Keynote Talks


John Chuang

Professor John Chuang

Title: I Think, Therefore I Am -- Authenticating with Passthoughts

Abstract: Interest in user authentication using neural signals has been fueled by recent progress in consumer brain-computer interface (BCI) technologies. In particular, the passthought paradigm supports one-step multi-factor authentication, offering security and usability benefits over other knowledge or biometric-based schemes. At the same time, significant technical and usability challenges remain in bringing brainwave authentication to daily use. I will share our research journey involving iterations of design, prototyping, experimental validation, and user studies, and reflect on potential shifts in our attitudes toward identity and authentication in an era of ubiquitous biosensors.

Bio: Dr. John Chuang is a Professor at the UC Berkeley School of Information, and Director of the BioSENSE Lab, with research interests in bio-sensory computing applications, security, and privacy. His recent and ongoing projects include: passthoughts authentication, brain-computer interfaces using in-ear electroencephalography, privacy and research ethics of remote biosensing platforms, and interrogating user beliefs and attitudes on ubiquitous sensing technologies. He received his Ph.D. in Engineering and Public Policy from Carnegie Mellon University, M.S. in Electrical Engineering from Stanford University, and graduated summa cum laude in Electrical Engineering from the University of Southern California.




Mohan_Kankanhalli

Professor Mohan Kankanhalli

Title: Social Interactions and Presentation Analytics

Abstract: Social interactions play an important role in our daily lives: people organize themselves in groups to share views, opinions, as well as thoughts. In many settings, observing these interactions offer deep insights into on-going events and situations. Manual analysis of such interactions is accurate but is tedious. Recent developments in sensors and processing enable the possibility for automated analysis of social interactions. This talk focuses on the analysis of social interactions from the social signal perspective in a multi-sensor setting. The talk starts with our work on extended F-formation system for robust interaction and interactant detection in an ambient sensor environment. Building upon this work, we study the spatial structure of social interactions in a multiple wearable sensor environment. We use a search-based method to reconstruct the social interaction structure given multiple first-person views, where each view contributes to the multi-faceted understanding of the social interaction. The talk ends with our work on "presentation analytics" which is a very important sub-class of social interactions. A new multi-sensor analytics framework is proposed using ambient and wearable sensors for a substantially improved sensing which allows for presentation self-quantification. We have used some deep learning techniques for the analysis. Feedback from presenters shows a lot of potential for the use of such analytics.

Bio: Mohan Kankanhalli is Provost's Chair Professor of Computer Science at the National University of Singapore (NUS). He is also the Dean of NUS School of Computing. Before becoming the Dean in July 2016, he was the NUS Vice Provost (Graduate Education) during 2014-2016 and Associate Provost during 2011-2013. Mohan obtained his BTech from IIT Kharagpur and MS & PhD from the Rensselaer Polytechnic Institute. His current research interests are in Multimedia Computing, Information Security & Privacy, Image/Video Processing and Social Media Analysis. He directs the SeSaMe (Sensor-enhanced Social Media) Centre which does fundamental exploration of social cyber-physical systems which has applications in social sensing, sensor analytics and smart systems. He is on the editorial boards of several journals including the ACM Transactions on Multimedia, Springer Multimedia Systems Journal, Pattern Recognition Journal and Springer Multimedia Tools & Applications Journal. He is a Fellow of IEEE.