Nikola Banovic is an Assistant Professor of Computer Science and Engineering at the University of Michigan, Ann Arbor. His research broadly focuses on Computational Interaction, Explainable AI, and Responsible AI. Having realized that complex computational models of human behavior that are at the core of Computational Interaction research are rarely (if ever) inherently explainable to and interpretable by a broader audience of relevant stakeholders (e.g., domain experts, policy makers, consumers), Nikola has taken a keen interest in developing methods to explain the decisions of such models (and other forms of AI) to end-users who are not computer science-savvy. In particular, Nikola's research focuses on using explanations to raise end-user AI literacy, which in turn could help them detect and counter untrustworthy AI. Before joining the University of Michigan, Nikola received his Ph.D. degree from the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University, and his B.Sc. and M.Sc. degrees from the University of Toronto. Nikola has published his award-winning research in premier Human-Computer Interaction (HCI) journals and conferences.

Anca Dragan is an Associate Professor in the EECS Department at UC Berkeley. Her goal is to enable robots to work with, around, and in support of people. She runs the InterACT Lab, where she focuses on algorithms for human-robot interaction -- algorithms that move beyond the robot's function in isolation, and generate robot behavior that coordinates well with people, and is aligned with what we actually want the robot to do. She works across different applications, from assistive arms, to quadrotors, to autonomous cars, and draws from optimal control, game theory, reinforcement learning, Bayesian inference, and cognitive science. She also helped found and serves on the steering committee for the Berkeley AI Research (BAIR) Lab, and is a co-PI of the Center for Human-Compatible AI. She has been honored by the Sloan Fellowship, MIT TR35, the Okawa award, an NSF CAREER award, and the PECASE award.

James Landay is a Professor of Computer Science and the Anand Rajaraman and Venky Harinarayan Professor in the School of Engineering at Stanford University. He co-founded and is Vice Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). Landay previously was a tenured faculty member at Cornell Tech, the University of Washington, and UC Berkeley. He was also Director of Intel Labs Seattle and co-founder of NetRaker. Landay received his BS in EECS from UC Berkeley, and MS and PhD in Computer Science from Carnegie Mellon University. He is a member of the ACM SIGCHI Academy and an ACM Fellow. He served on the NSF CISE Advisory Committee for six years.

Toby Jia-Jun Li is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame where he directs the SaNDwich Lab. Toby received a Ph.D. degree in Human-Computer Interaction at Carnegie Mellon University, where he was advised by Brad A. Myers. Toby also worked closely with Tom M. Mitchell. Toby works at the intersection of Human-Computer Interaction (HCI), End-User Software Engineering, Machine Learning (ML), and Natural Language Processing (NLP) applications, where he uses human-centered methods to design, build, and study interactive systems to empower individuals to create, configure, and extend AI-powered computing systems. His recent work seeks to address the societal challenges in the future of work through a bottom-up human-AI collaborative approach that helps individual workers automate and augment their tasks with AI systems. Toby publishes at premier academic venues across HCI, NLP, and systems (e.g., CHI, UIST, CSCW, ACL, MobiSys), including 4 award-winning papers. His work has been supported by NSF, the Google Research Scholar Program, the AnalytiXIN Initiative, Yahoo! through the InMind project, and J.P. Morgan.

Q. Vera Liao is a Principal Researcher at Microsoft Research Montréal, where she is part of the FATE (Fairness, Accountability, Transparency, and Ethics in AI) group. Her current research interests are in human-AI interaction, explainable AI, and responsible AI. Prior to joining MSR, she worked at IBM Research and studied at the University of Illinois at Urbana-Champaign and Tsinghua University. Her research received multiple paper awards at ACM and AAAI venues. She currently serves as the Co-Editor-in-Chief for Springer HCI Book Series, on the Editorial Board of ACM TiiS, an Editor for CSCW, and an Area Chair for FAccT.

Meredith Ringel Morris is a Principal Scientist in Google Deepmind. Prior to joining Google Deepmind, she served as Director of the People + AI Research team within Google Research's Responsible AI organization. Previously, she was a Sr. Principal Researcher at Microsoft Research, and Research Area Manager for Interaction, Accessibility, and Mixed Reality. She founded the Ability Research Group at MSR. She is an internationally-recognized leader in HCI, particularly in collaborative and social computing. Merrie is widely known as the founder of the field of collaborative web search; her SearchTogether system inspired numerous researchers in HCI and Information Retrieval to pursue work in this area. She subsequently co-developed a myriad of collaborative search prototypes and interaction techniques, aimed at supporting different search tasks, group configurations, and technologies. Her foundational studies of peoples’ collaborative searching habits and needs have informed the community’s understanding of search as a collaborative task. She was also the first to study the trend of friendsourced information seeking, wherein people use question-asking within social networks as an alternative to search engines; she contributed several articles describing and quantifying this phenomenon, as well as co-creating “socially embedded search engines,” an early type of chatbot that combined algorithmic search with friendsourcing. Additionally, Merrie is also widely known for her contributions to surface computing and gesture design: her dissertation introduced collaborative interaction techniques for the then-nascent field of surface computing, including cooperative gestures and identity-aware widgets, and her subsequent work as co-creator of the user-defined gesture-elicitation methodology has had broad impact in academia and industry, where it is frequently employed to design guessable gesture interfaces. She is also a leader in the field of accessibile technologies, particularly accessible social media, accessible communication technologies, the use of AI for accessibility applications, and AI equity for people with disabilities and older adults. Her current research at Google focuses on human-centered AI, including topics relating to human-AI interaction, AI ethics, and the societal impact of AI. 

Dr. Morris has served as the general chair for ACM’s CSCW conference and has previously served as Technical Program Chair of the CHI, CSCW, ASSETS, and ISS conferences. Dr. Morris is a past member of the TOCHI editorial board and of the CSCW and CHI steering committees. She has been recognized as one of Technology Review’s “35 under 35” for her work on collaborative web search and was named an ACM Fellow and elected to the SIGCHI Academy for her contributions to HCI research. She is the author of more than 100 peer-reviewed research articles, many of which have been recognized with best paper awards, as well as Lasting Impact Awards from the UIST and ISS conferences. She is also an inventor on more than 20 U.S. patents, and her HCI innovations have influenced many of Microsoft’s products and services. In addition to her role at Google, Dr. Morris is also an Affiliate Professor at the University of Washington in The Paul G. Allen School of Computer Science & Engineering and in The Information School. Dr. Morris earned her Sc.B. in computer science from Brown University, and her M.S. and Ph.D. in computer science from Stanford University

Chenhao Tan is an assistant professor of computer science and data science at the University of Chicago, and is also affiliated with the Harris School of Public Policy. He obtained his PhD degree in the Department of Computer Science at Cornell University and bachelor's degrees in computer science and in economics from Tsinghua University. Prior to joining the University of Chicago, he was an assistant professor at the University of Colorado Boulder and a postdoc at the University of Washington. His research interests include natural language processing, human-centered AI, and computational social science. His work has been covered by many news media outlets, such as the New York Times and the Washington Post. He also won a Sloan research fellowship, an NSF CAREER award, an NSF CRII award, a Google research scholar award, research awards from Amazon, IBM, JP Morgan, and Salesforce, a Facebook fellowship, and a Yahoo! Key Scientific Challenges award.