Title:Multimodal Analysis of Human Behavior
Abstract: Computational analysis of human behavior is an active multidisciplinary area of research. While previous studies mostly rely on facial responses, more recent approaches exploit information from several modalities, such as voice, speech content (transcriptions), and facial expressions, for more reliable modeling and analysis of behavioral patterns. In this talk, I will discuss deep architectures to model such patterns for various tasks, from assessing psychopathology to detection of deceit.
Bio: Hamdi Dibeklioglu is an Assistant Professor in the Computer Engineering Department of Bilkent University as well as being a Research Affiliate with the Pattern Recognition & Bioinformatics Group of Delft University of Technology. He received the Ph.D. degree from the University of Amsterdam in 2014. Before joining Bilkent University, he was a Postdoctoral Researcher at Delft University of Technology, a Visiting Researcher at Carnegie Mellon University, University of Pittsburgh, and Massachusetts Institute of Technology. His research focuses on Affective Computing, Computer Vision, and Machine Learning. Dr. Dibeklioglu is a member of Program and Organizing Committees for several top tier conferences in these areas, and serves as an Associate Editor for IEEE Transactions on Affective Computing. Earlier, he served as a Guest Editor for Springer Journal on Multimodal User Interfaces (2020), and Frontiers in Computer Science (2021-2022). He has received the Outstanding Young Scientist Award of Turkish Academy of Sciences in 2022, the Young Scientist Award of the Science Academy Society of Turkey in 2023, and the Research Incentive Award of the METU Mustafa Parlar Foundation in 2023.