Caryn Tran

About Me

Hi! I am a first year Ph.D. student in Computer Science and Learning Sciences at Northwestern University in Evanston, Illinois. I love to dance and cook!

Research Interest

I am interested in interfaces, programming languages, and learning environments for K-12 CS education. This includes visual programming languages, online programming editors, ML-assisted programming, and collaborative programming. I’m also exploring the future of programming and Computer Science education as it evolves due to LLMs, multi-modal ML, and the invention of new computing interfaces. My secondary interest is broadly in applications and algorithms in ML.

Publications/Posters

  1. Logan Mondal Bhamidipaty, Tommy Bruzzese, Caryn Tran, Rami Ratl Mrad, and Max Kanwal. “DynaDojo: An Extensible Platform for Benchmarking Sample Efficiency in Dynamical System Identification”. Advances in Neural Information Processing Systems. 2023. Web https://openreview.net/forum?id=pTSNoBTk8E _equal contribution_
  2. Caryn Tran and Eleanor O’Rourke. 2023. Understanding novices’ perceptions of “authentic” programming. In Proceedings of the 2023 ACM Conference on International Computing Education Research V.2 (ICER ’23 V2), August 7–11, 2023, Chicago, IL, USA. ACM, New York, NY, USA, 2 pages. https://doi.org/10.1145/3568812.3603492. Poster
  3. Anant Sahai, Joshua Sanz, Vignesh Subramanian, Caryn Tran, and Kailas Vodrahalli. “Blind Interactive Learning of Modulation Schemes: Multi-Agent Cooperation Without Co-Design”. IEEE Access PP. doi: 10.1109/ACCESS.2020.2984218 (Mar. 2020): 1–1. Web. all authors made equal contributions.
  4. A. Sahai, J. Sanz, V. Subramanian, C. Tran and K. Vodrahalli, “Learning to Communicate with Limited Co-design,” 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, USA, 2019, pp. 184-191, doi: 10.1109/ALLERTON.2019.8919749. all authors made equal contributions.

Education

  1. Ph.D. student in Computer Science and Learning Sciences at Northwestern University
  2. M.S. in EECS at UC Berkeley (AI Concentration)
  3. B.A. in CS at UC Berkeley

Work Experience

  1. Adobe Intern and Software Engineer
  2. TeachFX Full-stack + ML Engineer
  3. Synapse School Middle School Computer Science Teacher

University Teaching Experience

  1. CS61AS Spring 2016 TA/Instructor (Structure and Interpretation of Computer Programs)
  2. CS188 Fall 2016 TA (Artificial Intelligence)
  3. CS188 Fall 2017 TA (Artificial Intelligence)
  4. CS188 Summer 2019 Head TA (Artificial Intelligence)

Thoughts

On creativity: Why do I create? Sometimes fiction is closer to the truth than fact.

On learning: We learn when we feel. (and what makes us feel varies so much.) It could be money, or friendship, or community, or recognition, or truth, or beauty, or trauma.

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