Hari Subramonyam is an Assistant Professor (Research) at the Graduate School of Education and a Faculty Fellow at the Institute for Human-Centered AI (HAI) at Stanford University. He is also a member of the HCI Group at Stanford. Hari's research focuses on augmenting critical human tasks (such as learning, creativity, and sensemaking) with AI by incorporating principles from cognitive psychology. He also investigates support tools for multidisciplinary teams to co-design human-centered AI experiences. Prior to joining Stanford, Hari received his Ph.D. in Information from the University of Michigan School of Information where he was advised by Dr. Eytan Adar. He also holds a M.S. from Michigan and B.E. from Visvesvaraya Technological University in India.
Subramonyam, H.,,Adar, E., Á Drucker, S. (2022, June). Composites: A Tangible Interaction Paradigm for Visual Data Analysis in Design Practice
[To Appear AVI'22]
Preprint
Subramonyam, H.,Im, J., Seifert, C., & Adar, E. (2022, February). Solving Separation-of-Concerns Problems in Collaborative Design of Human-AI Systems through Leaky Abstractions
[To Appear CHI'22]
Preprint
Cao, Y., Subramonyam, H., & Adar, E. (2022). VideoSticker: A Tool for Active Viewing and Visual Note-taking from Videos. [To Appear IUI'22]
Preprint
Madaio, M.,Egede, L., Subramonyam, H., & Wortman Vaughan, J., Wallach, H. (2022). Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support. [To Appear CSCW'22]
Preprint
Subramonyam, H., Seifert, C., & Adar, E. (2021, December). How Can Human-Centered Design Shape Data-Centric Data AI? HCAI@NeurIPS2021 workshop on Human Centered AI
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