Philip Guo is an associate professor of cognitive science at UC San Diego. His research spans human-computer interaction, programming tools, and online learning. He currently studies what motivates people to learn programming and builds tools to help people better understand code and data.

Contact | FAQ / Advice | Google Scholar | Curriculum Vitae

Students

• Ian Drosos (Ph.D., Cognitive Science)
• Sean Kross (Ph.D., Cognitive Science)
• Sam Lau (Ph.D., Cognitive Science)
• Julia Markel (undergrad, Computer Engineering)
• Xiong Zhang (Ph.D., Computer Science, University of Rochester)

Publications

2020

• Wrex: A Unified Programming-by-Example Interaction for Synthesizing Readable Code for Data Scientists. Ian Drosos, Titus Barik, Philip J. Guo, Robert DeLine, Sumit Gulwani. ACM Conference on Human Factors in Computing Systems (CHI), 2020. Best Paper Award
  [bibtex]
• The Design Space of Computational Notebooks: An Analysis of 60 Systems in Academia and Industry. Sam Lau, Ian Drosos, Julia M. Markel, Philip J. Guo. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2020.
  [Podcast | bibtex]
• Learnersourcing at Scale to Overcome Expert Blind Spots for Introductory Programming: A Three-Year Deployment Study on the Python Tutor Website. Philip J. Guo, Julia M. Markel, Xiong Zhang. ACM Conference on Learning at Scale (work-in-progress), 2020.
  [bibtex]
• Designing the Future of Experiential Learning Environments for a Post-COVID World: A Preliminary Case Study. Julia M. Markel and Philip J. Guo. Symposium on the New Future of Work, 2020.
  [Video preview | bibtex]
• Papercode: Generating Paper-Based User Interfaces for Code Review, Annotation, and Teaching. Priyan Vaithilingam, Julia M. Markel, Philip J. Guo. ACM Symposium on User Interface Software and Technology (UIST) (poster), 2020.
  [bibtex]
• Towards a Dynamic Multiscale Personalized Information Space. Jim Hollan, Amy Fox, Philip Guo, Clemens Nylandsted Klokmose, Arvind Satyanarayan, Haijun Xia. Convivial Computing Salon (workshop at the <Programming> conference), 2020.
  [bibtex]

2019

• Practitioners Teaching Data Science in Industry and Academia: Expectations, Workflows, and Challenges. Sean Kross and Philip J. Guo. ACM Conference on Human Factors in Computing Systems (CHI), 2019. Honorable Mention Paper
  [Blog post | bibtex]
• Improv: Teaching Programming at Scale via Live Coding. Charles Chen and Philip J. Guo. ACM Conference on Learning at Scale, 2019.
  [Blog post | bibtex]
• Software Developers Learning Machine Learning: Motivations, Hurdles, and Desires. Carrie J. Cai and Philip J. Guo. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2019. Best Paper Award
  [Blog post | bibtex]
• End-User Programmers Repurposing End-User Programming Tools to Foster Diversity in Adult End-User Programming Education. Sean Kross and Philip J. Guo. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2019.
  [Blog post | bibtex]
• Bespoke: Interactively Synthesizing Custom GUIs from Command-Line Applications By Demonstration. Priyan Vaithilingam and Philip J. Guo. ACM Symposium on User Interface Software and Technology (UIST), 2019.
  [bibtex]
• Mallard: Turn the Web into a Contextualized Prototyping Environment for Machine Learning. Xiong Zhang and Philip J. Guo. ACM Symposium on User Interface Software and Technology (UIST), 2019.
  [Webpage | bibtex]

2018

• Non-Native English Speakers Learning Computer Programming: Barriers, Desires, and Design Opportunities. Philip J. Guo. ACM Conference on Human Factors in Computing Systems (CHI), 2018.
  [Blog post | bibtex]
• Mismatch of Expectations: How Modern Learning Resources Fail Conversational Programmers. April Y. Wang, Ryan Mitts, Philip J. Guo, Parmit K. Chilana. ACM Conference on Human Factors in Computing Systems (CHI), 2018. Honorable Mention Paper
  [Blog post | bibtex]
• Codemotion: Expanding the Design Space of Learner Interactions with Computer Programming Tutorial Videos. Kandarp Khandwala and Philip J. Guo. ACM Conference on Learning at Scale, 2018.
  [Blog post | bibtex]
• Students, Systems, and Interactions: Synthesizing the First Four Years of Learning@Scale and Charting the Future. Sean Kross and Philip J. Guo. ACM Conference on Learning at Scale, 2018.
  [Blog post | bibtex]
• Porta: Profiling Software Tutorials Using Operating-System-Wide Activity Tracing. Alok Mysore and Philip J. Guo. ACM Symposium on User Interface Software and Technology (UIST), 2018. Best Paper Award
  [Blog post | bibtex]
• Fusion: Opportunistic Web Prototyping with UI Mashups. Xiong Zhang and Philip J. Guo. ACM Symposium on User Interface Software and Technology (UIST), 2018.
  [Blog post | bibtex]
• The Impact of Culture on Learner Behavior in Visual Debuggers. Kyle Thayer, Philip J. Guo, Katharina Reinecke. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2018.
  [Blog post | bibtex]

2017

• Older Adults Learning Computer Programming: Motivations, Frustrations, and Design Opportunities. Philip J. Guo. ACM Conference on Human Factors in Computing Systems (CHI), 2017. Honorable Mention Paper
  [Blog post | Press release | Podcast | bibtex]
• CodePilot: Scaffolding End-to-End Collaborative Software Development for Novice Programmers. Jeremy Warner and Philip J. Guo. ACM Conference on Human Factors in Computing Systems (CHI), 2017.
  [Blog post | Webpage | bibtex]
• Hack.edu: Examining How College Hackathons Are Perceived By Student Attendees and Non-Attendees. Jeremy Warner and Philip J. Guo. ACM International Computing Education Research conference (ICER), 2017.
  [Blog post | bibtex]
• DS.js: Turn Any Webpage into an Example-Centric Live Programming Environment for Learning Data Science. Xiong Zhang and Philip J. Guo. ACM Symposium on User Interface Software and Technology (UIST), 2017. Honorable Mention Paper
  [Blog post | Webpage | bibtex]
• Omnicode: A Novice-Oriented Live Programming Environment with Always-On Run-Time Value Visualizations. Hyeonsu Kang and Philip J. Guo. ACM Symposium on User Interface Software and Technology (UIST), 2017.
  [Blog post | bibtex]
• Torta: Generating Mixed-Media GUI and Command-Line App Tutorials Using Operating-System-Wide Activity Tracing. Alok Mysore and Philip J. Guo. ACM Symposium on User Interface Software and Technology (UIST), 2017.
  [Blog post | bibtex]
• HappyFace: Identifying and Predicting Frustrating Obstacles for Learning Programming at Scale. Ian Drosos, Philip J. Guo, Chris Parnin. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2017.
  [Blog post | bibtex]

2016

• Paradise Unplugged: Identifying Barriers for Female Participation on Stack Overflow. Denae Ford, Justin Smith, Philip J. Guo, Chris Parnin. ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE), 2016.
  [Blog post | bibtex]
• Understanding Conversational Programmers: A Perspective from the Software Industry. Parmit K. Chilana, Rishabh Singh, Philip J. Guo. ACM Conference on Human Factors in Computing Systems (CHI), 2016.
  [Blog post | bibtex]

2015

• Codeopticon: Real-Time, One-To-Many Human Tutoring for Computer Programming. Philip J. Guo. ACM Symposium on User Interface Software and Technology (UIST), 2015.
  [Blog post | bibtex]
• Codechella: Multi-User Program Visualizations for Real-Time Tutoring and Collaborative Learning. Philip J. Guo, Jeffery White, Renan Zanelatto. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2015.
  [Blog post | bibtex]
• Codepourri: Creating Visual Coding Tutorials Using A Volunteer Crowd Of Learners. Mitchell Gordon and Philip J. Guo. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2015.
  [Blog post | bibtex]
• Perceptions of Non-CS Majors in Intro Programming: The Rise of the Conversational Programmer. Parmit K. Chilana, Celena Alcock, Shruti Dembla, Anson Ho, Ada Hurst, Brett Armstrong, Philip J. Guo. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2015.
  [Blog post | bibtex]
• Toward a Domain-Specific Visual Discussion Forum for Learning Computer Programming: An Empirical Study of a Popular MOOC Forum. Joyce Zhu, Jeremy Warner, Mitchell Gordon, Jeffery White, Renan Zanelatto, Philip J. Guo. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2015.
  [Blog post | bibtex]
• How High School, College, and Online Students Differentially Engage with an Interactive Digital Textbook. Jeremy Warner, John Doorenbos, Bradley N. Miller, Philip J. Guo. International Conference on Educational Data Mining (EDM), short paper, 2015.
  [bibtex]
• Wait-Learning: Leveraging Wait Time for Second Language Education. Carrie J. Cai, Philip J. Guo, James Glass, Robert C. Miller. ACM Conference on Human Factors in Computing Systems (CHI), 2015.
  [Press release | bibtex]
• OverCode: Visualizing Variation in Student Solutions to Programming Problems at Scale. Elena L. Glassman, Jeremy Scott, Rishabh Singh, Philip J. Guo, Robert C. Miller. ACM Transactions on Computer-Human Interaction (TOCHI), 2015.
  [Press release | Webpage | bibtex]

2014

• Data-Driven Interaction Techniques for Improving Navigation of Educational Videos. Juho Kim, Philip J. Guo, Carrie J. Cai, Shang-Wen (Daniel) Li, Krzysztof Z. Gajos, Robert C. Miller. ACM Symposium on User Interface Software and Technology (UIST), 2014.
  [Webpage | bibtex]
• A Direct Manipulation Language for Explaining Algorithms. Jeremy Scott, Philip J. Guo, Randall Davis. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), short paper, 2014.
  [bibtex]
• Crowdsourcing Step-by-Step Information Extraction to Enhance Existing How-to Videos. Juho Kim, Phu Nguyen, Sarah Weir, Philip J. Guo, Robert C. Miller, Krzysztof Z. Gajos. ACM Conference on Human Factors in Computing Systems (CHI), 2014. Honorable Mention Paper
  [bibtex]
• Demographic Differences in How Students Navigate Through MOOCs. Philip J. Guo and Katharina Reinecke. ACM Conference on Learning at Scale, 2014.
  [Blog post | bibtex]
• How Video Production Affects Student Engagement: An Empirical Study of MOOC Videos. Philip J. Guo, Juho Kim, Rob Rubin. ACM Conference on Learning at Scale, 2014.
  [Blog post | bibtex]
• Understanding In-Video Dropouts and Interaction Peaks in Online Lecture Videos. Juho Kim, Philip J. Guo, Daniel T. Seaton, Piotr Mitros, Krzysztof Z. Gajos, Robert C. Miller. ACM Conference on Learning at Scale, 2014.
  [bibtex]

2013

• Online Python Tutor: Embeddable Web-Based Program Visualization for CS Education. Philip J. Guo. ACM Technical Symposium on Computer Science Education (SIGCSE), 2013.
  [Webpage | bibtex]

2012

• Characterizing and Predicting Which Bugs Get Reopened. Thomas Zimmermann, Nachiappan Nagappan, Philip J. Guo, Brendan Murphy. ACM/IEEE International Conference on Software Engineering (ICSE), Software Engineering In Practice (SEIP) track, 2012. Best Paper Award
  [bibtex]
• Burrito: Wrapping Your Lab Notebook in Computational Infrastructure. Philip J. Guo and Margo Seltzer. USENIX Workshop on the Theory and Practice of Provenance (TaPP), 2012.
  [Blog post | bibtex]
• Software Tools to Facilitate Research Programming. Philip J. Guo. Ph.D. dissertation, Department of Computer Science, Stanford University, 2012.
  [bibtex]
• HAMPI: A Solver for Word Equations over Strings, Regular Expressions and Context-free Grammars. Adam Kiezun, Vijay Ganesh, Shay Artzi, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst. ACM Transactions of Software Engineering Methodology (TOSEM), 2012.
  [bibtex]
• CDE: A Tool for Creating Portable Experimental Software Packages. Philip J. Guo. IEEE Computing in Science and Engineering, 2012.
  [Blog post | bibtex]

2011

• Proactive Wrangling: Mixed-Initiative End-User Programming of Data Transformation Scripts. Philip J. Guo, Sean Kandel, Joseph M. Hellerstein, Jeffrey Heer. ACM Symposium on User Interface Software and Technology (UIST), 2011.
  [bibtex]
• Using Automatic Persistent Memoization to Facilitate Data Analysis Scripting. Philip J. Guo and Dawson Engler. International Symposium on Software Testing and Analysis (ISSTA), 2011.
  [Blog post | bibtex]
• Sloppy Python: Using Dynamic Analysis to Automatically Add Error Tolerance to Ad-Hoc Data Processing Scripts. Philip J. Guo. International Workshop on Dynamic Analysis (WODA), 2011.
  [Blog post | bibtex]
• CDE: Run Any Linux Application On-Demand Without Installation. Philip J. Guo. USENIX Large Installation System Administration Conference (LISA), 2011.
  [Blog post | bibtex]
• CDE: Using System Call Interposition to Automatically Create Portable Software Packages. Philip J. Guo and Dawson Engler. USENIX Annual Technical Conference, short paper, 2011.
  [Blog post | bibtex]
• "Not My Bug!" and Other Reasons for Software Bug Report Reassignments. Philip J. Guo, Thomas Zimmermann, Nachiappan Nagappan, Brendan Murphy. ACM Conference on Computer Supported Cooperative Work (CSCW), 2011.
  [bibtex]

2010

• Characterizing and Predicting Which Bugs Get Fixed: An Empirical Study of Microsoft Windows. Philip J. Guo, Thomas Zimmermann, Nachiappan Nagappan, Brendan Murphy. IEEE International Conference on Software Engineering (ICSE), 2010.
  [bibtex]
• Towards Practical Incremental Recomputation for Scientists: An Implementation for the Python Language. Philip J. Guo and Dawson Engler. USENIX Workshop on the Theory and Practice of Provenance (TaPP), 2010.
  [Blog post | bibtex]

2009

• HAMPI: A Solver for String Constraints. Adam Kiezun, Vijay Ganesh, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst. International Symposium on Software Testing and Analysis (ISSTA), 2009. ACM SIGSOFT Distinguished Paper Award, ISSTA 10-Year Impact Paper Award
  [bibtex]
• Linux Kernel Developer Responses to Static Analysis Bug Reports. Philip J. Guo and Dawson Engler. USENIX Annual Technical Conference, short paper, 2009.
  [bibtex]
• Automatic Creation of SQL Injection and Cross-site Scripting Attacks. Adam Kiezun, Philip J. Guo, Karthick Jayaraman, Michael D. Ernst. IEEE International Conference on Software Engineering (ICSE), 2009.
  [bibtex]
• Two Studies of Opportunistic Programming: Interleaving Web Foraging, Learning, and Writing Code. Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira Dontcheva, Scott R. Klemmer. ACM Conference on Human Factors in Computing Systems (CHI), 2009. Honorable Mention Paper
  [bibtex]
• Opportunistic Programming: Writing Code to Prototype, Ideate, and Discover. Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira Dontcheva, Scott R. Klemmer. IEEE Software, 2009.
  [bibtex]

2008

• Opportunistic Programming: How Rapid Ideation and Prototyping Occur in Practice. Joel Brandt, Philip J. Guo, Joel Lewenstein, Scott R. Klemmer. Workshop on End-User Software Engineering (WEUSE), 2008.
  [bibtex]

2007

• The Daikon system for dynamic detection of likely invariants. Michael D. Ernst, Jeff H. Perkins, Philip J. Guo, Stephen McCamant, Carlos Pacheco, Matthew S. Tschantz, Chen Xiao. Science of Computer Programming, 2007.
  [Website | bibtex]

2006

• Dynamic Inference of Abstract Types. Philip J. Guo, Jeff H. Perkins, Stephen McCamant, Michael D. Ernst. International Symposium on Software Testing and Analysis (ISSTA), 2006.
  [bibtex]
• Automatic Inference and Enforcement of Data Structure Consistency Specifications. Brian Demsky, Michael D. Ernst, Philip J. Guo, Stephen McCamant, Jeff H. Perkins, Martin Rinard. International Symposium on Software Testing and Analysis (ISSTA), 2006.
  [bibtex]
• A Scalable Mixed-Level Approach to Dynamic Analysis of C and C++ Programs. Philip J. Guo. Master of Engineering (M.Eng.) thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 2006. Charles and Jennifer Johnson Award for Outstanding Computer Science Master of Engineering Thesis
  [Webpage | bibtex]

Email Policy

I no longer read or respond to most cold emails due to the large amounts of email I receive. There are only three exceptions:

• I already know you or know someone who knows you.
• You are my professional colleague contacting me about work.
• You are a UCSD student or affiliate. (See below for details.)

If you are a UCSD student or affiliate, feel free to email me about anything except:

• Do not email about trying to get into a course or registration issues. Talk to Thanh Maxwell or Quynh Dieu (undergrad advisors), or Ethel Lu (grad advisor).
  • If a course is overbooked and you are trying to get in, our policy is that we must prioritize students who fulfill all of the prerequisites and are already on the waitlist. I encourage you to always look into alternate courses to enroll in.
• If you're in one of my classes, use the course discussion forum (you can send private messages there) instead of email.
• Do not email me about course grades unless there is a data entry error. Each course's syllabus will have grading policies listed on it.

Please read the FAQ before cold-emailing.

My email address is on the first page of many of my recent publications.

FAQ / Advice

Q: Where can I find your old article / post / etc.?

If it's not linked from this webpage, then I no longer consider it available. Do not ask me for old content that I've taken offline. If you find old copies elsewhere on the internet, please do not share those links since they often contain outdated information.

Q: How can I get a job in a research lab on campus?

This is the most common question I get from students, especially undergrads. Here are some suggestions:

• Take upper-division courses, project-based courses, or even graduate courses, do well in them, then ask the professor at the end of the term whether there are available opportunities.
• Find any professor's office hours that you're interested in, even if they're outside of your department. Then go visit their office hours and ask for opportunities. Even if they don't have any job openings, they might be able to give you valuable advice.
• Find professors' lab webpages and look for postdocs (postdoctoral researchers), research scientists, research staff, lab technicians, graduate students (Ph.D. or masters students) there; then email them to ask for opportunities. They will be easier to reach than professors.
• You can also directly email professors, but your chances of getting a response are lower. Don't be discouraged if they don't respond; keep trying hard to find new opportunities.
• Look for newly-hired professors (often called assistant professors) since they may be looking to grow their new lab so are more likely to respond to your email.
• Again, be willing to look outside your department for opportunities.
• If any professors are giving special talks or guest lectures on campus, attend and go up to them afterward to ask for relevant opportunities.
• If you have friends who currently work in a research lab, try to get them to introduce you to the relevant graduate students, postdocs, research scientists, or professors. A good referral can be very effective.

Q: How can I get an internship or job related to HCI/UX/Design?

Check out HCI/UX/Design Jobs for New College Grads.

Q: How can I best ask for a recommendation letter?

Read Asking for Recommendation Letters.

Q: How can I improve my Ph.D. program applications?

Read A Five-Minute Guide to Ph.D. Program Applications.

Q: Got any advice for new Ph.D. students?

• Advice for early-stage Ph.D. students
• Ph.D. Student Internships
• Attending Professional Conferences as a Newcomer

Q: Got any advice for aspiring faculty?

• Three quick tips for faculty job applications
• PDF notes on tenure-track faculty job search
• Comparing academic departments when deciding between faculty job offers

Q: Got any advice for new assistant professors?

• What I would've wanted to know as a first-year assistant professor
• Professoring Logistics: Mundane but useful ways to organize faculty work life
• Managing the Logistics of Teaching Large Courses: A 10-Part Series
• What I would've wanted to know as a 3rd/4th-year assistant professor
• Example NSF CAREER proposals (including my own annotated one)