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ORCIDPhilip J. Guo
Philip Jia Guo
Person information
- affiliation: University of California, San Diego, Department of Cognitive Science, CA, USA
- affiliation: University of Rochester, Department of Computer Science, NY, USA
- affiliation: MIT, Computer Science and Artificial Intelligence Lab, Cambridge, MA, USA
- affiliation: edX, Cambridge, MA, USA
- affiliation: Stanford University, Department of Computer Science, CA, USA
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2020 – today
- 2024
[c81]Devamardeep Hayatpur
, Brian Hempel, Kathy Chen, William Duan, Philip J. Guo, Haijun Xia:
Taking ASCII Drawings Seriously: How Programmers Diagram Code. CHI 2024: 931:1-931:16- [c80]Alice Mira Chung, Philip J. Guo:
Perpetual Teaching Across Temporary Places: Conditions, Motivations, and Practices of Media Artists Teaching Computing Workshops. ICER (1) 2024: 374-388 - [c79]Ruanqianqian (Lisa) Huang, Philip J. Guo, Sorin Lerner:
UNFOLD: Enabling Live Programming for Debugging GUI Applications. VL/HCC 2024: 306-316 - 2023
- [j15]Philip J. Guo:
Six Opportunities for Scientists and Engineers to Learn Programming Using AI Tools Such as ChatGPT. Comput. Sci. Eng. 25(3): 73-78 (2023) - [c78]Sam Lau, Sean Kross, Eugene Wu, Philip J. Guo:
Teaching Data Science by Visualizing Data Table Transformations: Pandas Tutor for Python, Tidy Data Tutor for R, and SQL Tutor. DataEd@SIGMOD 2023 - [c77]Kendall Nakai, Philip J. Guo:
Uncovering the Hidden Curriculum of University Computing Majors via Undergraduate-Written Mentoring Guides: A Learner-Centered Design Workflow. ICER (1) 2023: 63-77 - [c76]Sam Lau, Philip J. Guo:
From "Ban It Till We Understand It" to "Resistance is Futile": How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot. ICER (1) 2023: 106-121 - [c75]Thomas D. LaToza, Esther Guerra, Philip J. Guo:
Foreword. VL/HCC 2023: xii-xiv - [e1]Daniel Spikol, Olga Viberg, Alejandra Martínez-Monés, Philip J. Guo:
Proceedings of the Tenth ACM Conference on Learning @ Scale, Copenhagen, Denmark, July 20-22, 2023. ACM 2023 [contents] - 2022
- [j14]Georgios Sakkas, Madeline Endres, Philip J. Guo, Westley Weimer, Ranjit Jhala:
Seq2Parse: neurosymbolic parse error repair. Proc. ACM Program. Lang. 6(OOPSLA2): 1180-1206 (2022) - [c74]Ian Drosos, Philip J. Guo:
The Design Space of Livestreaming Equipment Setups: Tradeoffs, Challenges, and Opportunities. Conference on Designing Interactive Systems 2022: 835-848 - [c73]Sam Lau, Justin Eldridge, Shannon Ellis, Aaron Fraenkel, Marina Langlois, Suraj Rampure, Janine Tiefenbruck, Philip J. Guo:
The Challenges of Evolving Technical Courses at Scale: Four Case Studies of Updating Large Data Science Courses. L@S 2022: 201-211 - [c72]Kendall Nakai, Philip J. Guo:
Scaling Up Access to the Hidden Curriculum: A Design Methodology for Creating Undergraduate Mentoring Guides. L@S 2022: 413-417 - [c71]Sam Lau, Deborah Nolan, Joseph Gonzalez, Philip J. Guo:
How Computer Science and Statistics Instructors Approach Data Science Pedagogy Differently: Three Case Studies. SIGCSE (1) 2022: 29-35 - [c70]Sean Kross, Philip J. Guo:
Five Pedagogical Principles of a User-Centered Design Course that Prepares Computing Undergraduates for Industry Jobs. SIGCSE (1) 2022: 168-174 - [c69]Sam Lau, Philip J. Guo:
Codehound: Helping Instructors Track Pedagogical Code Dependencies in Course Materials. SPLASH-E 2022: 1-6 - [c68]Rimika Chaudhury, Philip J. Guo, Parmit K. Chilana:
"There's no way to keep up!": Diverse Motivations and Challenges Faced by Informal Learners of ML. VL/HCC 2022: 1-11 - 2021
- [j13]Sean Kross, Philip J. Guo:
Orienting, Framing, Bridging, Magic, and Counseling: How Data Scientists Navigate the Outer Loop of Client Collaborations in Industry and Academia. Proc. ACM Hum. Comput. Interact. 5(CSCW2): 311:1-311:28 (2021) - [c67]Julia M. Markel, Philip J. Guo:
Inside the Mind of a CS Undergraduate TA: A Firsthand Account of Undergraduate Peer Tutoring in Computer Labs. SIGCSE 2021: 502-508 - [c66]Philip J. Guo:
Ten Million Users and Ten Years Later: Python Tutor's Design Guidelines for Building Scalable and Sustainable Research Software in Academia. UIST 2021: 1235-1251 - [c65]Ian Drosos, Philip J. Guo:
Streamers Teaching Programming, Art, and Gaming: Cognitive Apprenticeship, Serendipitous Teachable Moments, and Tacit Expert Knowledge. VL/HCC 2021: 1-6 - [i1]Sean Kross, Philip J. Guo:
Orienting, Framing, Bridging, Magic, and Counseling: How Data Scientists Navigate the Outer Loop of Client Collaborations in Industry and Academia. CoRR abs/2105.05849 (2021) - 2020
- [c64]Ian Drosos, Titus Barik, Philip J. Guo, Robert DeLine, Sumit Gulwani:
Wrex: A Unified Programming-by-Example Interaction for Synthesizing Readable Code for Data Scientists. CHI 2020: 1-12 - [c63]Philip J. Guo, Julia M. Markel, Xiong Zhang:
Learnersourcing at Scale to Overcome Expert Blind Spots for Introductory Programming: A Three-Year Deployment Study on the Python Tutor Website. L@S 2020: 301-304 - [c62]Amy Rae Fox, Philip J. Guo, Clemens Nylandsted Klokmose, Peter Dalsgaard, Arvind Satyanarayan, Haijun Xia, James D. Hollan:
Towards a dynamic multiscale personal information space: beyond application and document centered views of information. Programming 2020: 136-143 - [c61]Priyan Vaithilingam, Julia M. Markel, Philip J. Guo:
Papercode: Generating Paper-Based User Interfaces for Code Review, Annotation, and Teaching. UIST (Adjunct Volume) 2020: 77-79 - [c60]Sam Lau, Ian Drosos, Julia M. Markel, Philip J. Guo:
The Design Space of Computational Notebooks: An Analysis of 60 Systems in Academia and Industry. VL/HCC 2020: 1-11
2010 – 2019
- 2019
- [c59]Sean Kross, Philip J. Guo:
Practitioners Teaching Data Science in Industry and Academia: Expectations, Workflows, and Challenges. CHI 2019: 263 - [c58]Adam Kiezun, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst, Vijay Ganesh:
Theory and practice of string solvers (invited talk abstract). ISSTA 2019: 6-7 - [c57]Charles H. Chen, Philip J. Guo:
Improv: Teaching Programming at Scale via Live Coding. L@S 2019: 9:1-9:10 - [c56]Priyan Vaithilingam, Philip J. Guo:
Bespoke: Interactively Synthesizing Custom GUIs from Command-Line Applications By Demonstration. UIST 2019: 563-576 - [c55]Xiong Zhang, Philip J. Guo:
Mallard: Turn the Web into a Contextualized Prototyping Environment for Machine Learning. UIST 2019: 605-618 - [c54]Carrie J. Cai, Philip J. Guo:
Software Developers Learning Machine Learning: Motivations, Hurdles, and Desires. VL/HCC 2019: 25-34 - [c53]Sean Kross, Philip J. Guo:
End-User Programmers Repurposing End-User Programming Tools to Foster Diversity in Adult End-User Programming Education. VL/HCC 2019: 65-74 - 2018
- [c52]Philip J. Guo:
Non-Native English Speakers Learning Computer Programming: Barriers, Desires, and Design Opportunities. CHI 2018: 396 - [c51]April Yi Wang, Ryan Mitts, Philip J. Guo, Parmit K. Chilana:
Mismatch of Expectations: How Modern Learning Resources Fail Conversational Programmers. CHI 2018: 511 - [c50]Sean Kross, Philip J. Guo:
Students, systems, and interactions: synthesizing the first four years of learning@scale and charting the future. L@S 2018: 2:1-2:10 - [c49]Kandarp Khandwala, Philip J. Guo:
Codemotion: expanding the design space of learner interactions with computer programming tutorial videos. L@S 2018: 57:1-57:10 - [c48]Alok Mysore, Philip J. Guo:
Porta: Profiling Software Tutorials Using Operating-System-Wide Activity Tracing. UIST 2018: 201-212 - [c47]Xiong Zhang, Philip J. Guo:
Fusion: Opportunistic Web Prototyping with UI Mashups. UIST 2018: 951-962 - [c46]Kyle Thayer, Philip J. Guo, Katharina Reinecke:
The Impact of Culture on Learner Behavior in Visual Debuggers. VL/HCC 2018: 115-124 - 2017
- [j12]Philip J. Guo:
How adults ages 60+ are learning to code. Commun. ACM 60(8): 10-11 (2017) - [j11]Philip J. Guo:
Building tools to help students learn to program. Commun. ACM 60(12): 8-9 (2017) - [c45]Jeremy Warner, Philip J. Guo:
CodePilot: Scaffolding End-to-End Collaborative Software Development for Novice Programmers. CHI 2017: 1136-1141 - [c44]Philip J. Guo:
Older Adults Learning Computer Programming: Motivations, Frustrations, and Design Opportunities. CHI 2017: 7070-7083 - [c43]Jeremy Warner, Philip J. Guo:
Hack.edu: Examining How College Hackathons Are Perceived By Student Attendees and Non-Attendees. ICER 2017: 254-262 - [c42]Xiong Zhang, Philip J. Guo:
DS.js: Turn Any Webpage into an Example-Centric Live Programming Environment for Learning Data Science. UIST 2017: 691-702 - [c41]Alok Mysore, Philip J. Guo:
Torta: Generating Mixed-Media GUI and Command-Line App Tutorials Using Operating-System-Wide Activity Tracing. UIST 2017: 703-714 - [c40]Hyeonsu B. Kang, Philip J. Guo:
Omnicode: A Novice-Oriented Live Programming Environment with Always-On Run-Time Value Visualizations. UIST 2017: 737-745 - [c39]Ian Drosos, Philip J. Guo, Chris Parnin:
HappyFace: Identifying and predicting frustrating obstacles for learning programming at scale. VL/HCC 2017: 171-179 - 2016
- [c38]Parmit K. Chilana, Rishabh Singh, Philip J. Guo:
Understanding Conversational Programmers: A Perspective from the Software Industry. CHI 2016: 1462-1472 - [c37]Denae Ford, Justin Smith, Philip J. Guo, Chris Parnin:
Paradise unplugged: identifying barriers for female participation on stack overflow. SIGSOFT FSE 2016: 846-857 - [p1]Philip J. Guo:
Parse that data! Practical tips for preparing your raw data for analysis. Perspectives on Data Science for Software Engineering 2016: 169-173 - 2015
- [j10]Elena L. Glassman, Jeremy Scott, Rishabh Singh, Philip J. Guo, Robert C. Miller:
OverCode: Visualizing Variation in Student Solutions to Programming Problems at Scale. ACM Trans. Comput. Hum. Interact. 22(2): 7:1-7:35 (2015) - [c36]Carrie J. Cai, Philip J. Guo, James R. Glass, Robert C. Miller:
Wait-Learning: Leveraging Wait Time for Second Language Education. CHI 2015: 3701-3710 - [c35]Jeremy Warner, John Doorenbos, Bradley Miller, Philip J. Guo:
How High School, College, and Online Students Differentially Engage with an Interactive Digital Textbook. EDM 2015: 528-531 - [c34]Quanzeng You, Jianbo Yuan, Jiaqi Wang, Philip J. Guo, Jiebo Luo:
Snap n' shop: Visual search-based mobile shopping made a breeze by machine and crowd intelligence. ICSC 2015: 173-180 - [c33]Philip J. Guo:
Codeopticon: Real-Time, One-To-Many Human Tutoring for Computer Programming. UIST 2015: 599-608 - [c32]Mitchell L. Gordon, Philip J. Guo:
Codepourri: Creating visual coding tutorials using a volunteer crowd of learners. VL/HCC 2015: 13-21 - [c31]Philip J. Guo, Jeffery White, Renan Zanelatto:
Codechella: Multi-user program visualizations for real-time tutoring and collaborative learning. VL/HCC 2015: 79-87 - [c30]Joyce Zhu, Jeremy Warner, Mitchell L. Gordon, Jeffery White, Renan Zanelatto, Philip J. Guo:
Toward a domain-specific visual discussion forum for learning computer programming: An empirical study of a popular MOOC forum. VL/HCC 2015: 101-109 - [c29]Parmit K. Chilana, Celena Alcock, Shruti Dembla, Anson Ho, Ada Hurst, Brett Armstrong, Philip J. Guo:
Perceptions of non-CS majors in intro programming: The rise of the conversational programmer. VL/HCC 2015: 251-259 - 2014
- [j9]Philip J. Guo:
Clarifying human-computer interaction. Commun. ACM 57(2): 10-11 (2014) - [j8]Mark Guzdial, Philip J. Guo:
The difficulty of teaching programming languages, and the benefits of hands-on learning. Commun. ACM 57(7): 10-11 (2014) - [j7]Philip J. Guo:
Refining students' coding and reviewing skills. Commun. ACM 57(9): 10-11 (2014) - [c28]Carrie J. Cai, Philip J. Guo, James R. Glass, Robert C. Miller:
Wait-learning: leveraging conversational dead time for second language education. CHI Extended Abstracts 2014: 2239-2244 - [c27]Juho Kim, Phu Tran Nguyen, Sarah A. Weir, Philip J. Guo, Robert C. Miller, Krzysztof Z. Gajos:
Crowdsourcing step-by-step information extraction to enhance existing how-to videos. CHI 2014: 4017-4026 - [c26]Philip J. Guo, Katharina Reinecke:
Demographic differences in how students navigate through MOOCs. L@S 2014: 21-30 - [c25]Juho Kim, Philip J. Guo, Daniel T. Seaton, Piotr Mitros, Krzysztof Z. Gajos, Robert C. Miller:
Understanding in-video dropouts and interaction peaks inonline lecture videos. L@S 2014: 31-40 - [c24]Philip J. Guo, Juho Kim, Rob Rubin:
How video production affects student engagement: an empirical study of MOOC videos. L@S 2014: 41-50 - [c23]Anvisha H. Pai, Philip J. Guo, Robert C. Miller:
Modeling programming knowledge for mentoring at scale. L@S 2014: 181-182 - [c22]Elena L. Glassman, Jeremy Scott, Rishabh Singh, Philip J. Guo, Robert C. Miller:
OverCode: visualizing variation in student solutions to programming problems at scale. UIST (Adjunct Volume) 2014: 129-130 - [c21]Juho Kim, Philip J. Guo, Carrie J. Cai, Shang-Wen (Daniel) Li, Krzysztof Z. Gajos, Robert C. Miller:
Data-driven interaction techniques for improving navigation of educational videos. UIST 2014: 563-572 - [c20]Jeremy Scott, Philip J. Guo, Randall Davis:
A direct manipulation language for explaining algorithms. VL/HCC 2014: 45-48 - 2013
- [j6]Philip J. Guo:
Teaching programming the way it works outside the classroom. Commun. ACM 56(8): 10-11 (2013) - [j5]Philip J. Guo:
Helping scientists, engineers to work up to 100 times faster. Commun. ACM 56(10): 12-13 (2013) - [c19]Philip J. Guo:
Online python tutor: embeddable web-based program visualization for cs education. SIGCSE 2013: 579-584 - 2012
- [b1]Philip J. Guo:
Software tools to facilitate research programming. Stanford University, USA, 2012 - [j4]Philip J. Guo:
CDE: A Tool for Creating Portable Experimental Software Packages. Comput. Sci. Eng. 14(4): 32-35 (2012) - [j3]Adam Kiezun, Vijay Ganesh, Shay Artzi, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst:
HAMPI: A solver for word equations over strings, regular expressions, and context-free grammars. ACM Trans. Softw. Eng. Methodol. 21(4): 25:1-25:28 (2012) - [c18]Thomas Zimmermann, Nachiappan Nagappan, Philip J. Guo, Brendan Murphy:
Characterizing and predicting which bugs get reopened. ICSE 2012: 1074-1083 - [c17]Philip J. Guo, Margo I. Seltzer:
BURRITO: Wrapping Your Lab Notebook in Computational Infrastructure. TaPP 2012 - 2011
- [c16]Vijay Ganesh, Adam Kiezun, Shay Artzi, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst:
HAMPI: A String Solver for Testing, Analysis and Vulnerability Detection. CAV 2011: 1-19 - [c15]Philip J. Guo, Thomas Zimmermann, Nachiappan Nagappan, Brendan Murphy:
"Not my bug!" and other reasons for software bug report reassignments. CSCW 2011: 395-404 - [c14]Philip J. Guo:
Sloppy Python: using dynamic analysis to automatically add error tolerance to ad-hoc data processing scripts. WODA 2011: 35-40 - [c13]Philip J. Guo, Dawson R. Engler:
Using automatic persistent memoization to facilitate data analysis scripting. ISSTA 2011: 287-297 - [c12]Philip J. Guo:
CDE: Run Any Linux Application On-Demand Without Installation. LISA 2011 - [c11]Philip J. Guo, Sean Kandel, Joseph M. Hellerstein, Jeffrey Heer:
Proactive wrangling: mixed-initiative end-user programming of data transformation scripts. UIST 2011: 65-74 - [c10]Philip J. Guo, Dawson R. Engler:
CDE: Using System Call Interposition to Automatically Create Portable Software Packages. USENIX ATC 2011 - 2010
- [c9]Philip J. Guo, Thomas Zimmermann, Nachiappan Nagappan, Brendan Murphy:
Characterizing and predicting which bugs get fixed: an empirical study of Microsoft Windows. ICSE (1) 2010: 495-504 - [c8]Philip J. Guo, Dawson R. Engler:
Towards Practical Incremental Recomputation for Scientists: An Implementation for the Python Language. TaPP 2010
2000 – 2009
- 2009
- [j2]Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira Dontcheva, Scott R. Klemmer:
Opportunistic Programming: Writing Code to Prototype, Ideate, and Discover. IEEE Softw. 26(5): 18-24 (2009) - [c7]Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira Dontcheva, Scott R. Klemmer:
Two studies of opportunistic programming: interleaving web foraging, learning, and writing code. CHI 2009: 1589-1598 - [c6]Adam Kiezun, Philip J. Guo, Karthick Jayaraman, Michael D. Ernst:
Automatic creation of SQL Injection and cross-site scripting attacks. ICSE 2009: 199-209 - [c5]Adam Kiezun, Vijay Ganesh, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst:
HAMPI: a solver for string constraints. ISSTA 2009: 105-116 - [c4]Philip J. Guo, Dawson R. Engler:
Linux Kernel Developer Responses to Static Analysis Bug Reports. USENIX ATC 2009 - 2008
- [c3]Joel Brandt, Philip J. Guo, Joel Lewenstein, Scott R. Klemmer:
Opportunistic programming: how rapid ideation and prototyping occur in practice. WEUSE@ICSE 2008: 1-5 - 2007
- [j1]Michael D. Ernst, Jeff H. Perkins, Philip J. Guo, Stephen McCamant, Carlos Pacheco, Matthew S. Tschantz, Chen Xiao:
The Daikon system for dynamic detection of likely invariants. Sci. Comput. Program. 69(1-3): 35-45 (2007) - 2006
- [c2]Brian Demsky, Michael D. Ernst, Philip J. Guo, Stephen McCamant, Jeff H. Perkins, Martin C. Rinard:
Inference and enforcement of data structure consistency specifications. ISSTA 2006: 233-244 - [c1]Philip J. Guo, Jeff H. Perkins, Stephen McCamant, Michael D. Ernst:
Dynamic inference of abstract types. ISSTA 2006: 255-265
Coauthor Index
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