Computational Intelligence and Applications|计算智能与应用

Keynote&Plenary Speakers for ICCIA 2018

IEEE Fellow, Prof. David Zhang, Chinese University of Hong Kong (Shenzhen), China

Speech Title: Facial Multi-Characteristics and Applications

Abstract: What features could we extract from a face and how about their applications for each given feature? In fact, we could find multi-characteristics from a face, which may get two main kinds of features, e.g., original (or physiological) features and changed features during a lifetime. As a result, there will be some different applications, including facial identification in original special features, beauty analysis in original common features, facial diagnosis by disease changed features, and expression recognition by affect changed features. This presentation will define these different features extracted from a face and provide their typical applications. Experimental results of the performance under different application challenges have shown the superiority of these multi-characteristics.

Biography: David Zhang graduated in Computer Science from Peking University. He received his MSc in 1982 and his PhD in 1985 in Computer Science from the Harbin Institute of Technology (HIT), respectively. From 1986 to 1988 he was a Postdoctoral Fellow at Tsinghua University and then an Associate Professor at the Academia Sinica, Beijing. In 1994 he received his second PhD in Electrical and Computer Engineering from the University of Waterloo, Ontario, Canada. He is a Chair Professor since 2005 at the Hong Kong Polytechnic University where he is the Founding Director of the Biometrics Research Centre (UGC/CRC) supported by the Hong Kong SAR Government in 1998. Afterwards, he has moved to Chinese University of Hong Kong (Shenzhen), China. He also serves as Visiting Chair Professor in Tsinghua University, and Adjunct Professor in Peking University, Shanghai Jiao Tong University, HIT, and the University of Waterloo. He is Founder and Editor-in-Chief, International Journal of Image and Graphics (IJIG); Founder and and Series Editor, Springer International Series on Biometrics (KISB); Organizer, the 1st International Conference on Biometrics Authentication (ICBA); Associate Editor of more than ten international journals including IEEE Transactions and so on. So far, he has published over 10 monographs, 400 international journal papers and 35 patents from USA/Japan/HK/China. According to Google Scholar, his papers have got over 34,500 citations and H-index is 86. He was selected as a highly cited researcher in Engineering by Thomson Reuters in 2014 and in 2015, respectively. Professor Zhang is a Croucher Senior Research Fellow, Distinguished Speaker of the IEEE Computer Society, and a Fellow of both IEEE and IAPR.

IEEE Fellow, Prof. C. L. Philip Chen, Dean and Chair Professor of Faculty of Science and Technology, University of Macau, Macau

Speech Title: Universal Approximation Capability of Broad Learning System and its Structural Variations

Abstract: After a very fast and efficient discriminative Broad Learning System (BLS) that takes advantage of flatted structure and incremental learning has been developed, this talk will discuss mathematical proof of the universal approximation property of BLS. In addition, the framework of several BLS variants with their mathematical modellings are given. The variations include cascade, recurrent, and broad-deep combination that cover existing deep-wide/broad-wide structures. From the experimental results, the BLS and its variations outperforms several exist learning algorithms on regression performance over function approximation, time series prediction, and face recognition databases.

Biography: Dr. Chen’s research areas are in systems, cybernetics and computational intelligence. He is a Fellow of the IEEE, AAAS, and IAPR. He was the President of IEEE Systems, Man, and Cybernetics Society (SMCS) (2012-2013), where he also has been a distinguished lecturer for many years and received Outstanding Service Awards 4 times. Currently, he is the Editor-in-Chief of IEEE Transactions on Systems, Man, and Cybernetics: Systems (2014-). He has been an Associate Editor of several IEEE Transactions, and currently he is an Associate Editor of IEEE Trans on Fuzzy Systems, IEEE Trans on Cybernetics, and IEEE/CAA Automatica Sinica. He was the Chair of TC 9.1 Economic and Business Systems of IFAC (2015-2017). He is also a Fellow of CAA and Fellow of HKIE and an Academician of International Academy of Systems and Cybernetics Science (IASCYS). In March 2018, he is listed in world top 14 having the most highly cited paper in computer science area by WoS.

In addition, he is an ABET (Accreditation Board of Engineering and Technology Education, USA) Program Evaluator for Computer, Electrical, and Software Engineering programs. University of Macau’s Engineering and Computer Science programs receiving HKIE’s accreditation and Washington/Seoul Accord is his utmost contribution in engineering education for Macau as the former Dean. During his deanship, the engineering and computer science programs both have been ranked at world top 200 in the Times Higher Education (THE) world university ranking. The computer science program is also ranked at world top 161 in the US News and World Report global university ranking. Dr. Chen received Outstanding Electrical and Computer Engineering Award in 2016 from his alma mater, Purdue University, West Lafayette, where he received his Ph.D. degree in 1988, after he received his M.S. degree in electrical engineering from the University of Michigan, Ann Arbor, in 1985.

 

Prof. Manuel Núñez, Complutense University of Madrid, Spain

Speech Title: An Application of Fuzzy Automata to Analyze Heart Data

Abstract: In this talk I will briefly introduce a formalism to represent system where uncertainty plays an important role. I will define its syntax and semantics. Finally, I will show how this formalism can be successfully applied to define and analyze information extracted from electrocardiograms (ECGs) with the goal of identifying potential illnesses. 

Biography: Manuel Núñez is a Professor in the Department of Computer Systems and Computation of the Complutense University of Madrid, Spain. He holds a Doctorate degree in Mathematics & Computer Science, obtained in 1996. Additionally, he holds a Master degree in Economics, obtained in 2002. 

He has done research in the broad field of formal methods. Currently, he is interested in the study of formal methods for testing complex systems. Specifically, he has three main lines of research:

* Formal analysis of systems with distributed testers, in particular, those where time and probabilities play an important role.

* Passive testing of multi-user systems with asynchronous communications.

* Specification and testing of health related systems. 

Manuel Núñez belongs to the following scientific committees:

* IEEE SMC Technical Committee on Computational Collective Intelligence,

* Board of Directors of the Tarot Summer School on Software Testing,

* ICCCI Steering Committee,

* A-MOST Workshop Steering Committee

He is a member of several Editorial Boards of journals and has served in more than 130 Program Committees of international events in Computer Science. He has published more than 130 papers in international scientific journals and meetings.

Prof. Ning Xiong, Mälardalen University, Sweden

Speech Title: Fuzzy and Case-Based Reasoning

Abstract: Fuzzy and case-based reasoning (CBR) reflect two cognitive aspects of human thinking. On one hand people receive a lot of imprecise and vague information in daily life and they can use such information for reasoning in an approximate way. On the other hand, humans also have the talent to utilize previous experiences for efficient problem solving via a case-based approach. A promising research topic is how to achieve synergy between fuzzy and case-based reasoning in building intelligent and learning systems. This talk will start with basic concept and principle of CBR. Then I will try to reveal the inherent relation between the two seemingly separated areas.  Some research efforts to build hybrid fuzzy-CBR systems will be outlined.

Biography: Ning Xiong obtained the Ph.D with outstanding distinction from the University of Kaiserslautern (Germany) in 2000. His research addresses various aspects of computational intelligence techniques, incuding machine learning and big data analytics, evolutionary computing, fuzzy systems, uncertainty management, as well as multi-sensor data fusion, for building self-learning and adaptive systems in industrial and medical domains. He is serving as editorial board members for three international journals. He has been lead guest editor for a special issue in the journal "Neural Processing Letters" (Springer). He also has been programme committee members for a number of conferences and invited referee for many leading international journals.

Prof. William W. Song, Dalarna University, Sweden

Speech Title: Does Semantic Structure Guide Logic Reasoning in Big Data?

Abstract: Although (big) data, nowadays, have become a huge asset with powerful data analysis tools which can dig into every detail of our society, however, many data may not convey a single concept – semantics of a single word (a piece of knowledge) which appears very straightforward to people, let along reasoning about concepts and their links. This presentation intends to build a connection between semantic structures (knowledge representation in AL in particular) with analysis and reasoning, including data reasoning, logic reasoning, and semantic reasoning. We aim to investigate how description logic methods can support big data analysis and make data more meaningful.

Biography: William Wei Song received his BSc in computer science from Zhejiang University, Hangzhou, China in 1982 and PhD in information systems and sciences from Stockholm University and the Royal institute of Technology, Stockholm, in Sweden in 1995.

He started his career at a university in 1982. After receiving his PhD degree, he became staff researcher at SISU, Sweden from 1995, senior researcher at ETI, Hong Kong University, China from 1999, and associate professor at Durham University, UK, from 2003. He is now a full professor in Business Intelligence and Information Systems at Dalarna University, Sweden. His research interest covers a wide range of fields, including computer science, information systems, artificial intelligence, semantic web, service science, business intelligence, e-business, e-learning, and online education. He has published more than 100 research papers in international journals and conferences.

Professor Song is also guest professor (researcher) of a number of overseas universities and sits at the board of a number of international journals.