Bio


Hari Subramonyam is an Assistant Professor (Research) at the Graduate School of Education and a Faculty Fellow at Stanford's Institute for Human-Centered AI. He is also a member of the HCI Group at Stanford. His 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 AI experiences. His work has received multiple best paper awards at top human-computer interaction conferences, including CHI and IUI.

Academic Appointments


Honors & Awards


  • Student Design Competition 3rd Place, CHI (05/2015)
  • Best Paper Award, CHI (05/2019)
  • Best Paper Award, CHI (04/2020)

Professional Education


  • Ph.D. Information, University of Michigan, Dissertation: Role of End-User Data in Co-Designing AI-Powered Applications (2021)
  • B.E. Telecommunication, CMR Institute of Technology (2008)
  • M.S. Information, University of Michigan, Human Computer Interaction (2015)

All Publications


  • texSketch: Active Diagramming through Pen-and-Ink Annotations Subramonyam, H., Seifert, C., Shah, P., Adar, E., ACM ASSOC COMPUTING MACHINERY. 2020
  • Explore, Create, Annotate: Designing Digital Drawing Tools with Visually Impaired People Pandey, M., Subramonyam, H., Sasia, B., Oney, S., O'Modhrain, S., ACM ASSOC COMPUTING MACHINERY. 2020
  • Affinity Lens Data-Assisted Affinity Diagramming with Augmented Reality Subramonyam, H., Drucker, S. M., Adar, E., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019
  • SmartCues: A Multitouch Query Approach for Details-on-Demand through Dynamically Computed Overlays IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS Subramonyam, H., Adar, E. 2019; 25 (1): 597-607

    Abstract

    Details-on-demand is a crucial feature in the visual information-seeking process but is often only implemented in highly constrained settings. The most common solution, hover queries (i.e., tooltips), are fast and expressive but are usually limited to single mark (e.g., a bar in a bar chart). 'Queries' to retrieve details for more complex sets of objects (e.g., comparisons between pairs of elements, averages across multiple items, trend lines, etc.) are difficult for end-users to invoke explicitly. Further, the output of these queries require complex annotations and overlays which need to be displayed and dismissed on demand to avoid clutter. In this work we introduce SmartCues, a library to support details-on-demand through dynamically computed overlays. For end-users, SmartCues provides multitouch interactions to construct complex queries for a variety of details. For designers, SmartCues offers an interaction library that can be used out-of-the-box, and can be extended for new charts and detail types. We demonstrate how SmartCues can be implemented across a wide array of visualization types and, through a lab study, show that end users can effectively use SmartCues.

    View details for DOI 10.1109/TVCG.2018.2865231

    View details for Web of Science ID 000452640000057

    View details for PubMedID 30136998

  • Designing Interactive Intelligent Systems for Human Learning, Creativity, and Sensemaking Subramonyam, H., ACM ASSOC COMPUTING MACHINERY. 2019: 158-161
  • TakeToons: Script-driven Performance Animation Subramonyam, H., Li, W., Adar, E., Dontcheva, M., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2018: 663-674
  • The application of ecological momentary assessment and geolocation to a longitudinal twin study of substance use Brazel, D., Corley, R., Phelan, C., Frieser, M., Subramonyam, H., Rhea, S., Vernier, H., Hewitt, J., Resnick, P., Vrieze, S. SPRINGER. 2017: 676-677
  • Agency in Assistive Technology Adoption: Visual Impairment and Smartphone Use in Bangalore Pal, J., Viswanathan, A., Chandra, P., Nazareth, A., Kameshwaran, V., Subramonyam, H., Johri, A., Ackerman, M. S., O'Modhrain, S., ACM ASSOC COMPUTING MACHINERY. 2017: 5929-5940