Keynote Speakers

 

Prof. Saman Halgamuge
The University of Melbourne, Australia

Prof Saman Halgamuge is a Fellow of IEEE, a Professor in the Department of Mechanical Engineering of School of Electrical, Mechanical and Infrastructure Engineering. He is a highly cited expert in his field and listed as one of the top 2% cited experts for AI and Image Processing in the Stanford University Database published in 2020. His most-cited paper being "Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients", with over 3300 citations, according to GoogleScholar. He is a Distinguished Speaker/Lecturer on Computational Intelligence appointed by IEEE. He has supervised 45 PhD scholars to completion and delivered over 50 keynotes at International and national conferences. He has previously served as Director/Head, Research School of Engineering of the Australian National University (2016-18) and as a member of Australian Research Council (ARC) College of Experts for Engineering, Information and Computing Sciences (2016-18). He was the founding Director of the PhD training centre Melbourne India Postgraduate Program (MIPP) of University of Melbourne and contributed as Associate Dean (2013-15) and Assistant Dean (2008-13) in International Engagement at the Faculty of Engineering and IT. He is also a member of various International advisory committees including the Visiting Committee of Chinese University of Hong Kong (2018) and Research Advisory Council of University of Technology PETRONAS (2015-18). He is an honorary Professor of Australian National University. His research interests are in AI and Data Engineering including Inclusive Learning algorithms and Active data gathering sensor systems, Unsupervised Learning, Big Data Analytics focusing on applications in Mechatronics, Energy and Bioengineering. These applications vary from Sensor Networks in Irrigation, Smart Grids, and Sustainable Energy generation to Bioinformatics and Neuro-Engineering.

 

Prof. Weinan Gao

Northeastern University, Shenyang, China
Weinan Gao received the Ph.D. degree in Electrical Engineering from New York University, Brooklyn, NY, USA. He is a Professor with the State Key Laboratory of Synthetical Automation for Process Industries at Northeastern University, Shenyang, China. Previously, he was an Assistant Professor of Mechanical and Civil Engineering at Florida Institute of Technology, Melbourne, FL, USA, an Assistant Professor of Electrical and Computer Engineering at Georgia Southern University, Statesboro, GA, USA, and a Visiting Professor of Mitsubishi Electric Research Laboratory (MERL), Cambridge, MA, USA. His research interests include reinforcement learning, adaptive dynamic programming (ADP), optimal control, cooperative adaptive cruise control (CACC), intelligent transportation systems, sampled-data control systems, and output regulation theory. Prof. Gao is the recipient of the best paper award in IEEE Data Driven Control and Learning Systems (DDCLS) Conference in 2023, IEEE International Conference on Real-time Computing and Robotics (RCAR) in 2018 and the David Goodman Research Award at New York University in 2019. He is an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, IEEE/CAA Journal of Automatica Sinica, Control Engineering Practice, Neurocomputing and IEEE Transactions on Circuits and Systems II: Express Briefs, a member of Editorial Board of Neural Computing and Applications, and a Technical Committee member in IEEE Control Systems Society on Nonlinear Systems and Control, IFAC TC 1.2 Adaptive and Learning Systems, and CAAI Industrial Artificial Intelligence.

 

Invited Speakers

 

Prof. Athakorn Kengpol

King Mongkut’s University of Technology North Bangkok, Thailand

Dr. Athakorn Kengpol is Professor of Industrial Engineering at the Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, Thailand. He received his PhD in Manufacturing Engineering and Operations Management from The University of Nottingham, UK. He obtained his Post-doctoral Research at University of Innsbruck, Austria and at Lappeenranta University of Technology, Finland. His research interests include Artificial Intelligence, Machine/Deep Learning, Decision Support Systems in Industry 4.0, management information systems and packaging design. His National Awards are, for example, National Outstanding Lecturer, National Outstanding Government Officer etc. His International Awards are, for example, Medal from International Exhibition of Geneva, Switzerland, and Industry Solutions Award from IEOM Society International, USA. He conducted and published research about Machine Learning and Deep Learning in a number of reputable journals, for example, International Journal of Production Economics, International Journal of Production Research, Expert Systems with Applications, Computers and Industrial Engineering etc. He also participated in MSIE-CBHE Erasmus+ Curriculum Development of Master’s Degree Program in Industrial Engineering for Thailand Sustainable Smart Industry (MSIE4.0) funded by the European Commission, and ReCap 4.0 that is proposed to enhance the capacity and ability of the non-university sector at the tertiary level in Thailand for the effective delivery of engineering and technology knowledge and skills related to Industry 4.0 to support Thailand Sustainable Smart Industry.

 

Assist Prof. Damiano Di Francesco Maesa

University of Pisa, Italy

Damiano Di Francesco Maesa is Assistant professor at the department of computer science of the University of Pisa, Italy. His past positions include College Research Associate at Clare College of the university of Cambridge, Research Associate at the Innovation and Intellectual Property Management Laboratory of the University of Cambridge, Research Associate at the Computer Lab of the University of Cambridge, Research Associate at King's college London, and Research Assistant at the National Research Institute in Pisa, Italy. He has a PhD in Computer Science from the University of Pisa and specializes in the analysis and study of novel applications of blockchain and Distributed Ledger Technologies (DLT). Beside his academic contributions, he has held several guest lectures, seminars, and workshops to spread awareness on blockchain technology.

 

Dr. Ching-Chun Chang

National Institute of Informatics, Japan

Dr. Ching-Chun Chang received his PhD in Computer Science from the University of Warwick, UK, in 2019. He participated in a short-term scientific mission supported by European Cooperation in Science and Technology Actions at the Faculty of Computer Science, Otto-von-Guericke-Universität Magdeburg, Germany, in 2016. He was granted the Marie-Curie fellowship and participated in a research and innovation staff exchange scheme supported by Marie Skłodowska-Curie Actions at the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, USA, in 2017. He was a Visiting Scholar with the School of Computer and Mathematics, Charles Sturt University, Australia, in 2018, and with the School of Information Technology, Deakin University, Australia, in 2019. He was a Research Fellow with the Department of Electronic Engineering, Tsinghua University, China, in 2020. He is currently a researcher with the National Institute of Informatics, Japan. His research interests include steganography, forensics, biometrics, cybersecurity, computer vision, computational linguistics and artificial intelligence.

 


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