Julia Mae Markel

Photo of Me

I'm a final-year PhD student in computer science at Stanford advised by James Landay. My research interests are in human-computer interaction with a focus on human-centered AI. I'm currently working on projects that span philosophy of the self and AI, specifically investigating how we can leverage the notion of the plural self to design AI systems and understand their effects on individuals' self-concepts. Early in my PhD I worked with Chris Piech on building support tools for computer science educators.

  • Julia M. Markel, Jane L. E, James Landay, Hariharan Subramonyam. Which Self Does AI Remember? LLM Memory and the Plural Self. Conference on Neural Information Processing Systems (NeurIPS) Workshop on AI and the Self, 2026..

  • Julia M. Markel, Steven G. Opferman, James Landay, Chris Piech. GPTeach: Interactive TA Training with GPT Based Students. ACM Conference on Learning at Scale, 2023.

  • Julia M. Markel and Philip J. Guo. Inside the Mind of a CS Undergraduate TA: A Firsthand Account of Undergraduate Peer Tutoring in Computer Labs. ACM Technical Symposium on Computer Science Education (SIGCSE), 2021. Best Paper Award

  • Julia M. Markel and Philip J. Guo. Designing the Future of Experiential Learning Environments for a Post-COVID World: A Preliminary Case Study. Symposium on the New Future of Work, 2020 (Blog post summary)

  • C. Ailie Fraser, Julia M. Markel, N. James Basa, Mira Dontcheva, Scott Klemmer. ReMap: Lowering the Barrier to Help-Seeking with Multimodal Search. ACM Symposium on User Interface Software and Technology (UIST), 2020.

  • Sam Lau, Ian Drosos, Julia M. Markel, Philip J. Guo. The Design Space of Computational Notebooks: An Analysis of 60 Systems in Academia and Industry. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2020.

  • Priyan Vaithilingam, Julia M. Markel, Philip J. Guo. Papercode: Generating Paper-Based User Interfaces for Code Review, Annotation, and Teaching. ACM Symposium on User Interface Software and Technology (UIST) (poster), 2020.

  • C. Ailie Fraser, Julia M. Markel, N. James Basa, Mira Dontcheva, and Scott Klemmer. ReMap: Multimodal Help-Seeking. ACM Symposium on User Interface Software and Technology (UIST) (poster), 2019.

  • Philip J. Guo, Julia M. Markel, Xiong Zhang. Learnersourcing at Scale to Overcome Expert Blind Spots for Introductory Programming: A Three-Year Deployment Study on the Python Tutor Website. ACM Conference on Learning at Scale (work-in-progress), 2020.

    • jmarkel@stanford.edu
    Google Scholar
    GitHub
    Twitter
    LinkedIn