Speakers and Panelists

Hatice Gunes is a Professor of Affective Intelligence and Robotics (AFAR) and the Director of the AFAR Lab at the University of Cambridge. Her expertise is in the areas of affective computing and social signal processing cross-fertilizing research in multimodal interaction, computer vision, machine learning and human-robot interaction. She has published over 150 papers in these areas (h-index=36, citations >7,100), with most recent works on lifelong learning for affect recognition, fairness and affective robotics; and longitudinal HRI for wellbeing. Her recent research highlights include, Guest Editor of the 2022 Frontiers Research Topic on Lifelong Learning and Long-Term Human-Robot Interaction and the 2021 IEEE Trans. Affect. Comput. Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data, RSJ/KROS Distinguished Interdisciplinary Research Award Finalist at IEEE RO-MAN'21, Distinguished PC Award at IJCAI'21, Best Paper Award Finalist at IEEE RO-MAN'20, Finalist for the 2018 Frontiers Spotlight Award, Outstanding Paper Award at IEEE FG'11, and Best Demo Award at IEEE ACII'09. Prof Gunes is the former President of the Association for the Advancement of Affective Computing (AAAC), and is the General Co-Chair of ACM ICMI'24 and ACII'19, and the Program Co-Chair of ACM/IEEE HRI'20 and IEEE FG'17. She was a member of the Human-Robot Interaction Steering Committee (2018-2021) and was the Chair of the Steering Board of IEEE Transactions on Affective Computing (2017-2019). In 2019 she was awarded the prestigious EPSRC Fellowship as a personal grant (2019-2024) to investigate adaptive robotic emotional intelligence for wellbeing, and was named a Faculty Fellow of the Alan Turing Institute– UK’s national centre for data science and artificial intelligence (2019-2021). Prof Gunes is a Senior Member of the IEEE, a member of the AAAC and a Staff Fellow of Trinity Hall.

Marynel Vázquez is an Assistant Professor in Yale’s Computer Science Department, where she leads the Yale Interactive Machines Group (IMG). Her main area of research is Human-Robot Interaction (HRI). She studies fundamental problems to enable group human-robot interactions. For instance, her work investigates social group phenomena in HRI, including spatial patterns of behavior typical of group conversations and group social influence. Further, she works on advancing autonomous, social robot behavior, both in terms of perception and decision making. An example is her work on learning social navigation policies, which has led them to create interactive online surveys to scale data collection in HRI. A key idea that has driven our recent work in group HRI is abstracting interactions as graphs. This allows robots to reason about individual, relationship and group factors in unison (e.g., see our work on group detection and pose generation). She also enjoys building robotic systems to demonstrate ideas in practice (Chester, Shutter).