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jane l. e

postdoc at the design lab · je [at] ucsd.edu · ejane.me

I'm looking for faculty and industry research positions :)
research · teaching · diversity · cv

I am currently a postdoc at The Design Lab @ UCSD as part of the debut cohort of UCSD CSE’s Postdoctoral Fellows Program, where I am mentored by Haijun Xia and Steven Dow. I recently graduated from Stanford University with a PhD in Computer Science where I was coadvised by James Landay and Pat Hanrahan.

My research lies primarily at the intersection of human computer interaction and computer graphics. Broadly, I’m interested in thinking about how to design computational tools that can support users in developing domain expertise, which I currently explore within the domain of creativity. My work takes inspiration from cognitive science and education theory to design computational tools that scaffold novices’ creative processes. Inspired by how expert artists have trained their eyes to “see” in a certain way, I aim to design guidance that helps novices develop their own “artistic vision”—and in doing so, support them in developing their own artistic expertise.

More specifically, my dissertation work focused on photography and videography interfaces. I designed in-camera guidance interfaces that can help users be more aware of their artistic choices. During my postdoc, I am more directly exploring the impact of computational feedback on creativity to inform the design of such creativity support tools.

On the side, I am a dancer 🩰 and a photo enthusiast 📷. I am a foodie 🍛 and also a lover of fitness 🤸🏻‍♀️.

announcements

April 2024 Invited talks at USC CS, NUS Computing, and UCSD Cognitive Science
March 2024 “Jamplate: Exploring LLM-Enhanced Templates for Idea Reflection” presented at IUI 2024 by Tone Xu
March 2024 Invited talks at Oregon State EECS, Tufts CS, UVA CS, Cornell IS Colloquium, and Indiana HCC
February 2024 Invited talks at UW-Madison CS and Stevens Institute CS
February 2024 Submitted camera-ready to CSCW 2024 “ProcessGallery: Contrasting Early and Late Iterations for Design Principle Learning” (co-lead by Grace Yen and me)
November 2023 “Color Field: Developing Professional Vision by Visualizing the Effects of Color Filters” presented at UIST 2023 by Matt Beaudouin-Lafon
July 2023 Invited talk at DUB Seminar (video)
June 2023 Invited talks at UC Irvine Informatics, Fudan University EDA AI & Math Seminar, and Tsinghua HCI Seminar
May 2023 Invited talk at Berkeley Institute of Design Seminar
April 2023 “DataParticles: Block-Based and Language-Oriented Authoring of Animated Unit Visualization” presented at CHI 2023 by Rima Cao (received Best Paper )
April 2023 Invited talk at UT Austin HCI Seminar
October 2022 Attended Rising Stars in EECS 2022 at UT Austin

publications

  1. When to Give Feedback: Exploring Tradeoffs in the Timing of Design Feedback
    Jane L. E*, Yu-Chun Grace Yen*, Isabelle Yan Pan, Grace Lin, Mingyi Li, Hyoungwook Jin, Mengyi Chen, Haijun Xia, and Steven P. Dow
    (To Appear) Creativity & Cognition 2024.
  2. ProcessGallery: Contrasting Early and Late Iterations for Design Principle Learning
    Yu-Chun Grace Yen*, Jane L. E*, Hyoungwook Jin, Mingyi Li, Grace Lin, Isabelle Yan Pan, and Steven P. Dow
    (To Appear) CSCW 2024.
  3. Jamplate: Exploring LLM-Enhanced Templates for Idea Reflection
    Xiaotong (Tone) Xu, Jiayu Yin, Catherine Gu, Jenny Mar, Sydney Zhang, Jane L. E, and Steven P. Dow
    IUI 2024.
  4. Color Field: Developing Professional Vision by Visualizing the Effects of Color Filters
    Matthew T Beaudouin-Lafon, Jane L. E, and Haijun Xia
    UIST 2023.
  5. Machines as Collaborators for Art and Rituals
    Jane L. E, Cathy Mengying Fang, and Sam Bourgault
    XRDS Magazine 2023.
  6. Exploring the Horizon of Computation for Creativity
    Sam Bourgault, and Jane L. E
    XRDS Magazine 2023.
  7. DataParticles: Block-based and Language-oriented Authoring of Animated Unit Visualizations
    Yining Cao, Jane L. E, Zhutian Chen, and Haijun Xia
    CHI 2023. Best Paper
  8. Developing Comic-based Learning Toolkits for Teaching Computing to Elementary School Learners
    Francisco Castro, Sangho Suh, Jane L. E, Weena Naowaprateep, and Yang Shi
    SIGCSE Posters 2023.
  9. Artistic Vision: Providing Contextual Guidance for Capture-Time Decisions
    Jane L. E
    Stanford Unversity 2021.
  10. Dynamic Guidance for Decluttering Photographic Compositions
    Jane L. E, Kevin Y. Zhai, Jose Echevarria, Ohad Fried, Pat Hanrahan, and James A. Landay
    UIST 2021.
  11. Adaptive Photographic Composition Guidance
    Jane L. E, Ohad Fried, Jingwan Lu, Jianming Zhang, Radomı́r Měch, Jose Echevarria, Pat Hanrahan, and James A. Landay
    CHI 2020.
  12. Optimizing Portrait Lighting at Capture-Time Using a 360 Camera as a Light Probe
    Jane L. E, Ohad Fried, and Maneesh Agrawala
    UIST 2019.
  13. Understanding the Accessibility of Smartphone Photography for People with Motor Impairments
    Martez E. Mott, Jane L. E, Cynthia L. Bennett, Edward Cutrell, and Meredith Ringel Morris
    CHI 2018.
  14. How Teens with Visual Impairments Take, Edit, and Share Photos on Social Media
    Cynthia L. Bennett, Jane L. E, Martez E. Mott, Edward Cutrell, and Meredith Ringel Morris
    CHI 2018.
  15. Drone Near Me: Exploring Touch-Based Human-Drone Interaction
    Parastoo Abtahi, David Y. Zhao, Jane L. E, and James A. Landay
    IMWUT / UbiComp 2017.
  16. Human Perception of Swarm Robot Motion
    Griffin Dietz, Jane L. E, Peter Washington, Lawrence H. Kim, and Sean Follmer
    CHI EA 2017.
  17. Drone & Wo: Cultural Influences on Human-Drone Interaction Techniques
    Jane L. E, Ilene L. E, James A. Landay, and Jessica R. Cauchard
    CHI 2017.
  18. Towards a Drone Cinematographer: Guiding Quadrotor Cameras using Visual Composition Principles
    Niels Joubert*, Jane L. E*, Dan B Goldman, Floraine Berthouzoz, Mike Roberts, James A. Landay, and Pat Hanrahan
    arXiv 2016.
  19. Drone & Me: An Exploration into Natural Human-Drone Interaction
    Jessica R. Cauchard, Jane L. E, Kevin Y. Zhai, and James A. Landay
    UbiComp 2015.
  20. Fully Automatic Generation of Anatomical Face Simulation Models
    Matthew Cong, Michael Bao, Jane L. E, Kiran S. Bhat, and Ronald Fedkiw
    SCA 2015.