Mackenzie Leake

Mackenzie Leake

I am a PhD student in computer science at Stanford University advised by Maneesh Agrawala. I received a MS in computer science at Stanford and a BA in computational science and studio art at Scripps College. I've been fortunate to intern at Chatham Labs, Adobe Research, and IBM Research Almaden.

Contact Information:

first initial + lastname @cs.stanford.edu

Recent Projects

Improv
PatchProv is a design tool that supports improvisational quilt design. Quilters capture images of their fabrics and utilize the digital tool to iterate between design and sewing steps.

(CHI paper - coming soon!)

Slideshow
We present a method for automatically generating audio-visual slideshows from a text article by identifying representative concrete phrases from the text and searching for visuals that match these words.
(CHI paper | video | website)
Roughcut
We designed a tool that uses the structure of dialogue-driven scenes and cinematographic principles to edit video sequences automatically. The input is a script and multiple video takes, capturing different camera framings or performances of the scene. Our system automatically cuts together a video based on film-editing idioms.
(SIGGRAPH paper | video | website)
CSEd
Recommendations for designing online communities for high school computer science teachers. Based upon interviews with high school computer science teachers, we propose strategies for improving online resources for computer science teachers.
(SIGCSE paper)

Publications

  • Leake, M., Lai, F., Grossman, T., Wigdor, D., & Lafreniere, B. (2021). PatchProv: Supporting Improvisational Design Practices for Modern Quilting. CHI 2021 (to appear).
  • Leake, M., Kim, J., Shin, H., & Agrawala, M. (2020). Generating Audio-Visual Slideshows from Text Articles Using Word Concreteness. CHI Conference on Human Factors in Computing Systems (CHI'20).
  • Leake, M., Davis, A., Truong, A., & Agrawala, M. (2017). Computational Video Editing for Dialogue-Driven Scenes. ACM Transactions on Graphics (SIGGRAPH'17), 36(4), 130:1-130:14.
  • Leake, M. & Lewis, C.M. (2017). Designing CS Resource Sharing Sites for All Teachers. Proceedings of the 48th Technical Symposium on Computer Science Education (SIGCSE'17). 357-362.
  • Leake, M. & Lewis, C.M. (2016). Designing a New System for Sharing Computer Science Teaching Resources. Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work & Social Computing Companion (CSCW'16). 321-324.
  • Leake, M. (2015). Chart-based Strategies for Solving Bayesian Inference Problems. Journal of Computing Sciences in Colleges. 30(4), 107-114.
  • Leake, M., Xia, L., Rocki, K., & Imaino, W. (2015). Effect of Spatial Pooler Initialization on Column Activity in Hierarchical Temporal Memory. 29th AAAI Conference on Artificial Intelligence (AAAI'15), 4176-4177.

Awards

  • Adobe Research Fellowship, 2017
  • Brown Institute for Media Innovation Magic Grant, 2016
  • Stanford EDGE-STEM Fellowship, 2015
  • Stanford School of Engineering Fellowship, 2015
  • Goldwater Scholar, 2014
  • Amgen Scholar, 2013
  • James E. Scripps Scholarship, 2011-2015