Keynote Speakers


Keynote Speaker I


Prof. Seiichi Ozawa
Center for Mathematical and Data Sciences,
Kobe University, Japan

Seiichi Ozawa received the B.E. and M.E. degrees in instrumentation engineering from Kobe University in 1987 and 1989, respectively. In 1998, he received his Dr. Eng. in computer science from Kobe University. He is currently the deputy director of Center for Mathematical and Data Sciences and a full professor with the Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kobe University, Japan. He was a visiting researcher at Arizona State University in 2005. His current research interests are neural networks, machine learning, online learning, pattern recognition, big data analytics especially in cybersecurity, SNS and smart agriculture. He published 141 journal and refereed conference papers, and 9 book chapters/monographs. He is currently an associate editor of IEEE Trans. on Cybernetics, Evolving Systems Journal, Pattern Analysis and Applications Journal, and he was an associated IEEE Trans. on Neural Networks and Learning Systems for 6 years. Currently, he is a Pro Tempore Vice-President for Public Relations of International Neural Network Society (INNS), a vice-president for finance of Asia Pacific Neural Network Society (APNNS), and a special board of governor of Japan Neural Network Society (JNNS). He is a member of Neural Networks TC, Data Mining and Big Data Analytics TC, and Smart World TC of IEEE CI Society. He is serving as a general chair of INNS Conference on Big Data and Deep Learning 2018, Program Committee Chair of International Conference on Neural Information Processing 2018, Workshop Chair of 2018 IEEE Smart World Congress, and Program Committee Members of IJCNN 2018, INNS 2018, EAIS 2018, etc.


Keynote Speaker II


Prof. Kenji Suzuki
Tokyo Institute of Technology, Japan

Kenji Suzuki, Ph.D. (by Published Work; Nagoya University) worked at Hitachi Medical Corp., Japan, Aichi Prefectural University, Japan, as a faculty member, and in Department of Radiology, University of Chicago, as Assistant Professor. In 2014, he joined Department of Electric and Computer Engineering and Medical Imaging Research Center, Illinois Institute of Technology, as Associate Professor (Tenured). In 2017, he was jointly appointed in World Research Hub Initiative (WRHI), Institute of Innovative Research (IIR), Tokyo Institute of Technology, Japan, as Specially Appointed Professor (equivalent to Visiting Professor). He published 330 papers, including 110 peer-reviewed papers in leading journals such as IEEE TPAMI (Impact Factor: 17.7), IEEE TIP (IF: 6.8), IEEE TSP (IF: 5.2), and IEEE TMI (IF: 6.1). He has been actively studying deep learning in medical imaging and computer-aided diagnosis in the past 25 years, especially his early deep learning model was proposed in 1994, deep learning for image processing in 2004, receptive fields in 2004, semantic segmentation in 2004, U-net model in 2006, end-to-end deep learning in 2009, and deep learning reconstruction in 2010. His papers were cited more than 13,000 times, and his h-index is 48. He is inventor on 30 patents (including ones of earliest deep-learning patents), which were licensed to several companies and commercialized via FDA approvals. He published 11 books and 22 book chapters, and edited 13 journal special issues. He was awarded a number of grants as PI including NIH R01, ACS, JST, and NEDO grants. He served as the Editor-in-Chief/Associate Editor or Guest Editor of a number of leading international journals, including Pattern Recognition (IF: 5.9) and Neurocomputing (IF: 4.0). He served as a referee for 114 international journals such as Science Translational Medicine (IF: 17.1) and Nature Communications (IF: 11.9), an organizer of 93 international conferences, and a program committee member of 98 international conferences. He gave 120 invited talks and keynote speeches at international conferences. He received 26 awards, including Springer-Nature EANM Most Cited Journal Paper Award 2016 and 2017 Albert Nelson Marquis Lifetime Achievement Award. His research was covered in 49 articles in newspapers, magazines and journals by press and media, including Lancet Respiratory Medicine (IF: 23.0).

 

Keynote Speaker III


Prof. Yan Li
University of Southern Queensland, Australia

Prof Yan Li received her PhD degree from the Flinders University of South Australia, Australia. She is currently a Professor in the School of Agricultural, Computational and Environmental Sciences at the University of Southern Queensland (USQ), Australia. Her research interests lie in the areas of Artificial Intelligence, Machine Learning, Big Data Technologies, Internet Technologies, and Signal/Image Processing etc. Prof Yan Li has published more than 170 publications, supervised dozens of PhD completions, and obtained more than 2 million research grants through international collaborations. Prof Yan Li is the leader of USQ Data Science Programs and the recipient of many research and teaching excellence awards, including 2012 Australia prestigious National Learning and Teaching Citation Award, 2008 Queensland Government Smart State-Smart Women Award, 2009 USQ Teaching Excellence Award, 2009 USQ Research Excellence Award, and 2015-2017 Research Publication Excellence Awards.  Prof Yan Li has served as an elected academic leader in many high-level university committees, such as USQ Academic Board Executive Committee and USQ Research Committee etc.

 

 

 

 

 

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