Philip Guo

Philip Guo is a professor at the University of California San Diego, affiliated with the Cognitive Science Department, Design, and Computer Science & Engineering. His research focuses on human-computer interaction, computing education, and programmer productivity, with contributions to tools like the Python Tutor and CDE. He explores how people learn programming, data science, and utilizes AI for educational and software development purposes.

Education & Background:

• Ph.D., Computer Science, Stanford University (2012)
• M.Eng., Electrical Engineering & Computer Science, MIT (2006)

Research Interests:
His work spans educational tools for programming (e.g., Python Tutor), AI applications in learning, and developer productivity. Key themes include:

• Designing scalable educational platforms
• AI-driven coding assistance
• Debugging and visualization tools
• Education equity and hidden curricula

Publications & Trends:
Recent work highlights generative AI applications in coding, peer tutoring challenges, and live programming environments. His articles explore both theoretical frameworks and practical tool development, emphasizing real-world impact in education and software engineering.

Awards & Recognition:

• Best Paper Awards at UIST, CHI, SIGCSE, and other top venues
• ISSTA 10-Year Impact Paper Award (2009)
• Charles & Jennifer Johnson Award for M.Eng. Thesis (2006)

Grants & Collaborations:

• CAREER: Interactive Systems for Learning Programming at Scale (NSF, 2019)
• CRII: CHS grants for scaling peer tutoring (NSF, 2015/2016)

Labs & Teams:
Involved in interdisciplinary research groups at UCSD, focusing on human-centered computing and educational technology. Collaborations span academia and industry to advance tool development and pedagogical practices.