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Prof. Shyi-Ming Chen
IEEE Fellow, IET Fellow, IFSA Fellow, AAIA Fellow, IETI Distinguished Fellow, Fellow of the Pakistan Academy of Engineering
Asia University, Taiwan
Bio: Shyi-Ming Chen is a Chair Professor in the Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. He received the Ph.D. degree in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in June 1991. He is an IEEE Fellow, an IET Fellow, an IFSA Fellow, an AAIA Fellow, an IETI Distinguished Fellow, and a Fellow of the Pakistan Academy of Engineering. He was a Chair Professor in the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. He was the Dean of the College of Electrical Engineering and Computer Science, Jinwen University of Science and Technology, New Taipei City, Taiwan. He was the Vice President of the National Taichung University of Education, Taichung, Taiwan. He was the President of the Taiwanese Association for Artificial Intelligence (TAAI). He was the President of the Taiwanese Association for Consumer Electronics (TACE). He has published more than 600 papers in referred journals, conference proceedings and book chapters. His research interests include Fuzzy Systems, Intelligent Systems, Fuzzy Decision Making, Computational Intelligence, Knowledge-Based Systems, Machine Learning, Data Mining, Big Data Analysis, Genetic Algorithms, and Particle Swam Optimization Techniques. He is an Associate Editor of IEEE Transactions on Fuzzy Systems, an Associate Editor of IEEE Transactions on Cybernetics, an Associate Editor of IEEE Transactions on Artificial Intelligence, an Associate Editor of Knowledge-Based Systems, an Editorial Board Member of Information Fusion, an Associate Editor of Journal of Intelligent & Fuzzy Systems, an Associate Editor of International Journal on Artificial Intelligence Tools, an Associate Editor of International Journal of Pattern Recognition and Artificial Intelligence, an Associate Editor of International Journal of Fuzzy Systems, an Associate Editor of Journal of Information Science and Engineering, an Associate Editor of Fuzzy Optimization and Decision Making, an Associate Editor of Knowledge and Information Systems, an Editor of International Journal of Intelligent Systems, an Editor of Mathematical Problems in Engineering, an Editor of Engineering Applications of Artificial Intelligence, an Editor of Applied Computational Intelligence and Soft Computing, and an Associate Editor of International Journal of Computational Intelligence and Applications.
Speech Title: Fuzzy Forecasting Based on High-Order Fuzzy Time Series and Genetic Algorithms
Abstract: In our daily life, we often use forecasting techniques to predict the weather, the earthquakes, the stock, the temperature, .., etc. Many methods have been presented to deal with forecasting problems. The drawbacks of the traditional forecasting methods are that they cannot deal with forecasting problems whose historical data are linguistic values and their forecasting accuracy rates are not good enough. In this talk, we will present a method for temperature prediction and TAIFEX forecasting based on two-factors high-order fuzzy time series and genetic algorithms. The proposed method gets higher forecasting accuracy rates than the ones obtained by the existing methods. We also will point out some future research directions in this talk.
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Prof. Loi Lei Lai
IEEE Life Fellow, IET Fellow
Chairman, DRPT International Incorporated, Perth, Australia
Bio:Professor Loi Lei Lai received his B.Sc. (First Class Hons.) and Ph.D. from the University of Aston, Birmingham, UK, in 1980 and 1984 respectively. His D.Sc. is from City, University of London, London, UK, in 2005. All degrees are in electrical and electronic engineering. Professor Lai is currently Chairman of DRPT International Incorporated, Australia. He was a Pao Yue Kong Chair Professor with Zhejiang University, Hangzhou, China; Professor & Chair of Electrical Engineering with City, University of London, London, UK and University Distinguished Professor with Guangdong University of Technology, Guangzhou, China. Professor Lai received an IEEE Third Millennium Medal, the IEEE Power and Energy Society (IEEE/PES) UKRI Power Chapter Outstanding Engineer Award in 2000, a special award from City, University of London in 2005 and is its honorary graduate, the IEEE/PES Energy Development and Power Generation Committee Prize Paper in 2006 and 2009 (Papers published in IEEE Transactions on Energy Conversion), the IEEE Systems, Man, and Cybernetics Society (IEEE/SMCS) Outstanding Contribution Award in 2013 and 2014, the Most Active Technical Committee Award in 2015 and 2024, and his research team received a Best Paper Award in the IEEE International Smart Cities Conference in October 2020. Professor Lai is an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics: Systems, Editor-in-Chief of the IEEE Smart Cities Newsletter; a member of the IEEE Smart Cities Board of Governor; Member-at-large, IEEE Technical Activities Board (TAB) Committee on Standards & Chair of the Seed Funding ad hoc, Chair of IEEE/SMCS Standards Committee, IEEE/SMCS Fellow Committee Evaluator, IEEE/SMCS Distinguished Lecturer and IEEE/PES Lifetime Achievement Award Committee Assessor. He was a member of the IEEE Smart Grid Steering Committee; the Director of Research and Development Center, State Grid Energy Research Institute, Beijing, China; a Vice President for Membership and Student Activities of IEEE/SMCS; and a Fellow Committee Evaluator and Distinguished Lecturer for the IEEE Industrial Electronics Society. His current research and development interests are in smart cities, smart grid, clean energy and computational intelligence. He is an IEEE Life Fellow and IET Fellow.
Speech Title: Impact of Artificial Intelligence and Data Analytics on Sustainability and Daily Life
Abstract: This talk covers a few important topics from smart cities such as smart energy, smart transportation, smart mobility, smart health, smart education and standards development based on machine learning and data science to enhance citizen’s daily life and sustainability. In smart energy with advanced intelligent control and management approaches, this will play a key role in a carbon-neutral society. Power system operation, control and management could be enhanced with the introduction of batteries such as those from electric vehicles with smart charging. For transportation, this includes transportation technologies in conjunction with Big Data that can improve the transportation efficiency of a city. Major environmental, economic, and technological challenges, for example climate change, economic restructuring, pressure on public finances, digitalization of the retail and entertainment industries, and growth of urban and ageing populations have generated huge interest for cities to be run smartly with the integration of communication technologies and artificial intelligence (AI). AI also offers educators good support by organizing repetitive administrative tasks effectively and enabling more efficient analysis of student data. This allows teachers to spend more quality time adapting the curriculum to the needs of students. Some current international research and development activities will be reported, importance of standards activities and future directions will be discussed.
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Prof. Hideyuki TAKAGI
Vice-President of the IEEE SMCS (2006–2007 and 2008–2009)
Professor Emeritus of Kyushu University, Japan
Bio: Prof. Hideyuki Takagi received the degrees of Bachelor and Master from Kyushu Institute of Design in 1979 and 1981, and the degree of Doctor of Engineering from Toyohashi University of Technology in 1991. He worked for Panasonic Central Research Laboratories in 1981 - 1995 and Kyushu Institute of Design and Kyushu University in 1995 - 2022. He retired Kyushu University in March, 2022, but worked for Kyushu University as a Research Professor in April, 2022 - March, 2023. He was a visiting researcher at Computer Science Division, University of California at Berkeley in 1991 -1993 hosted by Prof. Lotfi A. Zadeh.
He is interested in computational intelligence or so-called Soft Computing, especially cooperation of these technologies and human factors. Humanized Computational Intelligence is his research keyword as well as interactive evolutionary computation in these decades. His neuro-fuzzy paper co-authored by his colleague in 1988 became the trigger of big neuro-fuzzy research booming in Japan and then in the world, and many industrial systems and consumer products designed by neuro-fuzzy technology were put on the market since then. Their basic patent covers almost all neuro-fuzzy systems.
He published over 400 papers and book chapters, was an inventor of 39 patents, and received 11 awards including the Best Paper Awards from a journal and conferences and several awards from academic societies. He was listed in the October, 2023 version of the World's Top 2% Scientists list made by Stanford University.
Prof. Takagi had been an active volunteer for academic societies and international conferences. Some of them for IEEE Systems, Man and Cybernetics Society were a Vice-President, a Board of Governors member, a Technical Committee Chair, a SMC Japan Chapter Chair, an Associate Editor of Trans. on Cybernetics, and a Lecturer of Distinguish Lecturer Program, and General Chair of several international conferences.
Speech Title: Human-Computer Interaction Approach for Design and Analysis
Abstract: We focus on human-computer interaction approaches and show how they
bring out human capabilities to solve problems through cooperation with a computer.
Firstly, we show the philosophical difference between AI modeling approaches and the
human-computer interaction approaches. To help understand this difference, we show
concrete examples in design and knowledge acquisition. Secondly, after showing the
difference from AI modeling approaches, we focus on the human-computer interaction
approaches and introduce three research directions of the approaches: interaction
approach for awareness computing, that for optimization/design, and that for analyzing
human characteristics. We show many concrete research examples of these three research
areas to understand these non-AI approaches work well.
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