Nate Weinman

Nate (Nathaniel) Weinman

HCI and Education · Ph.D. Candidate · nweinman@berkeley.edu · linkedin · github

Hey! I am a fourth year Ph.D. candidate advised by Armando Fox and Marti Hearst in the department of Electrical Engineering and Computer Science at UC Berkeley. My research lies at the intersection of human computer interaction, education, and software engineering. I am grateful to have been supported by a department EECS Excellence Award and an NSF GRFP Fellowship.

I am interested in undrestanding the process by which people engage with new knowledge, and building tools to improve those processes. In my thesis work, I am focused on helping instructors target student learning. I have introduced and studied the power of Faded Parsons Problems (examples) in CS1 and CS2 and beyond to teach students relevant programming skills.

Outside of my thesis work, I worked on a project supporting data scientists' exploratory processes by extending Jupyter notebooks. Our extensions allowed data scientists to more directly express and navigate between decision points. Additionally, I am currently advising a Master's student and collaborating with the University of Seville to understand how gender bias affects pair programming sessions.

Experience (Highlights)

Most recent CV - last updated Nov 2019

Faded Parsons Problems

Equity and Inclusion

Software Engineering/Data Science

Teaching

  • Berkeley: CS375 - Teaching Techniques for Computer Science
  • Berkeley: CS160 - User Interface Design and Development
  • Google: Taught day-long Python courses to fellow Googlers
  • Airbnb: Taught new hires about the internationalization service

Misc/Other