Masashi Sugiyama received the PhD degree in Computer Science from Tokyo Institute of Technology, Japan, in 2001. After experiencing assistant and associate professors at the same institute, he became a professor at the University of Tokyo in 2014. Since 2016, he has concurrently served as Director of RIKEN Center for Advanced Intelligence Project, leading the groups of fundamental AI technologies, AI applications, and social issues of AI. He (co)-authored machine learning monographs including Machine Learning in Non-Stationary Environments (MIT Press, 2012), Density Ratio Estimation in Machine Learning (Cambridge University Press, 2012), Statistical Reinforcement Learning (Chapman and Hall, 2015), Introduction to Statistical Machine Learning (Morgan Kaufmann, 2015), Variational Bayesian Learning Theory (Cambridge University Press, 2019), and Machine Learning from Weak Supervision (MIT Press, 2022).

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Sven Dickinson received the B.A.Sc. degree in Systems Design Engineering from the University of Waterloo, in 1983, and the M.S. and Ph.D. degrees in Computer Science from the University of Maryland, in 1988 and 1991, respectively. He is currently Professor of the Department of Computer Science at the University of Toronto, where he has served as Chair (2010-2015), Acting Chair (2008-2009), and Vice Chair (2003-2006). Since July, 2018, he's also served as Vice President and inaugural Head of the Samsung Toronto AI Research Center, doubling as Chief Scientist for the first six months. From 1995-2000, he was Assistant Professor of Computer Science at Rutgers University, where he held a joint appointment in the Rutgers Center for Cognitive Science (RuCCS) and membership in the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS). From 1994-1995, he was a Research Assistant Professor in the Rutgers Center for Cognitive Science, and from 1991-1994, a Research Associate at the Artificial Intelligence Laboratory, University of Toronto. He has held affiliations with the MIT Media Laboratory (Visiting Scientist, 1992-1994), the University of Toronto (Visiting Assistant Professor, 1994-1997), the Computer Vision Laboratory of the Center for Automation Research at the University of Maryland (Assistant Research Scientist, 1993-1994, Visiting Assistant Professor, 1994-1997), and the University of California, Santa Barbara (Visiting Professor, 2010-2011, 2015-2016). Prior to his academic career, he worked in the computer vision industry, designing image processing systems for Grinnell Systems Inc., San Jose, CA, 1983-1984, and optical character recognition systems for DEST, Inc., Milpitas, CA, 1984-1985.

Dr. Dickinson's research interests revolve around the problem of shape perception in computer vision and, more recently, human vision. Much of his recent work focuses on perceptual grouping and its role in image segmentation and shape recovery. He's introduced numerous qualitative shape representations, and their basis in symmetry provides a focus for his perceptual grouping research. His interest in multiscale, parts-based shape representations, and their common abstraction as hierarchical graphs, has motivated his research in inexact graph indexing and matching -- key problems in object recognition, another broad focus of his research. His research has also explored many problems related to object recognition, including object tracking, vision-based navigation, content-based image retrieval, language-vision integration, and image/model abstraction.

In 1996, Dr. Dickinson received the NSF CAREER award for his work in generic object recognition, and in 2002, received the Government of Ontario Premiere's Research Excellence Award (PREA), also for his work in generic object recognition. In 2012, he received the Lifetime Research Achievement Award from the Canadian Image Processing and Pattern Recognition Society (CIPPRS). In an effort to bring together researchers from human and computer vision, he was co-chair of the 1997, 1999, 2004, and 2007 IEEE International Workshops on Generic Object Recognition (or Object Categorization), which culminated in the interdisciplinary volume, Object Categorization: Computer and Human Vision Perspectives, in 2009, and was co-chair of the 2008, 2009, 2010, and 2011 International Workshops on Shape Perception in Human and Computer Vision, which culminated in the interdisciplinary volume, Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective, in 2013. He was General Co-Chair of CVPR 2014 and WACV 2019, and currently serves, or has served, on the editorial boards of the journals: IEEE Transactions on Pattern Analysis and Machine Intelligence; International Journal of Computer Vision; Computer Vision and Image Understanding; Image and Vision Computing; Graphical Models; Pattern Recognition Letters; IET Computer Vision; Frontiers in Computer Science: Computer Vision; and the Journal of Electronic Imaging. From 2017-2021, he was Editor-in-Chief of the IEEE Transactions on Pattern Analysis and Machine Intelligence. He is also co-editor of the Synthesis Lectures on Computer Vision from Morgan & Claypool Publishers, since its inauguration in 2009. He is a Fellow of the International Association for Pattern Recognition (IAPR).

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Francesca Rossi is an IBM fellow and the IBM AI Ethics Global Leader.

She works at the T.J. Watson IBM Research Lab, New York.

Her research interests focus on artificial intelligence, specifically they include constraint reasoning, preferences, multi-agent systems, computational social choice, and collective decision making. She is also interested in ethical issues in the development and behaviour of AI systems, in particular for decision support systems for group decision making. She has published over 200 scientific articles in journals and conference proceedings, and as book chapters. She has co-authored a book and she has edited 17 volumes, between conference proceedings, collections of contributions, special issues of journals, and a handbook.

She is a fellow of both the worldwide association of AI (AAAI) and of the European one (EurAI).She has been president of IJCAI (International Joint Conference on AI), an executive councillor of AAAI, and the Editor in Chief of the Journal of AI Research. She is a member of the scientific advisory board of the Future of Life Institute (Cambridge, USA) and a deputy director of the Leverhulme Centre for the Future of Intelligence (Cambridge, UK). She is in the executive committee of the IEEE global initiative on ethical considerations on the development of autonomous and intelligent systems and she is a member of the board of directors of the Partnership on AI, where she represents IBM as one of the founding partners.

She has been a member of the European Commission High Level Expert Group on AI and the general chair of the AAAI 2020 conference. She is a member of the Responsible AI working group of the Global Partnership on AI and the industry representative in its Steering Committee. She will be the AAAI President in 2022-2024.

Michael Wooldridge is a Professor of Computer Science at the University of Oxford, and director for foundational AI at the Alan Turing Institute. He has been an AI researcher for more than 30 years, and has published more than 400 scientific articles on the subject, including nine books, three of which have been translated into a total of 7 languages. He is a Fellow of the Association for Computing Machinery (ACM), the Association for the Advancement of AI (AAAI), and the European Association for AI (EurAI). From 2014-16, he was President of the European Association for AI, and from 2015-17 he was President of the International Joint Conference on AI (IJCAI). In 2020 he received the Lovelace Medal from the British Computer Society, and in 2021 he received the Outstanding Educator Award from the Association for Advancement of AI. From January 2023 he will be co-editor-in-chief of Artificial Intelligence Journal.

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