Prof. Witold Pedrycz
University of Alberta, Canada
IEEE Fellow
Bio:
Witold Pedrycz (IEEE Fellow, 1998) is Professor and Canada Research Chair (CRC) in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. In 2009 Dr. Pedrycz was elected a foreign member of the Polish Academy of Sciences. In 2012 he was elected a Fellow of the Royal Society of Canada. Witold Pedrycz has been a member of numerous program committees of IEEE conferences in the area of fuzzy sets and neurocomputing. In 2007 he received a prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society. He is a recipient of the IEEE Canada Computer Engineering Medal, a Cajastur Prize for Soft Computing from the European Centre for Soft Computing, a Killam Prize, and a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society. His main research directions involve Computational Intelligence, fuzzy modeling and Granular Computing, knowledge discovery and data mining, fuzzy control, pattern recognition, knowledge-based neural networks, relational computing, and Software Engineering. He has published numerous papers in this area. He is also an author of 15 research monographs covering various aspects of Computational Intelligence, data mining, and Software Engineering. Dr. Pedrycz is intensively involved in editorial activities. He is an Editor-in-Chief of Information Sciences, Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley), and Int. J. of Granular Computing (Springer). He currently serves on the Advisory Board of IEEE Transactions on Fuzzy Systems and is a member of a number of editorial boards of other international journals.
Prof. Ram Bilas Pachori
Indian Institute of Technology Indore
Bio: Ram Bilas Pachori (born 1979) is Institute Chair Professor and Professor (HAG) in the Department of Electrical Engineering at the Indian Institute of Technology Indore, India. He is also Adjunct Professor in the Department of Electronics & Communication Engineering at Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India. His research focuses on signal processing, image processing, biomedical signal processing, non-stationary signal processing, speech processing, brain–computer interface, machine learning, and artificial intelligence and internet of things in healthcare.
He was named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2025, "for contributions to application of signal decomposition methods to biomedical engineering". He was also elected as a fellow of Indian National Academy of Engineering (INAE), Institution of Engineering and Technology (IET), Institution of Electronics and Telecommunication Engineers (IETE), Institution of Engineers (India) (IEI), and International Academy of Artificial Intelligence Sciences (AAIS). He was elected as a Foreign Member of the Luxembourg Academy of Sciences and Arts (LASA) in 2026. He was awarded IETE-Prof SVC Aiya Memorial Award in 2021 and IETE-Ram Lal Wadhwa Award in 2025. He has been appointed as IEEE EMBS Distinguished Lecturer and Academy Mentor for EURASIP Academy. Pachori was awarded IET Journals Premium Award for Best Paper in IET Science, Measurement & Technology for consecutive two years (2019 and 2020). He has also received the Best Paper Award in XXIV International Conference on Digital Signal Processing and Its Applications (DSPA 2022) held at Moscow, Russia. He has been recognized as a Top Cited Scholar for three consecutive years, from 2023 to 2025, on the Scilit website.
Prof. Wei-Chiang Hong
Harbin Engineering University, China
Bio: Wei-Chiang Hong (Senior Member, IEEE) is a professor at the College of Shipbuilding Engineering at Harbin Engineering University, Harbin, China. His research interests mainly include computational intelligence, the application of forecasting technology, and machine learning algorithms. He serves as the program committee for various international conferences, including CEC, CIS, SMC, and SMCia. He was elected as the Outstanding Professor Award in 2014 and 2023. From 2020 to 2024, he has been indexed as one of the World's TOP 2% Scientists.
Prof. Wanyang Dai
Nanjing University, China
Bio: Wanyang Dai is a Distinguished Professor in Mathematics School of Nanjing University, Chief Scientist at Su Xia Control Technology, President and CEO of U.S. based (blochchain and quantum computing) SIR Forum (Industial 6.0 Forum), a Special Guest Expert in Jiangsu FinTech Research Center, Chairman of Jiangsu Big Data-Blockchain and Smart Information Special Committee, where his research includes stochastic processes related big model and quantum computing, artificial intelligence and machine learning, optimization and optimal control, admission/scheduling/routing protocols and performance analysis/optimization for various projects in BigData-Blockchain oriented quantum-cloud computing and the next generation of wireless and wireline communication systems, forward/backward stochastic (ordinary/partial) differential equations and their applications to queueing systems, stochastic differential games, communication networks, Internet of Things, financial engineering, energy and power engineering, etc. His “influential” achievements are published in “big name” journals including Journal of Applied Statistics, Probability in the Engineering and Informational Sciences, Quantum Information Processing, Operational Research, Operations Research, Computers & Mathematics with Applications, Communications in Mathematical Sciences, Journal of Computational and Applied Mathematics, Queueing Systems, Mathematical and Computer Modeling of Dynamical Systems, etc. His researches are awarded as outstanding papers by various academic societies, e.g., IEEE Top Conference Series, etc.. He has one Invention Patent approved by China National Intellectual Property Administration in 2024 and one Technology Transfer approved by (U.S.A.) Bell Labs (Now called Nokia Bell Labs) during 1998-1999. He received his Ph.D degree in applied mathematics jointly with industrial engineering and systems engineering from Georgia Institute of Technology, Atlanta, GA, U.S.A., in 1996, where he worked on stochastics and applied probability concerning network performance modeling and analysis, algorithm design and implementation via stochastic diffusion approximation. The breakthrough results and methodologies developed in his thesis were cited, used, and claimed as “contemporaneous and independent” achievements by some other subsequent breakthrough papers that were presented as “45 minute invited talk in probability and statistics” in International Congress of Mathematicians (ICM) 1998, which is the most privilege honor in the mathematical society. The designed finite element-Galerkin algorithm to compute the stationary distributions of reflecting Brownian motions (weak solutions of general dimensional partial differential equations) is also well-known to the related fields.
Prof. Jinping Zhang
University of Electronic Science and Technology of China
Bio: Jinping ZHANG received the Ph.D. degree from University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2009. He is currently a Professor with UESTC. His research interests include semiconductor power devices and integrated circuits.
Assoc. Prof. James Tan Swee Chuan
Singapore University of Social Sciences, Singapore
Bio: Associate Professor James Tan Swee Chuan serves as Head of the Business Analytics Programme at the School of Business, Singapore University of Social Sciences (SUSS), Singapore. He earned his PhD in Information Technology from Monash University, alongside a Master of Information Technology and a Bachelor of Information Technology from the University of Southern QueenslandSingapore
Before joining academia, he worked as an engineer at ST Electronics and Compaq Asia, bringing rich industry engineering experience. His research focuses on business analytics, decision trees, anomaly detection, ensemble learning and clustering. He has published extensively in top journals and conferences and won multiple best paper awards.
He has undertaken consultancy projects for organisations including Shanghai Rural Commercial Bank, SPSS Singapore and Danfoss Asia Pacific. He also collaborated on anomaly detection research funded by the US Air Force Office of Scientific Research. At SUSS, he leads curriculum development and teaching for business analytics, bridging data science theories with real-world business applications.