ICBEA 2017          Full Paper Submission Deadline: 15th February 2017     Conference Dates: 21th - 23th April 2017      Conference Place: Hong Kong


 

CONFERENCE TO BE HELD IN

Hong Kong





 




KEYNOTE & PLENARY SPEAKER

 

Keynote Speaker I


Prof. David Zhang
The Hong Kong Polytechnic University, Hong Kong
 

Prof. 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. 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 journal papers and 35 patents from USA/Japan/HK/China. According to Google Scholar, his papers have got over 35,000 citations and H-index is 86. He was listed 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.

 

Keynote Speaker II


Prof. Yuan-Ting Zhang
 The Key Lab for Health Informatics of Chinese Academy of Sciences, China


Prof. Yuan-Ting Zhang is the Director of Joint Research Center for Biomedical Engineering, Founding Head of the Division of Biomedical Engineering, and Professor of Department of Electronic Engineering at the Chinese University of Hong Kong. Dr. Zhang serves concurrently the Director of the Key Lab for Health Informatics of the Chinese Academy of Sciences (HICAS). His research spans several fields including wearable medical devices, body sensor networks, bio-THz technologies, bio-modeling, neural engineering, cardiovascular health informatics, and e-p-m-Heath and telemedicine technologies, and is closely tied up to his teaching and publishing activities. He has authored/co-authored over 400 scientific publications and 11 book chapters, and filed 31 patents. His research work has won him a number of Awards including the best journal paper awards from IEEE-EMBS and the Asia Pacific ICTA e-Health Award. Dr. Zhang provided extensively professional services of significant value to the local industries and global academic communities. He served as Associate Editor of IEEE Transactions on Biomedical Engineering, founding Associate Editor of IEEE Transactions on Mobile Computing, Guest Editor for IEEE Transactions on Information Technology in Biomedicine, and Guest Editor for IEEE Communication Magazine. He was previously the Vice-President of the IEEE-EMBS. He served as the Technical Program Chair and the General Conference Chair of the 20th and 27th IEEE-EMBS Annual International Conferences in 1998 and 2005, respectively. He was a member of IEEE Fellow Elevation Committee and the Award Committee for IEEE Medal on Innovations in Healthcare Technology.

 

Speech Title: "Cardiovascular Health Informatics: Wearable MINDS"

Abstract: This talk will discuss the miniaturization, intelligence, network, digitization, and standardization (MINDS) design of wearable devices. The focus will be placed on its convergence with unobtrusive sensing and imaging for cardiovascular health informatics in general and for the prediction of acute cardiovascular diseases in particular. Using the atherosclerotic plaque assessment and wearable cuffless blood pressure estimation as application examples, this talk will attempt to illustrate that the health informatics approaches should allow the practice of 8-Ps health that is precise, pervasive, predictive, preventive, personalized, participatory, preemptive, and patient-centralized.

 

Keynote Speaker III


Assoc. Prof. GAUTAM SETHI
Department of Pharmacology, National University of Singapore, Singapore

EDUCATION/TRAINING
B. S. 1998 Banaras Hindu University, Varanasi, India Chemistry (Honours)
M. S. 2000 Banaras Hindu University, Varanasi, India Biochemistry
Ph.D 2004 Banaras Hindu University, Varanasi, India Biotechnology
PDF 2004-07 UTMDACC Houston, Texas, USA. Cancer biology.
Asst Prof. 2008-14 National University of Singapore Pharmacology
Associate Prof. 2014- Now National University of Singapore

POSITIONS AND EMPLOYMENT
Sept. 2000 to Aug. 2002 Junior Research Fellow, School of Biotechnology, Banaras Hindu University, Varanasi, India.
Sept. 2002 to March 2004 Senior Research Fellow, School of Biotechnology, Banaras Hindu University, Varanasi, India
2004-2007 Postdoctoral Fellow, The University of Texas MD Anderson Cancer Center.
2008-2014 Assistant Professor, Dept. of Pharmacology, NUS.
2014-Now  Associate Professor with tenure,  Dept. of Pharmacology, NUS.

 

Speech Title: "Targeting Transcription Factor STAT3 for Prostate Cancer Therapy"

Abstract: STATs comprise a family of cytoplasmic transcription factors that transmit signals, mediate intracellular signaling usually generated at cell surface receptors and transmitted to the nucleus. Numerous studies have demonstrated constitutive activation of STAT3 in a wide variety of human tumors, including blood malignancies (leukemias, lymphomas, and multiple myeloma) as well as solid tissues (such as head and neck, breast, lung, gastric, hepatocellular and prostate cancers). There is a strong evidence to suggest that aberrant STAT3 signaling promotes development and progression of prostate cancer by either inhibiting apoptosis or inducing cell proliferation, angiogenesis, invasion, and metastasis. However, the development of novel drugs for the targeting STAT3 that is both safe and efficacious remains an important scientific and clinical challenge. We will present the data that shows that novel small molecule inhibitors of STAT3/JAK2 pathway can suppress the expression of genes involved in prostate cancer initiation, and promotion both in vitro and in vivo.

 

Plenary Speaker I


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, the Editor-in-Chief of IPSJ Transactions on Computer Vision & Applications 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 Video Analysis for Criminal Investigation"

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. We show the efficiency of our approaches by evaluating them with our large gait database.

 

Plenary Speaker II


Prof. Raymond Veldhuis
University of Twente, The Netherlands

Raymond Veldhuis graduated from The University of Twente, The Netherlands in 1981. From 1982 until 1992 he worked as a researcher at Philips Research Laboratories in Eindhoven in various areas of digital signal processing. In 1988, he received the PhD degree from Nijmegen University on a thesis entitled Adaptive Restoration of Lost Samples in Discrete-Time Signals and Digital Images. From 1992 until 2001 he worked at the IPO (Institute of Perception Research) Eindhoven in the field of speech processing. Raymond Veldhuis is now a full professor in Biometric Pattern recognition at The University of Twente, where he is leading a research group in this field. The main research topics are face recognition (2D and 3D), fingerprint recognition, vascular pattern recognition, multibiometric fusion, and biometric template protection. The research is both applied and fundamental.

 

Speech Title: "Advances in Face-Recognition at a Distance"

Abstract: During the past decade, automatic facial recognition has become an established biometric recognition technology with applications in, for instance, mobile banking, automatic border control as well as in social media applications. Also in the field of forensic search automatic and semi-automatic face recognition is starting to play an increasingly significant role. However, in this field there are still some challenges due to variations of pose, illumination, and facial expressions as well occlusion, image quality and low resolution. In this presentation, I want to address the challenge of facial recognition for surveillance applications. The typical problem here is the comparison of a high-resolution reference image, for example a mugshot, with a low-resolution trace image taken at some distance, for example found on a surveillance video. I will demonstrate that realistic low-resolution images that are taken at a distance, are not equivalent to low-resolution images obtained by down-sampling higher-resolution images. This implies that in order to improve the recognition performance specific training of classifiers is required, but also that a proper evaluation on realistic low-resolution images is crucial. In the presentation, I will discuss the implications the on design, training and testing of face recognition systems for surveillance applications and propose a mixed-resolution classifier for this purpose. Attention will be paid to the deployment of convolutional neural net based facial recognition systems for mixed-resolutions.

 

 

 

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