I'm an Assistant Professor in Computer Science & Engineering at the University of Minnesota. I am also affiliated with the GroupLens Research Lab, a group of HCI faculty and students in the department.

My research areas are human-centered artificial intelligence, explainability and interpretability, and hybrid intelligence systems. I study these areas in two ways: (1) critically evaluating existing systems and tools on meeting their intended goals; and (2) designing and building new systems that leverage human-centered cognitive, social, and organizational norms for human-machine collaboration. I apply these methods in a variety of domains, including exploratory data analysis, workplace wellbeing and productivity, knowledge search and sensemaking.

I received my Ph.D. in Information and Computer Science & Engineering from the University of Michigan, where I was co-advised by Cliff Lampe and Eric Gilbert.

I am recruiting Ph.D., master's, and undergraduate students to establish my new lab! If you're interested in the research areas mentioned above, please feel free to contact me via email. Ph.D. students must apply through the University of Minnesota Computer Science & Engineering Ph.D. program. This has a Fall deadline in December/January of each year.

Latest News

August 2023: Started my new position as a tenure-track faculty at the University of Minnesota. Excited to teach a research seminar on Human-Centered AI this Fall.
May 2023: Successfully defended my dissertation!
August 2022: FeedLens accepted to UIST. We present results from applying our polymorphic lenses technique to Semantic Scholar, improving engagement and exploration for literature search.
June 2022: Paper on Sensible AI accepted to FAccT. We propose an alternate framework for interpretability and explainability grounded in sensemaking theory from organizational studies.
Feb 2022: Paper on comparing Automatic Emotion Recognition technology and self-reported affective profiles accepted to CHI.
Jan 2022: I passed my dissertation proposal!
September 2021: Honored to receive the Google PhD Fellowship!

Upcoming Travel

Sept 28-29, 2023:  Stanford University, CA

Publications

Conference and Journal Papers

  1. H. Kaur, M. Conrad, D. Rule, C. Lampe, and E. Gilbert. (2023, August). Interpretability Gone Bad: The Role of Bounded Rationality in How Practitioners Understand Machine Learning. In Proceedings of the ACM - Human Computer Interaction (PACM-HCI;
    to be presented at CSCW 2024).
  2. H. Kaur, D. Downey, A. Singh, E. Cheng, D. Weld, and J. Bragg (2022, October). FeedLens: Polymorphic Lenses for Personalizing Exploratory Search over Knowledge Graphs. In Proceedings of the ACM Conference on User Interface Software and Technology (UIST 2022).
  3. H. Kaur, E. Adar, E. Gilbert, and C. Lampe (2022, June). Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theory. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency (FAccT 2022).
  4. H. Kaur, D. McDuff, A. C. Williams, J. Teevan, and S. T. Iqbal (2022, May). "I Didn't Know I Looked Angry": Characterizing Observed Emotion and Reported Affect at Work. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2022).
  5. O. Inel, T. Duricic, H. Kaur, E. Lex, and N. Tintarev (2021, November). Design Implications for Explanations: Supporting Reflective Assessment of Videos on Controversial Topics. (Frontiers in Artificial Intelligence 2021).
  6. D.A. Melis, H. Kaur, H. Daumé, H. Wallach, and J. W. Vaughan.(2021, November). A Human-Centered Approach to Interpretability Using Weight of Evidence. In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2021).
  7. H. Kaur and C. Lampe (2020, March). Using Affordances to Improve AI Support of Social Media Posting Decisions. In Proceedings of the ACM International Conference on Intelligent User Interfaces (IUI 2020).
    [IUI Best Paper Honorable Mention]
  8. H. Kaur, H. Nori, S. Jenkins, R. Caruana, H. Wallach, J. W. Vaughan. Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2020).
    [CHI Best Paper Honorable Mention]
  9. H. Kaur, A. Williams, D. McDuff, M. Czerwinski, J. Teevan, S. Iqbal. Optimizing for Happiness and Productivity: Modeling Opportune Moments for Transitions and Breaks at Work. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2020).
  10. A. Williams, H. Kaur, J. Teevan, R. White, S. Iqbal, A. Fourney (2019, October). Mercury: Empowering Programmers’ Mobile Work Practices with Microproductivity. In Proceedings of the ACM Conference on User Interface Software and Technology (UIST 2019).
  11. H. Kaur, A. Williams, A.L. Thompson, W.S. Lasecki, S. Iqbal, J. Teevan (2018, November). Creating Better Action Plans for Writing Tasks via Vocabulary-Based Planning. In Proceedings of the International ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2018). New York, NY.
  12. R. Fok, H. Kaur, S. Palani, M.E. Mott, W.S. Lasecki. (2018, November) Towards More Robust Speech Interactions for Deaf and Hard of Hearing Users. In Proceedings of the International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2018). Galway, Ireland.
  13. A. Rao, H. Kaur, W.S. Lasecki (2018, July). Plexiglass: Multiplexing Passive and Active Tasks for More Efficient Crowdsourcing. In Proceedings of the AAAI Conference on Human Computation (HCOMP 2018). Zurich, Switzerland.
  14. A. Williams, H. Kaur, G. Mark, A.L. Thompson, S. Iqbal, J. Teevan (2018, April). Supporting Workplace Detachment and Reattachment with Conversational Intelligence. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI 2018).
  15. H. Kaur, M. Gordon, Y. Yang, J. Bigham, J. Teevan, E. Kamar, W.S. Lasecki (2017, October). CrowdMask: Using Crowds to Preserve Privacy in Crowd-Powered Systems via Progressive Filtering. In Proceedings of the 5th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2017).
  16. F. M. Harper, F. Xu, H. Kaur, K. Condiff, S. Chang, L. Terveen (2015, September). Putting users in control of their recommendations. In Proceedings of the 9th ACM Conference on Recommender Systems (RecSys 2015).

Posters

  1. H. Kaur, A.C. Williams, A.L. Thompson, W.S. Lasecki, S. Iqbal, and J. Teevan. Using Vocabularies to Collaboratively Create Better Plans for Writing Tasks. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI 2018).
  2. H. Kaur, I. Johnson, H.J. Miller, L.G. Terveen, C. Lampe, B. Hecht, W.S. Lasecki. Oh The Places You’ll Share: An Affordances-Based Model of Social Media Posting Behaviors In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI 2018).
  3. H. Kaur, B. Hecht, C. Lampe, W. Lasecki. To Share or Not to Share: An Affordances Based Modeling of Social Media Usage For Posting Content. CRA-W Grad Cohort Workshop, Washington DC, 2017.
  4. H. Kaur, H. Miller, L. Terveen. Building Feeds Without Friends. University of Minnesota Undergraduate Research Symposium, Minneapolis, 2016.

Workshop Papers

  1. H. Kaur, A.C. Williams, W.S. Lasecki. Building Shared Mental Models between Humans and AI for Effective Collaboration. In CHI 2019 Workshop on Where is the Human? Bridging the Gap Between AI and HCI. Glasgow, Scotland. 2019.
  2. S.R. Gouravajhala, H. Kaur, R. Fok, and W.S. Lasecki. Challenges in Making Situated Interactions Accessible to Motor-Impaired Users. In Workshop at the International ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2018).
  3. H. Kaur, C. Lampe, and W.S. Lasecki. Crowdsourcing Law and Policy via Crowd-Civic Systems. In Workshop at the International ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2017).