Koenig Endowed Chair Professor, Electrical and Computer Engineering
Director, Computational Optimization and Innovation (COIN) Laboratory
Michigan State University, USA kdeb@msu.edu
Kalyanmoy Deb is University Distinguished Professor and Koenig Endowed Chair Professor at Department of Electrical and Computer Engineering in Michigan State University, USA. Prof. Deb's research interests are in evolutionary optimization and their application in multi-criterion optimization, modeling, and machine learning. He has been a visiting professor at various universities across the world including University of Skövde in Sweden, Aalto University in Finland, Nanyang Technological University in Singapore, and IITs in India. He was awarded IEEE Evolutionary Computation Pioneer Award for his sustained work in EMO, Infosys Prize, TWAS Prize in Engineering Sciences, CajAstur Mamdani Prize, Distinguished Alumni Award from IIT Kharagpur, Edgeworth-Pareto award, Bhatnagar Prize in Engineering Sciences, and Bessel Research award from Germany. He is fellow of IEEE, ASME, and three Indian science and engineering academies. He has published over 620 research papers with Google Scholar citation of over 215,830 with h-index 143 and i10-index 646. He is in the editorial board on 10 major international journals. More information about his research contribution can be found from https://www.coin-lab.org.
Professor, Department of Electrical Engineering and Information Systems
The University of Tokyo, Japan
Akira Hirose received the Ph.D. degree in electronic engineering from the University of Tokyo in 1991. In 1987, he joined Research Center for Advanced Science and Technology (RCAST), the University of Tokyo, as Research Associate. In 1991, he was appointed as Instructor at RCAST. From 1993 to 1995, on leave of absence from the University of Tokyo, he joined the Institute for Neuroinformatics, University of Bonn, Bonn, Germany. He is currently Professor with the Department of Electrical Engineering and Information Systems, the University of Tokyo. The main fields of his research interests are wireless electronics and neural networks. In the fields, he published several books such as Complex-Valued Neural Networks, 2nd Edition (Springer 2012). He served as the Founding President of Asia-Pacific Neural Network Society (APNNS) (2016), President of Japanese Neural Network Society (JNNS) (2013-2015), Vice President of the IEICE Electronics Society (ES) (2013-2015), Editor-in-Chief of the IEICE Transactions on Electronics (2011-2012), Associate Editor of journals such as the IEEE TRANSACTIONS ON NEURAL NETWORKS (2009-2011), IEEE GEOSCIENCE AND REMOTE SENSING NEWSLETTER (2009-2012), Chair of the Neurocomputing Technical Group in the IEICE, Founding Chair of the IEEE CIS NNTC Complex-Valued Neural Network Task Force (2010-), Governing Board Member of APNNA/APNNS (2006-), IEEE Geoscience and Remote Sensing Society (GRSS) All Japan Chapter Chair (2013-2015) and IEEE Computational Intelligence Society (CIS) All Japan Chapter Chair (2017- 2018). He also served as the General Chair of Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) 2013 Tsukuba, International Conference on Neural Information Processing (ICONIP) 2016 Kyoto, and International Geoscience and Remote Sensing Symposium (IGARSS) 2019 Yokohama. Dr. Hirose is a Fellow of the IEEE and the IEICE, and a member of JNNS and APNNS.
Professor of Computer Science and Oden Institute of Computational Engineering and Sciences
The University of Texas at Austin, USA
Prof. Bajaj’s current research is on the computer science and computational mathematics foundations of statistical and dynamic decision making, learning dynamical systems and exploratory visualization. He develops machine learning and geometric optimization algorithms for applications in the physical, chemical, health and environmental data sciences, medicine and neuro-morphic computing. Prof. Bajaj revisits his past research in modeling multi-scale form and function, through the lens of inferential data sciences. Prof. Bajaj’s current research projects include (a) forward and inverse optimization problems in microscopy, spectroscopy, electro-magnetic and electro-optical wide spectrum imaging; (b) generative shape and new material design for spatially realistic and phenomenological models; (c) learning from nature and generating models and mechanisms with accelerated and emergent properties. He also teaches an undergraduate course titled “Geometric Foundations of Data Sciences” and a graduate course titled “Predictive Machine Learning”. Prof. Bajaj has courtesy appointments and supervise undergraduates, M.S. and Ph.D. students from several UT departments, including biomedical and electrical engineering, neuroscience, and mathematics.
The following is a link to his most cited publications:
http://scholar.google.com/citations?user=gyL3CZ0AAAAJ"&user=gyL3CZ0AAAAJ
Global Head, NVIDIA AI Technology Centre, Singapore
Prof. Simon See is the Global Head, NVIDIA AI Technology Centre, Singapore. He is also a renowned Professor and Chief Scientific Computing Officer in Shanghai Jiao Tong University. Prof. Simon See is also the Adjunct Professor of the Department of Computer Science & Engineering, Mahindra University. He is currently involved in a number of smart city projects, especially in Singapore and China. His research interests are in the area of High Performance Computing, Big Data, Artificial Intelligence, machine learning, computational science, Applied Mathematics and simulation methodology. Prof. See is also leading some of the AI initiatives in Asia Pacific.
He has published over 200 papers in these areas and has won numerous awards in the field. Prof. See is also a member of SIAM, IEEE and IET. He is also a committee member of more than 50 conferences.
Prof. See graduated from University of Salford (UK) with a PhD in electrical engineering and numerical analysis in 1993. Prior to joining NVIDIA, Dr. See worked for SGI, DSO National Laboratory of Singapore, IBM, International Simulation Ltd (UK), Sun Microsystems and Oracle. He is also providing consultancy to a number of national research and supercomputing centres.