Eunice Jun

Eunice Jun


Engineering VI - Room 399

Phone: (310) 206-3321
Fax: (310) 825-2273

  •  Human-Computer Interaction
  • Programming Languages/Software Engineering
  • Statistics
  • Data Science programming

  • Gu, K., Jun, E., & Althoff, T. (2023). Understanding and Supporting Debugging Workflows in Multiverse Analysis. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1–19.
  • Tran O’Leary, J., Jun, E. M., & Peek, N. (2022). Verso: Extending Computational Notebooks for Exploratory Digital Fabrication. ACM Symposium on Computational Fabrication 
  • Jun, E. M., Seo*, A. L., Heer, J., & Just, R. (2022). Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI).
  • Jun, E. M., Birchfield*, M., De Moura*, N., Heer, J., & Just, R. (2022). Hypothesis Formalization: Empirical Findings, Software Limitations, and Design Implications. ACM Transactions on Computer-Human Interaction (TOCHI)29(1).
  • McDuff, D., Jun, E. M., Rowan, K., & Czerwinski, M. (2021). Longitudinal Observational Evidence of the Impact of Emotion Regulation Strategies on Affective Expression. IEEE Transactions on Affective Computing.
  • Jun, E. M., McDuff, D., & Czerwinski, M. (2019). Circadian rhythms and physiological synchrony: Evidence of the impact of diversity on small group creativity. Proceedings of the ACM on Human-Computer Interaction3(CSCW), 1–22.
  • Jun, E. M., Daum, M., Roesch, J., Chasins, S. E., Berger, E., Just, R., & Reinecke, K. (2019). Tea: A high-level language and runtime system for automating statistical analysis. Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology, 591–603.
  • Liu, Y., Jun, E. M., Li, Q., & Heer, J. (2019). Latent space cartography: Visual analysis of vector space embeddings. Computer Graphics Forum38(3), 67–78
  • Jun, E. M., Jo*, B. A., Oliveira, N., & Reinecke, K. (2018). Digestif: promoting science communication in online experiments. Proceedings of the ACM on Human-Computer Interaction2(CSCW), 1–26.
  • Jun, E. M., Arian, M., & Reinecke, K. (2018). The potential for scientific outreach and learning in mechanical turk experiments. Proceedings of the Fifth Annual ACM Conference on Learning at Scale, 1–10.
  • Jun, E. M., Hsieh, G., & Reinecke, K. (2017). Types of motivation affect study selection, attention, and dropouts in online experiments. Proceedings of the ACM on Human-Computer Interaction1(CSCW), 1–15.
  • Oliveira, N., Jun, E. M., & Reinecke, K. (2017). Citizen science opportunities in volunteer-based online experiments. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), 6800–6812.
  • Jun, E. M., Stefanucci, J. K., Creem-Regehr, S. H., Geuss, M. N., & Thompson, W. B. (2015). Big foot: Using the size of a virtual foot to scale gap width. ACM Transactions on Applied Perception (TAP)12(4), 1–12.

PhD, [2023] University of Washington - Computer Science & Engineering

  • Madrona Grand Prize Runner-up, Madrona VC, 2022
  • Best Paper Honorable Mention for CHI22, 2022
  • Rising Stars in EECS, MIT, 2021
  • Graduate Research Fellowship, National Science Foundation, 2018-2022
  • Madrona Grand Prize Winner, Madrona VC, 2017
  • Best Paper Honorable Mention for CSCW17, 2017
  • Wilma Bradley Endowed Fellowship in Computer Science & Engineering, UW CSE, 2016-2017
  • Barry M. Goldwater Scholarship Honorable Mention, 2015
  • TAP Paper Highlight in Special Issue, 2015