Dept. of Electrical and Computer Engineering, Schulich School of Engineering and Hotchkiss Brain Institute, University of Calgary, Alberta, Canada.
Yingxu Wang is professor of cognitive systems, brain science, software science, and denotational mathematics. He is the Founding President of International Institute of Cognitive Informatics and Cognitive Computing (ICIC, http://www.ucalgary.ca/icic/). He is Fellows of BCS, ICIC and WIF, P.Eng of Canada, and Senior Members of IEEE and ACM. He has held visiting professor positions 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, UK, 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-Chiefs of Int’l Journal of Cognitive Informatics & Natural Intelligence, Int’l Journal of Software Science & Computational Intelligence, and Journal of Mathematical & Computational Methods. He is Associate Editor of IEEE Trans. on Cognitive and Development Systems (TCDS) and the Computer Society Representative to the steering committee of TCDS.
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 (aI), the spike frequency modulation (SFM) theory, mathematical models of the brain, cognitive computing systems, cognitive learning engines, and the cognitive knowledge base theory. His work and basic studies have been across contemporary disciplines of intelligence science, robotics, knowledge science, computer science, information science, brain science, system science, software science, data science, neuroinformatics, cognitive linguistics, computational intelligence, and engineering systems. He has published 490+ peer reviewed papers and 36 books in aforementioned transdisciplinary fields. He has presented 43 invited keynote speeches in international conferences. He has served as honorary, general, and program chairs for more than 28 international conferences. He has led 10+ international, European, and Canadian research projects as PI by intensive collaborations with renowned peers and leading industrial partners. He is the recipient of dozens international awards in the last three decades. He is a top 2.5% scholar worldwide and top 10 at University of Calgary according to Research Gate’s international statistics.
Intelligence is a human or system ability that autonomously transfers a piece of information into a behavior or an item of knowledge. Intelligence science studies the general form of intelligence, formal principles and properties of intelligence, as well as engineering and computational implementations. An advanced form of intelligence is embodied by autonomous systems, which encompass nondeterministic and context-dependent behaviors towards perceptive, problem-driven, goal-driven, decision-driven, and deductive intelligence.
The fundamental constraints for AI have led to systematic studies in intelligence science that leads to latest breakthroughs towards autonomous systems beyond adaptive systems constrained by deterministic conventional computing technologies. This keynote talk presents the latest development in autonomous systems underpinned by the theories of intelligence, brain, and cognitive sciences. It reveals the adaptive bottleneck of intelligent systems constrained by traditional computational intelligence theories. The theoretical findings indicate that AI may not merely mimic imperative and iterative intelligence, but also implement more flexible human intelligence according to the abstract intelligence (aI) theory. The framework of a number of novel autonomous and cognitive systems will be demonstrated encompassing cognitive robots, cognitive machine learning systems, and cognitive neural networks (CNN).
Keywords — Intelligence science, AI, abstract intelligence (aI), computational intelligence, cognitive systems, cognitive robots, brain-inspired systems, cognitive learning engine, denotational mathematics, applications
June 26-28, 2020
Notification of Acceptance:
Camera Ready Submission Due:
Phone: 153 8711 8351
1.All submitted papers MUST be written in English.
2.Any submission must not have been, or will not be published elsewhere or submitted to another conference before the review notification date of this conference.
3.All submissions will be peer-reviewed based on originality, technical quality and presentation.
4.Each paper should be at least 4 pages or longer.
5.To complete the paper plan in advance and expand the scale of the meeting, IISA2020 encourages you to recommend more manuscripts
6.Article repetition rate cannot be higher than 18%, otherwise it will be rejected directly.
7.If you have a brilliant contribution in Information and Communication Technology area, and willing to serve as a TPC/Keynote Speaker, Please send your CV via email .
8.If your university is willing to serve as the conference co-organizer, please contact directly.