Professor Maja Pantic (Imperial College London, Computing Dept., UK)
Title of the talk:
"Automatic Face Analysis"
"Human face is our preeminent means to identify the other members of our species and communicate affective and social signals. This talk summarises a number of aspects of human face and facial behavior and how they can be automatically sensed and analysed by computers. Past research in the field conducted by the iBUG group at Imperial College London and how far are we from enabling computers to detect, track and recognise human face and facial expressions is discussed in detail.
More info on the work of the iBUG group can be found at http://ibug.doc.ic.ac.uk/home. For databases and software solutions to various problems in the field of automatic facial expression analysis, see http://ibug.doc.ic.ac.uk/
Maja Pantic obtained her PhD degree in computer science in 2001 from Delft University of Technology, the Netherlands. Until 2005, she was an Assistant/ Associate Professor at Delft University of Technology.
In 2006, she joined the Imperial College London, Department of Computing, UK, where she is Professor of Affective & Behavioural Computing and the Head of the iBUG group, working on machine analysis of human non-verbal behaviour. From November 2006, she also holds an appointment as the Professor of Affective & Behavioural Computing at the University of Twente, the Netherlands.
Prof. Pantic is one of the world's leading experts in the research on machine understanding of human behavior including vision-based detection, tracking, and analysis of human behavioral cues like facial expressions and body gestures, and multimodal analysis of human behaviors like laughter, social signals, and affective states. In 2011, Prof. Pantic received BCS Roger Needham Award, awarded annually to a UK based researcher for a distinguished research contribution in computer science within ten years of their PhD. She is an IEEE Fellow.
See also: http://ibug.doc.ic.ac.uk/~
Prof Stephen Schueller (Northwestern University, USA)
"Reaching People Where They’re At: Improving Mental Health Through Technology"
We are in the midst of a revolution in mental health care that is harnessing the affordances of new technologies to create fundamentally new methods of identifying, preventing, and treating mental health problems. These technologies have demonstrated the potential to transcend space, time, culture, and language and thus have the capacity to overcome several barriers that have plagued access to mental health resources. But a majority of these resources still rely on self-identification and self-presentation, placing the burden of accessing care in a timely manner primarily on the people experiencing significant psychological distress. A substantial step forward involves embedding resources and intervention strategies in the technologies people interact with on a daily basis and in a way that reflects how they typically interact with those technologies. I will present illustrative examples drawing from research I have conducted in collaboration with clinical psychologists, computer scientists, engineers, and human-computer interaction experts including work using smartphones, sensors, and social networks as ways to recognize patterns that may be early indicators of mental disorders and support skills to overcome mental disorders. This works demonstrates the potential of mental health resources to become more pervasive and to empower technologies to support the mental health of the people interacting with them.
Prof. Schueller received his Ph.D. in Clinical Psychology from the University of Pennsylvania in 2011, and completed his clinical internship and postdoctoral fellowship at the University of California, San Francisco. He is currently an Assistant Professor of Preventive Medicine at Northwestern University and a member of Northwestern’s Center for Behavioral Intervention Technologies (CBITs; http://cbits.northwestern.edu/