KEYNOTE SPEAKERS

Prof. Chee Peng Lim
Deakin University, Australia

Lim Chee Peng completed his Ph.D. degree at the Department of Automatic Control and Systems Engineering, University of Sheffield, UK, in 1997. His research focuses on the design and development of computational intelligence-based systems for data analytics and decision support, with application to medical prognosis and diagnosis, fault detection and classification, and manufacturing process optimisation. He has published over 450 technical articles in journals, conference proceedings, and books, and received 8 best paper awards in international conferences. He has also received many prestigious fellowships for international research collaboration, viz., Australia-India Senior Visiting Fellowship (by Australian Academy of Science), Australia-Japan Emerging Research Leaders Exchange Program (by Australian Academy of Technology and Engineering), Commonwealth Fellowship (at University of Cambridge), Fulbright Fellowship (at University of California, Berkeley), and Visiting Scientists Program of Office of Naval Research Global, USA (at Harvard University and Stanford University). In collaboration with co-workers, he has developed innovative software systems that have won various awards, which include Gold Medal at Pittsburgh Invention and New Product Exposition, USA, Gold Medal and Special Award at British Innovation Show, UK, Gold Medal at Geneva International Exhibition of Inventions, Switzerland, and Silver Prize at Open Source Software World Challenge, South Korea.

Speech Title: "Artificial Intelligence (AI)-based Systems for Biomedical Data Analytics and Decision Support"

Abstract: AI-based systems exhibit several key characteristics of human intelligence, e.g. learning, adaptability, reasoning, and decision making. In this talk, two aspects of designing and developing AI-based systems for data analytics and decision support applications are elucidated, viz., how to engineer computerised intelligent systems with an autonomous learning capability and how to reveal knowledge acquired by the intelligent systems for human reasoning and decision making. Specifically, single and hybrid data-based learning algorithms, which include neural, fuzzy, and evolutionary computational paradigms, are exploited. The importance of incremental learning without suffering from the catastrophic forgetting problem in perpetual data-based learning environments is highlighted. In addition, a human-in-the-loop framework that allows users to interact with the developed AI-based systems is formulated. This framework is crucial for users to understand the predictions yielded by the AI-based systems and, at the same time, to incorporate human knowledge, experience, and preference into the underlying learning algorithms during the operation stage. Application of the resulting AI-based systems to a range of image processing, pattern recognition, and decision support problems in biomedical and healthcare application domains will be demonstrated.

Prof. M. Iqbal Saripan
Universiti Putra Malaysia, Malaysia

M. Iqbal Saripan is a professor in the area of digital image processing from Universiti Putra Malaysia. He completed his PhD from the University of Surrey, United Kingdom in 2006. He is currently the Deputy Vice Chancellor (Academics and Internatonal), Universiti Putra Malaysia since February 2017. He was the recipient of Top Research Scientist Malaysia (TRSM), 2013 National Young Scientist Award and 2012 The Young Outstanding Malaysian Award (TOYM). Recently in 2016, he has received an alumnus of the year for University of Surrey. He was listed as Top Ten Creative Young Malaysian by Top Ten Magazine in 2015. In January 2013, Elsevier awarded him as the Most Valued Reviewer for Radiation Physics and Chemistry Journal. Other selected awards in his list are; the Travel Bursary Award ISRP Melbourne (International Radiation Physics Society), twice the Best Paper Award in San Francisco and London, GOLD medal in Geneva, GOLD medal in PECIPTA, SILVER in MTE, UPM Excellent Young Researcher Award and UPM Excellent Consultant Award. Iqbal is currently a Chartered Engineer with Engineering Council UK since 2015. He is active in his learned societies in his area. Currently, he is the Vice Chairman of International Radiation Physics Society (IRPS) which members are the prominent figures in the area of radiation physics. Apart from that, he has also served Institute of Electrical and Electronics Engineers (IEEE) at various positions – chairman, vice chairman and executive committee members over the years. At national level, he is currently a treasurer of Young Scientist Network (YSN). His research area focusses on medical image processing, particularly in nuclear medical imaging of cells activities detection, which includes cancer and Alzheimer. He has published more than 100 journal papers in flagship & impact journal journals, such as IEEE Transactions on Nuclear Science, IEEE Transactions on Biomedical Engineering, Nuclear Instruments and Methods, and Radiation Physics and Chemistry. His total number of publications exceeds 250 papers. His research has been funded by more than RM10million from various national and international sources.

Speech Title: "Imaging the Unseen"

Abstract: Imaging and picturing have become the norm of our daily lives. With the advancement of image processing technology, the boundary of what image processing can do, is further extended. There are a lot of applications for image processing now. One of the most important areas is in medical field. Image has started to be used previously in a simple medical observation, e.g. fracture detection and infection. As time passes by, more information can be extracted from the image. Often times, the captured images were internal structures that hidden inside the body. It requires a modern imaging technology to image the internal structure more accurately. Despite the more sophisticated imaging devices, the same old problem haunted the output images, i.e. noise. This talk will focus on the aspect of noise reduction, so that the details in the images can be preserved. Noise for nuclear imaging apparatus such as gamma camera, single photon emission tomography (SPECT) and position emission tomography (PET), can influence the overall quality of the image. Hence, noise need to be handle with care, especially when it comes to become the decision factor.

Prof. Ming Chen
Zhejiang University, China

Ming Chen received his PhD in Bioinformatics from Bielefeld University, Germany, in 2004. Currently he is working as a full Professor in Bioinformatics at College of Life Sciences, Zhejiang University. His group research work mainly focuses on the systems biology, computational and functional analysis of non-coding RNAs, and bioinformatics research and application for life sciences. Prof. Chen is serving as an academic leader in Bioinformatics at Zhejiang University. He chairs the Bioinformatics society of Zhejiang Province, China. He is a committee member of Chinese societies for "Modeling and Simulation of Biological Systems", "Computational Systems Biology", "Functional Genomics & Systems Biology" and "Biomedical Information Technology".

Speech Title: "Bioinformatics Approaches for Sing Cell Omics Data Analysis"

Abstract: With the rapid development of information technology and biological technology, multi-omics data is available, which brings us a challenge to develop appropriate bioinformatics approaches to model complex biological systems at spatial and temporal scales. We were motivated to characterize coding and non-coding RNAs including microRNAs, siRNAs, lncRNAs, ceRNAs and cirRNAs. An integrative interactome model of non-coding RNAs is built. Moreover, single-cell RNA sequencing makes it possible for bioinformatics to reveal expression patterns at the cellular level. We introduced a transcriptome-based single-cell atlas, and a web-based pipeline that accurately defines cell types based on single-cell digital expression. Additionally, we mined key factors of lncRNA regulating renal tumor metastasis based on single-cell RNA-seq data.