On Succinct Representation of Combinations and Graphs
Department of Modern Mechanical Engineering
Graphs and combinatorial objects have become relevant mechanisms enabling effective modelling and operation of interdependent systems ubiquitously. Also, the related research in Reliability Engineering, Robotics, Machine Learning, Chemistry, Material Science, and Cognitive Science has provided various approaches to model high-performing systems by using such concepts. Yet, the modelling of very large combinatorial and adaptive systems still poses a daunting task requiring exhaustive human intervention and being extremely difficult for the current technology. In this talk, I present my insights on new representation schemes able to handle relevant large-scale combinatorial concepts achieving the state-of-the-art performance/efficiency.
Victor Parque is Associate Professor at the Department of Modern Mechanical Engineering, Waseda University. He obtained the B.Sc. in Systems Engineering, from National Central University, 2004, the MBA from the Graduate School of Business Administration, Esan University, 2009, and the Ph.D. from the Graduate School of Information, Production and Systems, Waseda University, 2011. He was Post-Doctoral Fellow at the Department of Mechanical Engineering, Toyota Technological Institute in 2012-2014. His research interests span the principles in learning and intelligence (artificial intelligence), and the practical applications in control, planning and design engineering. He is the first author of more than 70 articles in conferences, book chapters and journals, and is actively involved in research collaboration with both industry and academia. He was honoured as finalist in the Hummies Awards for Human-Competitive Results, in 2018, and was honoured several sole and joint grants from academia an industry. He is member of IEEE (RAS, IES, SMC), ACM (SIGAI, SIGEVO), Robotics Society of Japan (RSJ), Japan Society for Precision Engineering (JSPE) and Japan Society for Design Engineering (JSDE).