Welcome to the official website of IISA2017£¡
Dr.Zhang: 15387118351
Tel: 027-87153536
QQ: 3357066350
Email: iisa2017@163.com

Advances in Intelligent Systems and Computing
£¨ISSN: 2194-5357£©
The latest journal in an EI journal list, click here to download a screenshot (row 137 in the list)
Keynote Speaker


Prof.Dr.Yingxu Wang, PhD, PEng, FICIC,FWIF, SMIEEE, SMACM President, International Institute of Cognitive Informatics and Cognitive Computing (ICIC) Dept. of Electrical and Computer Engineering,Schulich School of Engineering and Hotchkiss Brain Institute University of Calgary 2500 University Drive, NW, Calgary, Alberta, Canada T2N 1N4
Tel: (403) 220 6141, Fax: (403) 282 6855
http://www.ucalgary.ca/icic/  ,  Email: yingxu@ucalgary.ca

Yingxu Wang is professor of cognitive informatics, brain science, software science, and denotational mathematics. He is President of International Institute of Cognitive Informatics and Cognitive Computing (ICIC, http://www.ucalgary.ca/icic/). He is a Fellow of ICIC, a Fellow of WIF (UK), a P.Eng of Canada, and a Senior Member of IEEE and ACM. He is/was visiting professor (on sabbatical leave) at Oxford University (1995), Stanford University (2008|2016), UC Berkeley (2008), and MIT (2012), respectively. He received a PhD in Computer Science from the Nottingham Trent University in 1998 and has been a full professor since 1994. He is the founder and steering committee chair of the annual IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC) since 2002. He is founding Editor-in-Chief of Int¡¯l Journal of CognitiveInformatics & Natural Intelligence, founding Editor-in-Chief of Int¡¯l Journal of Software Science & Computational Intelligence, Associate Editor of IEEE Trans. on SMC - Systems, Editor-in-Chief of Journal of Advanced Mathematics & Applications, and Editor-in-Chief of Journal of Mathematical &Computational Methods. 
Dr. Wang is the initiator of a few cutting-edge research fields such as cognitive informatics, denotational mathematics (concept algebra, process algebra, system algebra, semantic algebra, inference algebra, big data algebra, fuzzy truth algebra,fuzzy probability algebra, fuzzy semantic algebra, visual semantic algebra, and granular algebra), abstract intelligence (I), the neural circuit theory, mathematical models of the brain,  cognitive computing, cognitive learning engines, cognitive knowledge base theory, and basic studies across contemporary disciplines of intelligence science, robotics, knowledge science, computer science, information science, brain science, system science, software science, data science, neuroinformatics, cognitive linguistics, and computational intelligence. He has published 400+ peer reviewed papers and 29 books in aforementioned transdisciplinary fields. He has presented 30 invited keynote speeches in international conferences. He has served as general chairs or program chairs for more than 20 international conferences. He is the recipient of dozens international awards on academic leadership, outstanding contributions, best papers, and teaching in the last three decades. He is a top 2.5% scholar worldwide according to the big data system of ResearchGate¡¯s international stats.

Speech Title:On Cognitive and Mathematical Theories of Contemporary Intelligence Science and Brain Informatics

Both fundamental challenges and curiosities to contemporary sciences of humanityhaverecently refocused on the brain and natural intelligence where the next generation of theories and technologies rely upon indispensably.Intelligenceis recognized as a driving force and an ability to acquire and use knowledge and skills, or to efficiently inference in problem solving. Intelligence science is a discipline that studies the mechanisms and theories of abstract intelligence and its paradigms such as natural, abstract, artificial, machinable, and computational intelligence.
This keynote lecture presents a theoretical framework of intelligence science and brain informatics.A set of cognitive models and mathematical theories for rigorously modeling the brain and abstract intelligence is elaboratedin abstract intelligence, essences of knowledge and wisdoms, the Layered Reference Model of the Brain (LRMB), the Cognitive Structural Model of the Brain (CSMB), the Cognitive Functional Model of the Brain (CFMB), cognitive informatics, brain informatics, cognitive robotics, and denotational mathematics. Latest findings and breakthroughs in the fields are reported. A wide range of applications of the theories of intelligence and brain sciences are revealed in brain-inspired systems, cognitive systems, cognitive knowledge bases, deep machine learning engines, downloadable wisdom, machine learning assistants, machine semantic analyzers, intelligent translators, and cognitive robots.

Keywords:Intelligence science, cognitive informatics, brain science, neuroinformatics, knowledge science, denotational mathematics, computational intelligence, artificial intelligence, cognitive models of the brain, brain-inspired systems, cognitive systems, cognitive robotics, and applications

Prof.Dr.Sam Kwong

Department of Computer Science City University of Hong Kong
83 Tat Chee Avenue, Kowloon £¬Hong Kong

Sam Kwong received the B.Sc. degree from the State University of New York at Buffalo, Buffalo, NY, in 1983, the M.A.Sc. degree in electrical engineering from the University of Waterloo, Waterloo, ON, Canada, in 1985, and the Ph.D. degree from the Fernuniversität Hagen, Hagen, Germany, in 1996. From 1985 to 1987, he was a Diagnostic Engineer with Control Data Canada, where he designed the diagnostic software to detect the manufacture faults of the VLSI chips in the Cyber 430 machine. Currently, he is the associate editor of Evolutionary Computation, the Associate Editor for the IEEE Transactions On Industrial Informatics, the IEEE Transactions on Industrial Electronics, the Journal of Information Science. He is the Head and Professor of the department of Computer Science, City University of Hong Kong. He is also the Vice President for IEEE Systems, Man and Cybernetics for conferences and meetings. Prof. Kwong was elevated to IEEE fellow for his contributions on Optimization Techniques for Cybernetics and Video coding in 2014. His research areas are in Pattern Recognition, Evolutionary Computations and Video Analytics

Speech Title: Stable Matching-Based Selection in Evolutionary Multiobjective Optimization

Multiobjective problems are always aroused in our daily life in that we have to make decisions based on many different objectives. Recently, Multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem into a set of scalar optimization subproblems and optimizes them in a collaborative manner. This approach has been proved to be the state of the art method in solving multi-objective/many objective problems. In MOEA/D, subproblems and solutions are modelled as two sets of agents for matching. Thus, this kind of selection of promising solutions for subproblems can be regarded as a matching between subproblems and solutions. This problem could be viewed as a Stable matching problem as for school admission, hospital residents problems. Also, it can effectively resolve conflicts of interests among selfish agents in the economic market. In this talk, I will advocate the use of a simple and effective stable matching (STM) model to coordinate the selection process in MOEA/D. In this model, subproblem agents can express their preferences over the solution agents, and vice versa. The stable outcome produced by the STM model matches each subproblem with one single solution, and it tradeoffs convergence and diversity of the evolutionary search. In addition, a two-level stable matching-based selection is proposed to further guarantee the diversity of the population. More specifically, the first level of stable matching only matches a solution to one of its most preferred subproblems and the second level of stable matching is responsible for matching the solutions to the remaining subproblems. Experimental studies demonstrate that the proposed selection scheme is effective and competitive comparing to other state-of-the-art selection schemes for MOEA/D.

© Copyright IISA 2015-2017. All Rights Reserved. | Powered by IISA2017