow of SPIE and Optica. He also serves as Associate Editors of Optics and Lasers in Engineering and PhotoniX.
Prof. Xinsong Yang, Sichuan University
杨鑫松教授，四川大学
Biography:
Xinsong Yang (1968-), professor, master and doctoral director of the College of Electronics & Information Engineering, Sichuan University, head of Laboratory of "Swarm Intelligence and Control", project-review expert of Chengdu Science and Technology Association, innovation leader of "Tianfu Emei Plan", From 2019 to 2022, he was selected as a Global Highly Cited Scholar and Elsevier China Highly Cited Scholar for four consecutive years, and in 2019 and 2022, a distinguished reviewer awarded by SCI journalsJ. Franklin Instit. andIEEE Trans. Network Sci. Engineering, respectively. He was a Visiting scholar of Southeast University, City University of Hong Kong, University of Hong Kong, Hong Kong Polytechnic University. He is an Associate Editor of the journals Engineering Science and Technology,Frontiers in Applied Mathematics and Statistics,Mathematical Modelling and Control,Neurocomputing,Neural Processing Letters,Mathematics. He is a member of the Professional Committee of the National Complex Network Conference, member of the Academic Committee of TCCT Random System Control Group, member of the special Committee of the Intelligent Things Association, senior member of the Chinese Society of Automation, commentator of the American "Mathematical Review", won the second prize of Jiangsu Province Science and Technology Award in 2016 (ranking third), and won the Chongqing Excellent Academic Paper for three consecutive years from 2017 to 2019. In 2020, he won the first prize of the first Sichuan-Chongqing excellent paper, and in 2021, he won the second and third prizes of Sichuan-Chongqing excellent paper. 1 authorized invention patent, 144 scientific research papers published, a total of more than 7800 SCI citations, H index 50, Publications include SIAM Journal on Control and Optimization, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Circuits and Systems –I, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Automatic Control, IEEE Transactions on Cybernetics, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Science China Technological Sciences, Science China Information Science and other top magazines at home and abroad. Presided over the completion of 2 national and a number of provincial scientific research projects.
杨鑫松(1968-)，教授，四川大学电子信息学院硕导和博导，“群体智能与控制”实验室负责人，成都市科学技术协会项目评审专家，“天府峨眉计划”创新领军人才，2019-2022年连续4年入选科睿唯安全球高被引学者和Elsevier中国高被引学者，分别获2019、2022年SCI杂志J. Franklin Instit.和 IEEE Trans. Network Sci. Engineering杰出审稿人，访问过东南大学、香港城市大学、香港大学、香港理工大学，是杂志《工程科学与技术》(原四川大学学报(工程科学版))、Frontiers in Applied Mathematics and Statistics、Mathematical Modelling and Control、 SCI杂志Neurocomputing、Neural Processing Letters、Mathematics的编辑（AE），全国复杂网络会议专业委员会委员、TCCT随机系统控制学组学术委员会委员、智能物联专委会委员、中国自动化学会高级会员、美国《数学评论》的评论员，2016年获江苏省科学技术奖二等奖（排名第三），2017-2019年连续3年获重庆市优秀学术论文，2020年获首届川渝优秀论文一等奖，2021年获川渝优秀论文二、三等奖各1篇。授权发明专利1项，发表科研论文144篇，总共被SCI引用7800多次，H指数50，发表的杂志包括SIAM Journal on Control and Optimization, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Circuits and Systems–I, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Automatic Control，IEEE Transactions on Cybernetics, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Science China Technological Sciences, Science China Information Science等国内外顶级杂志。主持完成2项国家级和多项省级科研项目。
Prof. Dianhui Wang, China University of Mining and Technology
王殿辉教授，中国矿业大学
Biography:
Dr. Wang was awarded his PhD degree (March 1995) in Industrial Automation from Northeastern University, China. From Sept. 1995 to June 2001, he worked as a Postdoctoral Fellow at Nanyang Technological University, Singapore and The Hong Kong Polytechnic University, Hong Kong, China. He joined La Trobe University in July 2001 and worked as a Reader and Associate Professor in the Department of Computer Science and Information Technology until the end of 2020, and with an adjunct appointment from January 2021. Since 2017, Dr Wang has been a visiting Professor at State Key Laboratory of Synthetical Automation of Process Industries, Northeastern University, China. In July 2021, He joined the Institute of Artificial Intelligence at China University of Mining and Technology. He is the Funding Director of Research Center for Stochastic Configuration Machines. His current research focuses on Stochastic Configuration Machines (SCM) for big industrial data modelling and analytics, lightweight computing, and interpretable AI technology. Dr. Wang published more than 270 technical papers on applied mathematics, control engineering and computer sciences. He is a Senior Member of IEEE, serving as an executive Editor-in-Chief for Industrial Artificial Intelligence, Associate Editor for TCYB, TFS, INS, AIR, and WIREs Data Ming and Knowledge Discovery.
王殿辉博士于1995年三月在东北大学获得工业自动化专业工学博士学位。他于1995年至2001年在新加坡南洋理工大学和香港理工大学做博士后研究工作，2001年7月至2020年12月在澳大利亚La Trobe大学计算机科学与信息技术系就职。自2017年起，王殿辉博士任东北大学流程工业综合自动化国家重点实验室特聘教授。 2021年7月加盟中国矿业大学人工智能研究院任院长及随机配置机器学习研究中心主任。他目前的研究重点是随机配置学习机在工业大数据建模与分析中的应用、轻量计算及可解释AI技术。王殿辉博士发表有关应用数学、控制工程和计算机科学方面的论文270余篇， 目前是IEEE高级会员，2022年创建Industrial Artificial Intelligence杂志并担任执行主编，任IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, Information Sciences, Artificial Intelligence Review and WIREs Data Ming and Knowledge Discovery的副主编。
Prof. Juan Fang, Beijing University of Technology
方娟教授，北京工业大学
Biography:
Juan Fang is a professor and doctoral supervisor at Beijing Institute of Technology (BIT), deputy director of the Department of Informatics and deputy director of the Department of Computer Science and Technology. She is a distinguished member of CCF, an executive member of CCF Higher Committee, Architecture Committee, and Internet of Things Committee, a famous teacher of the Beijing Municipal Curriculum Civics and Politics and the person in charge of the national first-class undergraduate program construction site.She has been awarded the titles of Beijing Outstanding Talent and Beijing Young and Middle-aged Backbone, etc. In 2005 and 2012,She went to the United States for two years' academic exchange visits funded by the China Scholarship Council (CSC).She has long been engaged in teaching and scientific research in the fields of high-performance computing, heterogeneous intelligent computing, edge computing, etc. In recent years, she has presided over a number of scientific research projects such as the National Natural Science Foundation of China and the Natural Science Foundation of Beijing Municipality, and has been published in important academic journals at home and abroad as well as in important international academic conferences (PR, TNSM, JPDC, TJSC, JCST, IoT, JoS, FITEE, JCSC, INFOCOMM, etc.), published more than 100 scientific papers, authorized 34 national invention patents, 1 international invention patent, participated in the development of 3 national standards, and 1 patent results transformation.She serves as a reviewer for Chinese and English journals such as JPDS, TMC, IoT, JCSC, JoS, Journal of Computing, Journal of Software, Computer Research and Development, and Journal of Communication.She has published more than 20 teaching papers in teaching journals such as China University Teaching, Computer Education, etc. He has edited and co-edited 11 textbooks and 2 translations, and has been awarded with a number of educational and teaching achievement awards.
方娟，北京工业大学教授，博士生导师，信息学部副主任，计算机科学与技术系副主任。CCF杰出会员，CCF高专委、体系结构专委、物联网专委执行委员，北京市课程思政教学名师，国家一流本科专业建设点负责人。曾获北京市优秀人才、北京市中青年骨干等称号，于2005年和2012年两次受国家留学基金委（CSC）资助赴美国进行学术交流访问两年。长期从事高性能计算、异构智能计算、边缘计算等领域的教学和科研工作，近年来主持国家自然科学基金、北京市自然科学基金等科研项目多项，在国内外重要学术刊物和重要国际学术会议（PR、TNSM、JPDC、TJSC、JCST、IoT、JoS、FITEE、JCSC、INFOCOMM等）上发表科研论文100余篇，授权国家发明专利34项，国际发明专利1项，参加3项国家标准制定，1项专利成果转化。担任JPDS、TMC、IoT、JCSC、JoS、计算机学报、软件学报、计算机研究与发展、通信学报等中英文期刊审稿人。在《中国大学教学》、《计算机教育》等教学期刊发表教学论文20余篇，主编和参编教材11本，译著2本，曾获多项教育教学成果奖。
Prof. Haiquan Zhao, Southwest Jiaotong University
赵海全教授，西南交通大学
Title：Robust adaptive signal processing and deep filter
Abstract：As an important part of signal processing, adaptive filtering has been widely used in many fields, including communications, radar, power system and biomedical. In practical applications, these adaptive filters are based on Gaussian background noise design, and performance deteriorates in the Non-Gaussian noise environment. This topic shares our recent research findings how to enhance the robustness of algorithms against impulsive noise under acoustic echo cancellation(AEC) and system identificaiton. Moreove, deep filter we recent proposed are also introduced in this speech.
Biography:
Zhao Haiquan, Doctor of Engineering, Professor, Doctoral Supervisor,IEEE Senior Member and CIE Senior Member, Elsevier Highly Cited Researcher, Top 2% of the World's Top Scientists (for many years), Academic and Technical Leader of Sichuan Province, Outstanding Expert with Outstanding Contributions in Sichuan Province, Winner of Sichuan Outstanding Youth Fund and Core Member of Sichuan Youth Science and Technology Innovation Team, won 5 provincial and ministerial awards such as the first prize of CAA Natural Science of the Chinese Society of Automation, the second prize of the Ministry of Education's Science and Technology Progress Award, Tang Lixin Outstanding Scholar Award, Executive Director of the Provincial Federation of Science and Technology, Member of the Sichuan Youth Federation, and Executive Director of the Chengdu Municipal Knowledge Federation. He serves on the editorial board of international journals such as Signal Processing.In recent years, he has presided over 5 general projects of the National Natural Science Foundation of China, 1 Sichuan Youth Science and Technology Fund, 1 Provincial Applied Basic Key Project, 1 Provincial Academic Leader Fund, and 1 Basic Scientific Research and Technology Innovation Project of the Central Universities. He has researched more than 10 national, provincial and ministerial projects. As the first author or corresponding author has been published in IEEE TSMCA, IEEE TSP, IEEE TNNLS, IEEE TIE, IEEE TCOM, IEEE/ACM TASLP, IEEE Trans. He has published more than 180 papers (140+ SCI indexed journal papers) in domestic and foreign academic journals and academic conferences such as Cybernetics, IEEE TSMC-Part B, Signal Processing, Automatica, Journal of the Franklin Institute, MSSP, Science China, Acta Physica Sinica, ICASSP, etc., and 6 papers (1%) ESI are highly cited. 1 hot paper, 70 patents applied for and authorized, of which 49 were authorized (including 7 transfers). He has won 11 academic awards, including the "Excellent Student Paper Award" (a regular paper published in IEEE Transactions on System, Man and Cybernetics-Part B).Professor Zhao's research interests include pattern recognition and artificial intelligence (equipment fault diagnosis, deep learning); distributed adaptive filtering network; Nonlinear adaptive filtering: adaptive Volterra filter, kernel adaptive filter, neural network adaptive filter, etc.; Adaptive Signal Processing Theory; DC-DC modeling and system identification; active noise control; Power Quality Control - Adaptive Harmonic Suppression and Active Power Filter (APF); DSTATCOM adaptive control; identification of low-frequency oscillation mode; Intelligent signal processing and its application in power systems.
赵海全，工学博士，教授，博士生导师，IEEE和中国电子学会高级会员，爱思唯尔高被引学者、全球前2%顶尖科学家（连续多年）、四川省学术和技术带头人，四川省有突出贡献的优秀专家，四川省杰出青年基金获得者以及四川省青年科技创新团队核心成员，获中国自动化学会CAA自然科学一等奖、教育部科技进步二等奖等省部级奖励5项，唐立新优秀学者奖、省科青联常务理事、川青联委员、成都市知联会常务理事。担任Signal Processing等国际期刊的编委。近年来，主持国家自然科学基金面上项目5项，主持四川省青年科技基金、省应用基础重点项目以及省学术带头人基金、中央高校基本科研科技创新项目各1项；主研国家级或省部级项目10余项。以第一作者或通讯作者已在IEEE TSMCA、IEEE TSP、IEEE TNNLS、IEEE TIE、IEEE TCOM、IEEE/ACM TASLP、 IEEE Trans. Cybernetics、IEEE TSMC-Part B、Signal Processing、Automatica、Journal of the Franklin Institute、MSSP、《中国科学》、《物理学报》、ICASSP等国内外学术期刊与学术会议发表论文180多篇（140+篇SCI收录期刊论文），6篇（1%）ESI高被引，1篇热点论文，申请及授权专利70项，其中授权49项（其中转让7项）。获“Excellent Student Paper Award”奖（发表在IEEE Transactions on System, Man and Cybernetics-Part B上的Regular论文）等学术奖励11项。指导留学生甘布荣获2017年第二届动力与可再生能源国际会议最佳报告奖，2019年获2019IFAC最佳论文奖，指导硕士及博士生18人次获得国家奖学金，2名博士生获得轨道交通行业拔尖创新人才项目，2名博士生获得博士生创新基金项目，5名博士研究生获公派联合培养资助，分别赴McGill University 和 University of York等。赵教授的研究方向包括模式识别与人工智能（设备故障诊断、深度学习）；分布式自适应滤波网络；非线性自适应滤波：自适应Volterra滤波器、核自适应滤波器、神经网络自适应滤波器等；自适应信号处理理论；Dc-DC建模及系统辨识；主动噪声控制；电能质量控制-自适应谐波抑制及有源电力滤波器（APF）；DSTATCOM自适应控制；低频振荡模式辨识；智能信号处理及在电力系统中的应用。