ICoIAS' 2021 Keynote Speakers

Prof. Gary G. Yen | Oklahoma State University, USA

IEEE Fellow, and IET Fellow; Founding Editor-in-Chief of the IEEE Computational Intelligence Magazine 


Biography: Gary G. Yen received the Ph.D. degree in electrical and computer engineering from the University of Notre Dame in 1992. He is currently a Regents Professor in the School of Electrical and Computer Engineering, Oklahoma State University. His research interest includes intelligent control, computational intelligence, evolutionary multiobjective optimization, conditional health monitoring, signal processing and their industrial/defense applications.
Gary was an associate editor of the IEEE Transactions on Neural Networks and IEEE Control Systems Magazine during 1994-1999, and of the IEEE Transactions on Control Systems Technology, IEEE Transactions on Systems, Man and Cybernetics (Parts A and B) and IFAC Journal on Automatica and Mechatronics during 2000-2010. He is currently serving as an associate editor for the IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, IEEE Transactions on Emerging Topics on Computational Intelligence, and most recently IEEE Transactions on Artificial Intelligence. Gary served as Vice President for the Technical Activities, IEEE Computational Intelligence Society in 2004-2005 and was the founding editor-in-chief of the IEEE Computational Intelligence Magazine, 2006-2009. He was elected to serve as the President of the IEEE Computational Intelligence Society in 2010-2011 and is elected as a Distinguished Lecturer for the term 2012-2014, 2016-2018, and 2021-2023. He received Regents Distinguished Research Award from OSU in 2009, 2011 Andrew P Sage Best Transactions Paper award from IEEE Systems, Man and Cybernetics Society, 2013 Meritorious Service award from IEEE Computational Intelligence Society and 2014 Lockheed Martin Aeronautics Excellence Teaching award. He is a Fellow of IEEE and IET.

Title of Speech: Knee-Driven Optimization And Desion-Making in Evolutionary Multiobjective Optimization  

Abstract: Evolutionary computation is a branch of studying biologically motivated computational paradigms which exert novel ideas and inspiration from natural evolution and adaptation. Its applications based upon population-based meta-heuristics in solving multiobjective optimization problems have been receiving a growing attention. To search for a family of Pareto optimal solutions based on nature-inspiring metaphors, Evolutionary Multiobjective Optimization Algorithms have been successfully exploited to solve optimization problems in which the fitness measures and even constraints are uncertain and changed over time. When encounter optimization problems with many objectives, nearly all designs perform poorly because of loss of selection pressure in fitness evaluation solely based upon Pareto optimality principle. During the last years, evolutionary algorithms have been adapted to address these challenges of curse of dimensionality. In addition, a minimum Manhattan distance approach to multiple criteria decision making in many-objective optimization problems was proposed with effective measure. This procedure is equivalent to the knee selection in operation research. Given such a directive, knee-based evolutionary algorithms have been well-exploited to address multimodal optimization, dynamic optimization, constraint optimization, robust optimization. In addition, it is also extended into the applications in medical screening, early varied-length ECG classification, portfolio management, model recovery in climate fluid dynamics and most recently the design of convolutional neural networks autonomously. In this talk, I will attempt to detail the knee-driven evolutionary algorithm designs and their selected real-world applications pertaining to the interest of audience. 

Prof. Jonathan Garibaldi | University of Nottingham, UK

IEEE Fellow; Editor-in-Chief of IEEE Transactions on Fuzzy Systems 


Biography: Professor Jon Garibaldi is Head of School of Computer Science at the University of Nottingham, Head of the Intelligent Modelling and Analysis (IMA) Research Group, and Founding Director of the University of Nottingham Advanced Data Analysis Centre. His main research interest is in developing intelligent techniques to model human reasoning in uncertain environments, with a particular emphasis on the medical domain. Prof. Garibaldi has been the PI on EU and EPSRC projects worth over £3m, and CoI on a portfolio of grants worth over £25m. Prof. Garibaldi has published over 300 articles on fuzzy systems and intelligent data analysis, including over 100 journal papers and over 200 conference articles. In January 2017, Prof. Garibaldi was appointed as the Editor-in-Chief of the IEEE Transactions on Fuzzy Systems, the leading international journal in the field of fuzzy methods. He was Publications Chair of FUZZ-IEEE 2007 and General Chair of the 2009 UK Workshop on Computational Intelligence, and has served regularly in the organising committees and programme committees of a range of leading international conferences and workshops, such as FUZZ-IEEE, WCCI, EURO and PPSN. He has recently been elected as a Fellow of the IEEE (class of 2021).

Title of Speech: Advances in Type-2 Fuzzy Logic 

Abstract: Type-2 fuzzy sets and systems are now firmly established as tools for the fuzzy researcher that may be deployed on a wide range of applications and in a wide set of contexts. However, in many situations the output of type-2 systems are type-reduced and then defuzzified to an interval centroid, which are then often even simply averaged to obtain a single crisp output. Many successful applications of type-2 have been in control contexts, often focussing on reducing the RMSE. This is not taking full advantage of the extra modelling capabilities inherent in type-2 fuzzy sets. In this talk, I will present some recent research being carried out within the LUCID group at Nottingham into type-2 for modelling human reasoning. I will cover approaches and methodologies which make more use of type-2 capabilities, illustrating these with reference to practical applications such as classification of breast cancer tumours, modelling expert variability, and other decision support problems. 

Prof. Mohamad SAWAN | Westlake University, China (西湖大学)

IEEE Fellow, FCAE Fellow; Editor-in-chief of IEEE Transactions on Biomedical Circuits and Systems; H-Index: 45 


Biography: Mohamad Sawan is Chair Professor in Westlake University, Hangzhou, China, and Emeritus Professor in University of Montreal, Canada. He is founder and director of the Cutting-Edge Net of Biomedical Research And INnovation (CenBRAIN) in Westlake University. He received the Ph.D. degree from University of Sherbrooke, Canada. He is Co-Founder, Associate Editor and was Editor-in-Chief of the IEEE Transactions on Biomedical Circuits and Systems (2016-2019). He is founder of the International IEEE-NEWCAS Conference and of the Polystim Neurotech Laboratory, and Co-Founder of the International IEEE-BioCAS Conference. He was General Chair of the 2020 IEEE International Medicine, Biology and Engineering Conference (EMBC). He was awarded the Canada Research Chair in Smart Medical Devices (2001-2015), and was leading the Microsystems Strategic Alliance of Quebec, Canada (1999-2018). Dr. Sawan published more than 800 peer reviewed papers, two books, 10 book chapters, and 12 patents. He received several awards, among them the Queen Elizabeth II Golden Jubilee Medal, the Shanghai International Collaboration Award, the Qianjiang Friendship Ambassador Award, and the medal of merit from the President of Lebanon. Dr. Sawan is Fellow of the IEEE, Fellow of the Canadian Academy of Engineering, Fellow of the Engineering Institutes of Canada, and “Officer” of the National Order of Quebec. 

Title of Speech: Intelligent Microsystems to Predict Neurodegenerative Diseases and Enhance Health Conditions. 

Abstract: It is a multidisciplinary race to bring breakthroughs in mimicking brain when designing learning algorithms and corresponding hardware implementation. In particular, regular machine learning and advanced deep learning are occupying large parts of emerging chipsets. The later are intended to run complex neural network-based architectures. Smart medical devices intended for the diagnostic, treatment and prediction of neurodegenerative diseases are among these applications. This talk covers artificial intelligence algorithms, circuits and systems intended to implement brain interfaces dealing with multidimensional design challenges such as power management, low-power high-data rate wireless communication, and reliable harvesting energy methods. Application-specific system architectures will be demonstrated. Case studies include neurorecording intended for learning about the intracortical vision mechanism, and for spike onset detection of epileptic seizure for foci localization, cortical microstimulation for seizure abortion, and prediction to inform patient about the arrival of epileptic seizure. 

Prof. Zengguang Hou | Institute of Automation, Chinese Academy of Sciences, China


IEEE Fellow; 复杂系统管理与控制国家重点实验室副主任 


Biography: Zeng-Guang Hou is a Professor and Deputy Director of the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences (CAS).
He is a VP of the Chinese Association of Automation (CAA) and the Asia Pacific Neural Network Society (APNNS), and a member of Board of Governors of International Neural Network Society (INNS). Dr. Hou is an IEEE/CAA Fellow, an Associate Editor of the IEEE Transactions on Cybernetics and the Neural Networks.
Dr. Hou was a recipient of IEEE Transactions on Neural Networks Outstanding Paper Award in 2013, and the National Natural Science Award of China and the Outstanding Achievement Award of Asia Pacific Neural Network Society (APNNS) in 2017.

Title of Speech: Rehabilitation Robots: Challenges in Design, Control, and Clinical Use 

Abstract: Rehabilitation robots are in large demand in China due to annually increasing number of stroke patients. There are many promising researches on rehabilitation robots in recent years, but also we are facing many challenges. On the basis of biosignal acquisition, processing, and rehabilitation robots, this talk will mainly address the Design, Control, and Clinical Uses of rehabilitation robots, and also studied the passive training, active training and assistance training control methods for the needs of neurological rehabilitation of motor function of limbs for SCI or stroke patients. 



ICoIAS' Past Speakers

Prof. Tianyou Chai (IEEE Fellow) | Northeastern University, China




Biography: Tianyou Chai received the Ph.D. degree in control theory and engineering in 1985 from Northeastern University, Shenyang, China, where he became a Professor in 1988. He is the founder and Director of the Center of Automation, which became a National Engineering and Technology Research Center and a State Key Laboratory. He is a member of Chinese Academy of Engineering, IFAC Fellow and IEEE Fellow, director of Department of Information Science of National Natural Science Foundation of China.
His current research interests include modeling, control, optimization and integrated automation of complex industrial processes.
He has published 180 peer reviewed international journal papers. His paper titled Hybrid intelligent control for optimal operation of shaft furnace roasting process was selected as one of three best papers for the Control Engineering Practice Paper Prize for 2011-2013. He has developed control technologies with applications to various industrial processes. For his contributions, he has won 4 prestigious awards of National Science and Technology Progress and National Technological Innovation, the 2007 Industry Award for Excellence in Transitional Control Research from IEEE Multiple-conference on Systems and Control.

Prof. Feiyue Wang (IEEE Fellow) | Institute of Automation, Chinese Academy of Sciences, China


Fellow IEEE (2003), INCOSE (2005) , IFAC (2007), AAAS (2007), ASME (2007) 


Biography: Fei-Yue Wang received his Ph.D. in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, New York in 1990. He joined the University of Arizona in 1990 and became a Professor and Director of the Robotics and Automation Lab (RAL) and Program in Advanced Research for Complex Systems (PARCS). In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China, under the support of the Outstanding Overseas Chinese Talents Program from the State Planning Council and “100Talent Program” from CAS, and in 2002, was appointed as the Director of the Key Lab of Complex Systems and Intelligence Science, CAS. From 2006 to 2010, he was Vice President for Research, Education, and Academic Exchanges at the Institute of Automation, CAS. In 2011, he became the State Specially Appointed Expert and the Director of the State Key Laboratory for Management and Control of Complex Systems.
Dr. Wang’s current research focuses on methods and applications for parallel systems, social computing, parallel intelligence and knowledge automation. He was the Founding Editor-in-Chief of the International Journal of Intelligent Control and Systems (1995-2000), Founding EiC of IEEE ITS Magazine (2006-2007), EiC of IEEE Intelligent Systems (2009-2012), and EiC of IEEE Transactions on ITS (2009-2016). Currently he is EiC of IEEE Transactions on Computational Social Systems, Founding EiC of IEEE/CAA Journal of Automatica Sinica, and Chinese Journal of Command and Control. Since 1997, he has served as General or Program Chair of more than 20 IEEE, INFORMS, ACM, and ASME conferences. He was the President of IEEE ITS Society (2005-2007), Chinese Association for Science and Technology (CAST, USA) in 2005, the American Zhu Kezhen Education Foundation (2007-2008), the Vice President of the ACM China Council (2010-2011), and the Vice President and Secretary General of Chinese Association of Automation (CAA, 2008-2018). Since 2019, he has been the President of CAA Supervision Council. Dr. Wang has been elected as Fellow of IEEE, INCOSE, IFAC, ASME, and AAAS. In 2007, he received the National Prize in Natural Sciences of China and was awarded the Outstanding Scientist by ACM for his research contributions in intelligent control and social computing. He received IEEE ITS Outstanding Application and Research Awards in 2009, 2011 and 2015, and IEEE SMC Norbert Wiener Award in 2014.

Prof. Ljiljana Trajkovic (IEEE Fellow) | Simon Fraser University, Canada


Biography: Ljiljana Trajkovic received the Dipl. Ing. degree from University of Pristina, Yugoslavia, in 1974, the M.Sc. degrees in electrical engineering and computer engineering from Syracuse University, Syracuse, NY, in 1979 and 1981, respectively, and the Ph.D. degree in electrical engineering from University of California at Los Angeles, in 1986.
She is currently a Professor in the School of Engineering Science at Simon Fraser University, Burnaby, British Columbia, Canada. From 1995 to 1997, she was a National Science Foundation (NSF) Visiting Professor in the Electrical Engineering and Computer Sciences Department, University of California, Berkeley. She was a Research Scientist at Bell Communications Research, Morristown, NJ, from 1990 to 1997, and a Member of the Technical Staff at AT&T Bell Laboratories, Murray Hill, NJ, from 1988 to 1990. Her research interests include high-performance communication networks, control of communication systems, computer-aided circuit analysis and design, and theory of nonlinear circuits and dynamical systems.
Dr. Trajkovic serves as IEEE Division X Delegate-Elect/Director-Elect (2018), IEEE Division X Delegate/Director (2019–2020). She serves as Senior Past President (2018–2019) of the IEEE Systems, Man, and Cybernetics Society and served as Junior Past President (2016–2017), President (2014–2015), President-Elect (2013), Vice President Publications (2012–2013, 2010–2011), Vice President Long-Range Planning and Finance (2008–2009), and a Member at Large of its Board of Governors (2004–2006). She served as 2007 President of the IEEE Circuits and Systems Society. She was a member of the Board of Governors of the IEEE Circuits and Systems Society (2001–2003, 2004–2005). She is Chair of the IEEE Circuits and Systems Society joint Chapter of the Vancouver/Victoria Sections. She was Chair of the IEEE Technical Committee on Nonlinear Circuits and Systems (1998). She is General Co-Chair of SMC 2020 and SMC 2018 Workshop on BMI Systems and served as General Co-Chair of SMC 2016 and HPSR 2014, Special Sessions Co-Chair of SMC 2017, Technical Program Chair of SMC 2017 and SMC 2016 Workshops on BMI Systems, Technical Program Co-Chair of ISCAS 2005, and Technical Program Chair and Vice General Co-Chair of ISCAS 2004. She served as an Associate Editor of the IEEE Transactions on Circuits and Systems (Part I) (2004–2005, 1993–1995), the IEEE Transactions on Circuits and Systems (Part II) (2018–, 1999–2001, 2002-2003), and the IEEE Circuits and Systems Magazine (2001–2003). She was a Distinguished Lecturer of the IEEE Circuits and Systems Society (2010–2011, 2002–2003). She is a Professional Member of IEEE-HKN and a Fellow of the IEEE.

Prof. Haizhou Li (IEEE Fellow) | National University of Singapore, Singapore


Biography: Haizhou Li received his Ph.D degree from South China University of Technology, Guangzhou, China in 1990. He is currently Professor at the Department of Electrical and Computer Engineering, National University of Singapore. His research interests include speech information processing, natural language processing, and neuromorphic computing.
Professor Li has served as the Editor-in-Chief of IEEE/ACM Transactions on Audio, Speech and Language Processing (2015-2018), the President of the International Speech Communication Association (ISCA, 2015-2017), and the President of Asia Pacific Signal and Information Processing Association (APSIPA, 2015-2016). He is a Fellow of the IEEE and the ISCA. He was named Nokia Professor in 2009 by Nokia Foundation, and Bremen Excellence Chair Professor in 2019 by University of Bremen.