Invited Speakers
Seong-Whan Lee
  • Theme : Brain-Computer Interface: Recent Progress and Challenges in Neuro-Rehabilitation
Bio. Prof. Seong-Whan Lee is the Hyundai-Kia Motor Chair Professor at Korea University, where he is the head of the Department of Brain and Cognitive Engineering. He received the B.S. degree in computer science and statistics from Seoul National University, Seoul, Korea, in 1984, and the M.S. and Ph.D. degrees in computer science from Korea Advanced Institute of Science and Technology in 1986 and 1989, respectively. A Fellow of the IEEE, IAPR, and Korean Academy of Science and Technology, he has served several professional societies as chairman or governing board member. He was the founding Co-Editor-in-Chief of the International Journal of Document Analysis and Recognition and has been an Associate Editor of several international journals: Pattern Recognition, ACM Trans. on Applied Perception, IEEE Trans. on Affective Computing, Image and Vision Computing, International Journal of Pattern Recognition and Artificial Intelligence, and International Journal of Image and Graphics. His research interests include pattern recognition and brain engineering. He has more than 300 publications in international journals and conference proceedings, and authored 10 books.
Abstract This talk will introduce recent progress and challenges in neuro-rehabilitation for brain-computer interface (BCI) to enhance quality of life for both patients and aged person.
At first, we propose a novel method which can control a robot arm on multiple movement trajectories with the brain signals. To this end, we decoded motor commands on three dimensions from Electroencephalography (EEG) recordings while users either executed or observed/imagined complex upper limb movement trajectories. We then decoded the motor commands using a powerful non-linear method based on the Kernel Ridge Regression (KRR). We expect that patients who suffered muscular paralysis can easily control their arms with short training time. In addition, we also developed a brain-controlled wheelchair system. We classified three concentration tasks of user using spatial-frequency features of Steady-State Somatosensory Evoked Potentials (SSSEP) for control of the wheelchair. The user concentrates on one of vibration stimuli on fingers of left or right hands, or a toe; these tasks were associated with three wheelchair control commands: turn-left, turn-right, and move-forward, respectively. Experiment results show that the spatial-frequency features can increase the classification accuracy for the three concentration tasks.
We developed a lower-limb exoskeleton control system based on Steady-State Visual Evoked Potentials (SSVEP). In spite of the unfavorable artifacts induced in EEG signals under ambulatory environment, we proposed a convolutional neural network (CNN)-based signal processing algorithm that can decode user’s intentions robustly. Furthermore, we also developed a BCI-based motor rehabilitation system that classifies various gait movements containing leg movements at different walking speeds. To this end, we recorded EEG signals from subjects during continuous walking with a lower limb exoskeleton at two different speeds. The results presented the validity of system by correctly classifying gait movements at different speeds.
Sun Kim
  • Theme : Modeling and Mining Phenotype-Specific Biological Mechanisms Using Big Molecular Biology Data
Bio. Sun Kim is Professor in the School of Computer Science and Engineering, Director of Bioinformatics Institute, and an affiliated faculty for the Interdisciplinary Program in Bioinformatics at Seoul National University. Before joining SNU, he was Chair of Faculty Division C; Director of Center for Bioinformatics Research, an Associate Professor in School of Informatics and Computing; and an Adjunct Associate Professor of Cellular and Integrative Physiology, Medical Sciences Program at Indiana University (IU) Bloomington. Prior to joining IU in 2001, he worked at DuPont Central Research from 1998 to 2001, and at the University of Illinois at Urbana-Champaign from 1997 to 1998. Sun Kim received B.S and M.S and Ph.D in Computer Science from Seoul National University, KAIST and the University of Iowa, respectively.
Sun Kim is a recipient of Outstanding Junior Faculty Award at Indiana University 2004, US NSF CAREER Award from 2003 to 2008, and Achievement Award at DuPont Central Research in 2000. He is actively contributing to the bioinformatics community, serving on the editorial board for journals including editors for the METHODS journal and International Journal of Data Mining and Bioinformatics, serving as a board of directors member for ACM SIG Bioinformatics, as vice chair for education for the IEEE Computer Society Technical Committee on Bioinformatics. He has been co-organizing many scientific meetings including ACM BCB 2011 as a program co-chair, IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2008 as a program co-chair and 2009 as a conference co-chair.
Abstract Omics data, genome-wide measurement of biological events, is valuable for research in medical and biological sciences since it provides a “complete” picture of genetic and epigenetic events in the whole cell. Together with biological knowledge that accumulated over 100 years, we now have unprecedented opportunities to revolutionize medical and biological sciences. However, the amount of data is huge and mining bio big data is challenging. Modeling biological mechanisms is to explore new territories that no disciplines have tried. Data mining is at the heart of this transition since biology is now being transformed to data driven sciences that mine testable hypothesis from data. My talk is to try to convince why data scientists should participate in bio and medical research by introducing several projects: cancer, xenotransplanation, rice, and soybean projects.
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