Overview

Judith Donath is a writer, designer and artist whose work focuses on the co-evolution of technology and society. She has published numerous articles about social media, AI, ethics and anonymity, and is the author of The Social Machine: Designs for Living Online (MIT Press). As the former director of the MIT Media Lab's Sociable Media Group, she and her students designed innovative interfaces for on-line communities; their art projects examining the future of identity, privacy and mediated life have been exhibited in museums and galleries worldwide. Currently, she is a faculty fellow at Harvard's Berkman Klein Center and is writing a book about technology, trust and deception.

She received her doctoral and master's degrees in Media Arts and Sciences from MIT and her bachelor's degree in History from Yale University. 

Andrew Davison is Professor of Robot Vision and Director of the Dyson Robotics Laboratory at Imperial College London. His long-term research focus is on SLAM (Simultaneous Localisation and Mapping) and its evolution towards general `Spatial AI': computer vision algorithms which enable robots and other artificial devices to map, localise within and ultimately understand and interact with the 3D spaces around them. With his research group and collaborators he has consistently developed and demonstrated breakthrough systems, including MonoSLAM, KinectFusion, SLAM++ and CodeSLAM, and recent prizes include Best Paper at ECCV 2016 and Best Paper Honourable Mention at CVPR 2018. He has also had strong involvement in taking this technology into real applications, in particular through his work with Dyson on the design of the visual mapping system inside the Dyson 360 Eye robot vacuum cleaner and as co-founder of applied SLAM start-up SLAMcore. He was elected Fellow of the Royal Academy of Engineering in 2017.

Svetlana Lazebnik received a Ph.D. in Computer Science at University of Illinois in 2006. After serving as assistant professor at the University of North Carolina at Chapel Hill from 2007 to 2011, she returned as faculty to the University of Illinois, where she is currently Full Professor in the Department of Computer Science. Her notable awards include the NSF CAREER Award (2008), Microsoft Research Faculty Fellow (2009),  Sloan Research Fellow (2013), and IEEE Fellow (2021). Her CVPR 2006 paper on Spatial Pyramid Matching received the 2016 Longuet-Higgins Prize for a paper with significant impact on computer vision. She served as Program Chair for ECCV 2012 and ICCV 2019, and is currently serving as an Editor in Chief of the International Journal of Computer Vision. Her main research themes include scene understanding, modeling of large-scale photo collections, joint representations for images and text, and deep learning techniques for visual recognition problems.

Jitendra Malik was born in Mathura, India in 1960. He received the B.Tech degree in Electrical Engineering from Indian Institute of Technology, Kanpur in 1980 and the PhD degree in Computer Science from Stanford University in 1985. In January 1986, he joined the university of California at Berkeley, where he is currently the Arthur J. Chick Professor in the Department of Electrical Engineering and Computer Sciences. He is also on the faculty of the department of Bioengineering, and the Cognitive Science and Vision Science groups. During 2002-2004 he served as the Chair of the Computer Science Division, and as the Department Chair of EECS during 2004-2006 as well as 2016-2017. In 2018 and 2019, he served as Research Director and Site Lead of Facebook AI Research in Menlo Park.

Prof. Malik's research group has worked on many different topics in computer vision, computational modeling of human vision, computer graphics and the analysis of biological images. Several well-known concepts and algorithms arose in this research, such as anisotropic diffusion, normalized cuts, high dynamic range imaging, shape contexts and R-CNN. He has mentored more than 60 PhD students and postdoctoral fellows.

Aude Oliva, Ph.D. is the MIT director of the MIT–IBM Watson AI Lab and director of MIT Quest Corporate, MIT Schwarzman College of Computing, leading collaborations with industry to translate natural and artificial intelligence research into tools for the wider world. She is also a senior research scientist at the Computer Science and Artificial Intelligence Laboratory where she heads the Computational Perception and Cognition group. Her research is cross-disciplinary, spanning human perception and cognition, computer vision and cognitive neuroscience, and focuses on research questions at the intersection of all three domains.

Richard Szeliski is an Affiliate Professor at the University of Washington, a Member of the National Academy of Engineering, and a Fellow of the ACM and IEEE.  Dr. Szeliski has done pioneering research in the fields of Bayesian methods for computer vision, image-based modeling, image-based rendering, and computational photography, which lie at the intersection of computer vision and computer graphics.  His research on Photo Tourism, Photosynth, and Hyperlapse are exciting examples of the promise of large-scale image and video-based rendering.

Dr. Szeliski received his Ph.D. degree in Computer Science from Carnegie Mellon University in 1988.  He joined Facebook as the founding Director of the Computational Photography group in 2015 and retired in 2020.  Prior to Facebook, he worked at Microsoft Research for twenty years as well as several other industrial research labs.  He has published over 180 research papers in computer vision, computer graphics, neural networks, and numerical analysis, as well as the books Computer Vision: Algorithms and Applications and Bayesian Modeling of Uncertainty in Low-Level Vision.  He was a Program Chair for CVPR'2013 and ICCV'2003, served as an Associate Editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence and on the Editorial Board of the International Journal of Computer Vision, and was a Founding Editor of Foundations and Trends in Computer Graphics and Vision.

Tal Hassner received his M.Sc. and Ph.D. degrees in applied mathematics and computer science from the Weizmann Institute of Science, Israel, in 2002 and 2006, respectively. In 2008 he joined the Department of Math. and Computer Science at The Open Univ. of Israel where he was an Associate Professor until 2018. From 2015 to 2018, he was a senior computer scientist at the Information Sciences Institute (ISI) and a Visiting Associate Professor at the Institute for Robotics and Intelligent Systems, Viterbi School of Engineering, both at USC, CA, USA, working on the IARPA Janus face recognition project. From 2018 to 2019, Tal was a Principal Applied Scientist at AWS, where he led the design and development of the latest AWS face recognition pipelines. Since June 2019, he is an Applied Research Lead at Facebook AI, supporting both the text (OCR) and people (faces) photo understanding teams. Tal is an associate editor for both IEEE TPAMI and IEEE TBIOM. Some of his recent organizational roles include program chair for WACV'17, workshop chair for CVPR'20, and program chair for ICCV'21.

Hany Farid is a Professor at the University of California, Berkeley with a joint appointment in Electrical Engineering & Computer Sciences and the School of Information. His research focuses on digital forensics, forensic science, misinformation, image analysis, and human perception. He received his undergraduate degree in Computer Science and Applied Mathematics from the University of Rochester in 1989, his Ph.D. in Computer Science from the University of Pennsylvania in 1997. Following a two-year post-doctoral fellowship in Brain and Cognitive Sciences at MIT, he joined the faculty at Dartmouth College in 1999 where he remained until 2019. He is the recipient of an Alfred P. Sloan Fellowship, a John Simon Guggenheim Fellowship, and is a Fellow of the National Academy of Inventors.

Cristian Canton is the Research Manager at Facebook AI, focused on understanding weaknesses and vulnerabilities derived from the use (or misuse) of AI. He was the project lead for the Deepfake Detection Challenge (DFDC) and has co-chaired several workshops on media forensics. In the past, he managed the computer vision team within the objectionable and harmful content domain. From 2012-16, he was at Microsoft Research in Redmond (USA) and Cambridge (UK); from 2009-2012, he was at Vicon (Oxford), bringing CV to produce visual effects for the cinema industry. He got his PhD and MS from Technical University of Catalonia (Barcelona) and his MS Thesis from EPFL (Switzerland) on computer vision topics.

Sam Gregory is an award-winning technologist, media-maker, and advocate, and Program Director of WITNESS (www.witness.org) which helps people use video and technology to defend human rights. An expert on new forms of misinformation and disinformation as well as innovations in preserving trust, authenticity and evidence, he leads WITNESS’ work on global Technology Threats and Opportunities related to the nexus of broader use of AI and increasing audiovisual and immersive communication and trends in both smartphone witnessing and rising authoritarianism. In coordination with technical researchers, policy-makers, companies, media organizations, journalists and civic activists WITNESS's 'Prepare, Don't Panic' initiative builds better globally-inclusive preparedness for malicious usages of synthetic media (wit.to/Synthetic-Media-Deepfakes) including current work on deepfake detection equity, deepfake ethics and satire, and emerging standards in authenticity infrastructure. Quoted in major media worldwide, he publishes frequently on technology and human rights and has spoken at Davos and the White House. Sam is a former Young Global Leader of the World Economic Forum, is on the Technology Advisory Board of the International Criminal Court, co-chaired the Partnership on AI’s Expert Group on AI and the Media and previously taught 2010-2018 at the Harvard Kennedy School.

Mei Ngan is a scientist at the National Institute of Standards and Technology (NIST).  Her research focus includes evaluation of face recognition and tattoo recognition technologies.  She is currently involved in a number of key face recognition testing activities at NIST, including leading the Face Recognition Vendor Test (FRVT) MORPH project to evaluate face morphing detection algorithms.  Mei has authored and co-authored a number of technical publications, including the accuracy of face recognition with face masks, performance of facial age and gender estimation algorithms, and publication of a seminal open tattoo database for developing tattoo recognition research, which she received the Special Contribution Award for at the 2015 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA).  Mei was awarded the Department of Commerce Gold Medal Award in 2020 and was a recipient of the 2020 Women in Biometrics Award, a globally-recognized award honoring innovative women in the biometrics field.

Luisa Verdoliva is Associate Professor at University Federico II of Naples, Italy, where she leads the Multimedia Forensics Lab. In 2018 she has been visiting professor at Friedrich-Alexander-University (FAU) and in 2019-2020 she has been visiting scientist at Google AI in San Francisco. Her scientific interests are in the field of image and video processing, with main contributions in the area of multimedia forensics. She has published over 120 academic publications, including 45 journal papers. She is the PI for University Federico II of Naples in the DISCOVER (a Data-driven Integrated Approach for Semantic Inconsistencies Verification) project funded by DARPA under the SEMAFOR program (2020-2024). She has contributed to the academic community through service as technical Chair of the 2019 IEEE Workshop in Information Forensics and Security and the 2021 ACM Workshop on Information Hiding and Multimedia Security, area Chair of IEEE ICIP since 2017. She has been also co-Chair of the IEEE CVPR Media Forensics Workshop both in 2020 and 2021. She is on the Editorial Board of IEEE Transactions on Information Forensics and Security and IEEE Signal Processing Letters and has been Guest Editor for IEEE Journal of Selected Topics in Signal Processing. Dr. Verdoliva is Chair of the IEEE Information Forensics and Security Technical Committee and vice-Chair of the EURASIP Signal and Data Analytics for Machine Learning Special Area Teams. She is the recipient of the 2018 Google Faculty Award for Machine Perception and a TUM-IAS Hans Fischer Senior Fellowship (2020-2023). She has been elected to the grade of IEEE Fellow since January 2021.

John Konstantine Tsotsos received his Hons. BASc in Engineering Science, MSc in Computer Science and PhD in Computer Science all from the University of Toronto in 1974, 1976 and 1980 respectively. He then joined the University of Toronto on faculty in both Departments of Computer Science and of Medicine. There, he founded and led the computer vision group for almost 2 decades. He moved to York University in 2000 where he is Distinguished Research Professor of Vision Science, and maintains Adjunct Professorships at the University of Toronto in the Departments of Computer Science and in Ophthalmology and Vision Sciences. He directed York’s Centre for Vision Research from 2000-2006 and is the founding Director of York’s Centre for Innovation in Computing at Lassonde.

He has been in the ICCV family since the beginning, being part of the first group of Marr Prize winners in 1987, on several program committees and General Chair of ICCV 1999. He is best known for contributions to visual attention and active perception. He is currently focused on the role of visual attention and cognitive control in how active observers (human or artificial) solve complex 3D visuospatial tasks in real-world settings.

Awards include:  Fellow, Artificial Intelligence and Robotics Program of the Canadian Institute for Advanced Research (CIFAR);  Fellow of the Royal Society of Canada; Fellow IEEE; Canadian Image Processing and Pattern Recognition Society Award for Research Excellence and Service;  Geoffrey J. Burton Memorial Lectureship from the United Kingdom’s Applied Vision Association for significant contribution to vision science; the Royal Society of Canada’s 2015 Sir John William Dawson Medal for sustained excellence in multidisciplinary research, the first computer scientist so honored; and, the 2020 Lifetime Achievement Award from Canada's national computing society, CS-Can|Info-Can.

Sanja Fidler is an Associate Professor at the Department of Computer Science, University of Toronto. She joined UofT in 2014. In 2018, she took a role of Director of AI at NVIDIA, leading a research lab in Toronto. Previously she was a Research Assistant Professor at TTI-Chicago, a philanthropically endowed academic institute located in the campus of the University of Chicago. She completed her PhD in computer science at University of Ljubljana in 2010, and was a postdoctoral fellow at University of Toronto during 2011-2012. She received the NVIDIA Pioneer of AI award, Amazon Academic Research Award, Facebook Faculty Award, and the Connaught New Researcher Award. In 2018 she was appointed as the Canadian CIFAR AI Chair. Her work on semi-automatic object instance annotation won the Best Paper Honorable Mention at CVPR’17. Her main research interests are scene parsing from images and videos, interactive annotation, 3D scene understanding, 3D content creation, and multimodal representations.

David Forsyth is currently a full professor at U. Illinois at Urbana-Champaign, where he has occupied the occupied the Fulton-Watson-Copp chair in Computer Science since 2014. Prior to UIUC, he was a full professor at UC Berkeley. David has published over 130 papers on computer vision, computer graphics and machine learning. David has served as program co-chair for IEEE Computer Vision and Pattern Recognition in 2000, 2011, and 2018, general co-chair for CVPR 2006 and 2015, program co-chair for the European Conference on Computer Vision 2008, and is a regular member of the program committee of all major international conferences on computer vision.  David has served six years on the SIGGRAPH program committee, and is a regular reviewer for that conference. David has received best paper awards at the International Conference on Computer Vision and at the European Conference on Computer Vision. David received an IEEE technical achievement award for 2005 for his research. He became an IEEE Fellow in 2009, and an ACM Fellow in 2014. His recent textbook, “Computer Vision: A Modern Approach” (joint with J. Ponce and published by Prentice Hall) is now widely adopted as a course text (at such institutions as MIT, U. Wisconsin-Madison, UIUC, Georgia Tech and U.C. Berkeley.  David is currently serving a second term as Editor in Chief, IEEE TPAMI.

Georgia Gkioxari is a research scientist at Facebook AI Research. She received her PhD from UC Berkeley, where she was advised by Jitendra Malik. She did her bachelors in ECE at NTUA in Athens, Greece, where she worked with Petros Maragos. She is the recipient of the 2021 PAMI Young Researcher Award. She was named one of the "30 Influential Women Advancing AI in 2019: by Re-Work.