Keynote Speakers

Keynote Speaker I

Prof. David Zhang
Hong Kong Polytechnic University, Hong Kong

David Zhang graduated in Computer Science from Peking University. He received his MSc in 1982 and his PhD in 1985 in both 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. Currently, he is a Chair Professor at the Hong Kong Polytechnic University where he is the Founding Director of Biometrics Research Centre (UGC/CRC) supported by the Hong Kong SAR Government in 1998. He also serves as Visiting Chair Professor in Tsinghua University and HIT, and Adjunct Professor in Shanghai Jiao Tong University, Peking University, National University of Defense Technology and the University of Waterloo. He is the Founder and Editor-in-Chief, International Journal of Image and Graphics (IJIG); Book Editor, Springer International Series on Biometrics (KISB); Organizer, the first 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 20 monographs, 400 international journal papers and 40 patents from USA/Japan/HK/China. He has been continuously listed as a Highly Cited Researchers in Engineering by Clarivate Analytics (formerly known as Thomson Reuters) in 2014, 2015, 2016 and 2017, respectively. Professor Zhang is a Croucher Senior Research Fellow, Distinguished Speaker of the IEEE Computer Society, and a Fellow of both IEEE and IAPR.


Speech Title:"Medical Biometrics"


Abstract: As one of the most powerful and reliable means of personal authentication, biometrics has been an area of particular interest. In this talk, we will explore how biometrics technology could be also applied to medical applications. By learning from the biometrics definition, medical biometrics could be implemented by measuring different human being’s surface information, extracting all possible features as their representations and making a correct final decision. As a case study, Traditional Chinese Medicine (TCM) diagnosis methods, including looking/smelling/touching/hearing sensing, are developed by using of medical biometrics. The experimental results have been illustrated the effectiveness of medical biometrics.


Keynote Speaker II

Prof. Kar-Ann Toh
Yonsei University, South Korea

Kar-Ann Toh is a Professor in the School of Electrical and Electronic Engineering at Yonsei University, South Korea. He received the PhD degree from Nanyang Technological University (NTU), Singapore. He worked for two years in the aerospace industry prior to his post-doctoral appointments at research centers in NTU from 1998 to 2002. He was affiliated with Institute for Infocomm Research in Singapore from 2002 to 2005 prior to his current appointment in Korea. His research interests include biometrics, machine learning, pattern classification, and neural networks. He is a co-inventor of two US patents and has made several PCT filings related to biometric applications. Besides being active in publications, Dr. Toh has served as an advisor/co-chair/member of technical program committee for international conferences related to biometrics and artificial intelligence. He has served as an Associate Editor of IEEE Transactions on Information Forensics and Security, Pattern Recognition Letters and IET Biometrics. He is a senior member of the IEEE.


Speech Title:"Multi-biometrics and Machine Learning"


Abstract: We shall begin this talk with a brief introduction to biometrics and multi-biometrics. Then several modes for fusing a multiple number of biometrics will be discussed. Since the method for fusion under these modes can be viewed as a classification problem, a brief overview of related literature in classifier design is subsequently provided. With these backgrounds in place, we shall introduce several learning methods where their learning objective functions fit the needs of biometrics and have a deterministic solution. Particularly the minimization of the classification counting error goal and the maximization of the receiver operating characteristic curve will be presented with deterministic solution. Finally, we shall walk through several experimental case studies before concluding the talk.


Keynote Speaker III

Prof. Yasushi Yagi
OSAKA University, Japan

Yasushi Yagi is the Executive Vice President of Osaka University in 2015. He received his Ph.D. degree from Osaka University in 1991. In 1985, he joined the Product Development Laboratory, Mitsubishi Electric Corporation, where he worked on robotics and inspections. He became a research associate at Osaka University in 1990, a lecturer in 1993, an associate professor in 1996, and a professor in 2003. He was the director of the Institute of Scientific and Industrial Research at Osaka University from 2012 to 2015. The studies in his laboratory focus on computer vision and media processing including basic technologies such as sensor design, and applications such as an intelligent system with visual processing functions. Some of our major research projects are: the development of a novel vision sensors such as an omnidirectional catadioptric system; biomedical image processing such as endoscope and microscope images; person authentication, intention, and emotion estimation from human gait, and its applications to forensic and medical fields; photometry analysis and its application to computer graphics; an anticrime system using a wearable camera; and 3D shape and human measurement using infrared light. He is a member of the Editorial Board of the International Journal of Computer Vision and the Vice-President of the Asian Federation of Computer Vision Societies. He is a fellow of IPSJ and a member of IEICE, RSJ, and IEEE.


Speech Title:"Gait Analysis for Person Authentication"


Abstract: We have been studying human gait analysis for more than 10 years. Because everyone's walking style is unique, human gait is a prime candidate for person authentication tasks. Our gait analysis technologies are now being used in real criminal investigations. We have constructed a large-scale gait database, and proposed several methods of gait analysis. The appearances of gait patterns are influenced by changes in viewpoint, walking direction, speed, clothes, and shoes. To overcome these problems, we have proposed several approaches using a part-based method, an appearance-based view transformation model, a periodic temporal super resolution method, a manifold-based method and score-level fusion. In this talk, I briefly introduce an overview of our gait analysis technologies and show the efficiency of our approaches by evaluating them with our large gait database.

Keynote Speaker IV


Assoc. Prof. KUO-YUAN HWA
National Taipei University of Technology, Taiwan


Dr. Kuo-Yuan Hwa is an associate professor and the director of the Center for Biomedical Industries at the National Taipei University of Technology. Dr. Hwagraduated and received her PhD from the School of Medicine, the Johns Hopkins University. She is the president of the Medical Association for Indigenous Peoples of Taiwan (MAIPT). Dr. Hwa’s scientific interests are: 1) nanotechnology and biosensor, 2) new drug discovery for human diseases by proteomics and genomics approaches and 3) glycobiology, especially on enzymes kinetics. She has published 85 conference and journal articles and 10 patents. She has served in many national and international committees. Dr. Hwa has been invited as a speaker for many academic research institutes and universities in China, Korea, Japan and USA. She has been invited as a reviewer, a judge and an editor for international meetings and journals. In addition, one of her currently works is on developing culturally inclusive health science educational program, with both indigenous and western science knowledge for indigenous children. 


 Speech Title:"Anti-Cancer Drug Discovery in the Era Precision Medicine- from Compounds to SNPs"


Abstract: According to the World Health Organization, cancer is the second leading cause of death globally. Globally, nearly 1 in 6 deaths is due to cancer, about 8.8 million deaths in 2015. Cancer is a group of diseases which begin with abnormal and uncontrollable cell division and growth. Neoplastic cells can convert into malignant tumors. Although many anticancer drugs have been developed over the past 50 years such as 5-Fluorouracil, there are still limitation. It is because when chemotherapy is carried out, normal cells in the body are also killed, that results many adverse effects. To develop more effective anticancer treatments i.e. targeted-based drugs is needed. Moreover, the majority of the first-in-class drugs approved by the FDA between 2009 to 2013 have been discovered through target-based approaches. We have previously isolated a series of anti-cancer compounds with defined mechanisms of actions via a comparative genomics approach. To further develop these compounds, here we have taken in silico approaches to find the specific SNPs in association with the efficacy of compounds by developing an analysis workflow. The identified SNPs can be further developed as complimentary screening tools for designing pre-clinical and clinical studies. The SNPs found in this studies can be used to recruit the correct patients for the drug development that would accelerate the drug discovery in the era of precision medicine.


Plenary Speaker I


Assoc. Prof. Andrew Teoh

College of Engineering, Yonsei University, South Korea


Andrew Beng Jin Teoh obtained his BEng (Electronic) in 1999 and Ph.D degree in 2003 from National University of Malaysia. He is currently an associate professor in Electrical and Electronic Engineering Department, College Engineering of Yonsei University, South Korea.

His research, for which he has received funding, focuses on biometric applications and biometric security. His current research interests are Machine Learning and Information Security. He has published more than 250 international refereed journal papers, conference articles, edited several book chapters and edited book volumes. He served and is serving as a guest editor of IEEE Signal Processing Magazine, TPC member of Information Forensic and Security in IEEE Signal Processing Society, associate editor of IEEE Biometrics Compendium and editor-in-chief of IEEE Biometrics Council Newsletter. He was a program co-chair of ICONIP 2014, area chair of ICPR 2016 and ICIP 2017, track chair and TPC for several conferences related to computer vision, pattern recognition and biometrics.


Speech Title:"Cancelable Biometrics for Template Protection: Recent Advancements and Challenges"


Abstract: Although biometrics is a powerful means against repudiation and has been widely deployed in various security systems, the biometric characteristics are largely immutable, resulting in permanent biometric compromise. Cancellable biometrics was proposed by storing a transformed version of the biometric template and provides higher privacy level by allowing multiple templates to be associated with the same biometric data. This helps to promote non-linkability of user’s data stored across various databases and revocation can be done when template is compromised. This talk will present the advancement and the challenges of cancellable biometrics.