My research spans human-computer interaction, programming tools, and online learning.

• Short summary of my research
• Overview of this website
• Publications | Google Scholar | Curriculum Vitae

Philip Guo is an assistant professor of Cognitive Science and an affiliate assistant professor of Computer Science and Engineering at UC San Diego. His research spans human-computer interaction, programming tools, and online learning. He now focuses on building scalable systems that help people learn computer programming and data science. He is the creator of Python Tutor (http://pythontutor.com/), a widely-used code visualization and collaborative learning platform. So far, over five million people in over 180 countries have used it to visualize over 75 million pieces of Python, Java, JavaScript, C, C++, and Ruby code. Philip's research has won Best Paper and Honorable Mention awards at the CHI, UIST, ICSE, and ISSTA conferences, and an NSF CAREER award.

Philip received S.B. and M.Eng. degrees in Electrical Engineering and Computer Science from MIT and a Ph.D. in Computer Science from Stanford. His Ph.D. dissertation was one of the first to create programming tools for data scientists. Before becoming a professor, he built online learning tools as a software engineer at Google, a research scientist at edX, and a postdoc at MIT. Philip's website http://pgbovine.net/ contains over 500 articles, videos, and podcast episodes and gets over 750,000 page views per year.

(high-resolution photo for promotional materials)

Awards and Honors

• NSF CAREER Award, 2019
• ISSTA 10-Year Impact Paper Award, 2019
• UIST Best Paper Award, 2018
• CHI Honorable Mention Paper Award, 2018
• UIST Honorable Mention Paper Award, 2017
• CHI Honorable Mention Paper Award, 2017
• Google Faculty Research Award, 2015
• CHI Honorable Mention Paper Award, 2014
• ICSE Software Engineering In Practice Best Paper Award, 2012
• ACM SIGSOFT Distinguished Paper Award, 2009
• CHI Honorable Mention Paper Award, 2009
• NSF Graduate Research Fellowship, 2009–2011
• NDSEG Fellowship, 2006–2009
• MIT EECS Master's Thesis Award in Computer Science, 2006

Selected Talks and Press

• Learning Programming at Scale: Code, Data, and Environment, CMU HCI Seminar talk, 2018
• Learning Programming at Scale, 2018 research seminar talk
• Making Programming Accessible for All, MIT Connector, 2017
• Learning Programming at Scale, CACM, 2017
• Geeking Out in the Golden Years, UCSD Press Release, 2017
• Design Lab Faculty to Launch NSF-Funded Graduate Education Project, UCSD Press Release, 2017
• Interactive Systems for Learning Programming at Scale, 2016 job interview talk
• Learning Programming at Scale, O'Reilly Ideas, 2015
• Silent Technical Privilege, Slate, 2014
• Meet the Professional: Philip Guo, Khan Academy, 2014
• Programming On Demand: Wrangling, Iterating, and Opportunistic Learning, 2013 job interview talk
• Lessons from the Grind, MIT Technology Review, 2013

Graduate Students

• Charles Chen (masters, Computer Science & Engineering)
• Priyan Vaithilingam (masters, Computer Science & Engineering)
• Ian Drosos (Ph.D., Cognitive Science)
• Sean Kross (Ph.D., Cognitive Science)
• Xiong Zhang (Ph.D., Computer Science, University of Rochester)

Teaching

UC San Diego

• COGS 120/CSE 170: Human-Computer Interaction Design (Fall 2018, Fall 2017, Fall 2016)
• COGS 121: Human-Computer Interaction Programming Studio (Spring 2018, Spring 2017)
• COGS 124: HCI Technical Systems Research (Fall 2018, Fall 2017)
• COGS 231: Design Seminar on Human-Centered Programming (Spring 2018, Spring 2017)

University of Rochester

• CSC 210: Principles of Web Application Development (Fall 2015, Fall 2014)
  • Lecture videos: Web Programming Video Lectures
  • Tutorial videos: assertions, command-line, Git, Flask
• CSC 253: Dynamic Languages & Software Development (Fall 2014)
  • Lecture videos: CPython interpreter codewalk

MIT

• 6.813: User Interface Design & Implementation (Spring 2014)
  • co-taught with Rob Miller, Daniel Jackson, and David Karger