PhD - Computer Science
BSc - Electrical Engineering
FIEEE, FBCS, FICICC, FWIF, P.Eng.
Teaching has been one of the inspiring contexts of Dr. Wang's research for systematic and transdciplinary knowledge development. A series of 26+ courses have been developed and/or taught in computer science, software engineering, computational intelligence, cognitive science, and denotational mathematics such as follows:
Numerical Methods in Engineering (ENGG 407)
Formal Methods (SENG 523)
Theoretical Foundations of Software Engineering (ENSF 604)
Special Topics Denotational Mathematics for SE and Computational Intelligence (ENSF 619)
Software Engineering Standards and Models (SENG 629)
Dr. Wang and his lab’s research interests across 10+ disciplines encompassing intelligence science, brain science, computer science/engineering, software science/engineering, denotational mathematics, robotics, neural science, cognitive linguistics, system science, knowledge science, and data science. A series of basic studies and innovative projects have led to 480+ publications (36 invited keynotes speeches, 186 journal papers, 285 conference papers, and 29 books/proceedings).
The creation of synergistic knowledge has led to the development of and breakthroughs in a few cutting-edge research fields such as cognitive computers (computers for knowledge processing), cognitive informatics (theoretical foundations of the brain, abstract intelligence, and brain-inspired systems), mathematical models of the brain, cognitive robotics, denotational mathematics (such as concept algebra, semantic algebra, process algebra, inference algebra, system algebra, big data algebra, fuzzy truth algebra, fuzzy probability algebra, visual semantic algebra, and granular algebra), and the neural circuit theory. A set of novel technologies developed in his lab has attracted significant industrial sponsorship on cognitive robotics, cognitive computers, cognitive knowledge bases, deep machine learning engines, semantic search engines, and formal language translation systems.
Dr. Yingxu Wang is professor of cognitive informatics, brain science, software science, and denotational mathematics. He is the founding President of International Institute of Cognitive Informatics and Cognitive Computing (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 has been visiting professor (on sabbatical leaves) at Oxford University (1995), Stanford University (2008 | 2016), UC Berkeley (2008), and MIT (2012), respectively. He 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 International Journal of Cognitive Informatics & Natural Intelligence; International Journal of Software Science & Computational Intelligence; Journal of Advanced Mathematics & Applications; and Journal of Mathematical & Computational Methods, as well as Associate Editor of IEEE Trans. on SMC - Systems. He has served as chair or co-chair of 19 IEEE or other int’l conferences and a member of IEEE Selection Committee for Senior Members in 2011.
Dr. Wang’s publications have been cited for 30,000+ times according to Google Scholar. According to Research Gate statistics, his research profile has reached top 2.5 per cent worldwide, top one to 10 (timely vary in the range) at the University of Calgary, and the most read work in neural networks. He is the recipient of dozens international awards on academic leadership, outstanding contributions, best papers, and teaching in the last three decades.
Cross appointments and affiliations:
- President, The International Institute of Cognitive Informatics and Cognitive Computing (ICIC)
- Director, Lab for Computational Intelligence, Cognitive Systems, Denotational Mathematics, and Software Science
- Professor (Brain Science), The Hotchkiss Brain Institute (HBI)
- Theoretical & Empirical Software Engineering Research Center
Graduate student employment:
New PhD students are welcome on exploratory and innovative projects such as: a) Cognitive robotics; b) Deep machine learning; c) Cognitive systems; d) Software science theories; and e) Industry-sponsored projects.
Both theoretical (mathematical) and experimental (programming/MATLAB) skills are expected for strong candidates. Due to numerous applications, Dr. Wang regrets if a timely correspondence might not be sent.
Wang, Y. (2016). On Cognitive Foundations and Mathematical Theories of Knowledge Science, International Journal of Cognitive Informatics and Natural Intelligence, 10(2), 1-24.
Wang, Y. (2016). Big Data Algebra (BDA): A Denotational Mathematics for Big Data Science and Engineering, Journal of Advanced Mathematics and Applications, 5(1), 1-25.
Wang, Y. and G. Fariello (2012), On Neuroinformatics: Mathematical Models of Neuroscience and Neurocomputing, Journal of Advanced Mathematics and Applications, 1(2), 206-217.
Wang, Y. (2010). Cognitive Robots: A Reference Model towards Intelligent Authentication, IEEE Robotics and Automation, 17(4), 54-62.
Wang, Y. (2007). Software Engineering Foundations: A Software Science Perspective, Auerbach Publications (CRC), NY, USA, 1, 488pp.
For additional publications, visit ResearchGate.
- Awards (15 times) for outstanding contributions to the organization of the IEEE ICCI*CC’02 through ICCI*CC’16, The IEEE Steering Committee of ICCI*CC Series and ICIC, 2002-2016
- Recognition Award, U of C, 2015
- National Zhan Tianyou Young Scientist Prize and Gold Medal (one of the first ten recipients), National Science & Technology Foundation, China, 1994