My group studies, designs, and develops interactive Human-AI systems that empower data workers to discover insights and detect critical patterns in real-time data analysis, such as in-class students' learning behaviors. The systems we develop streamline the analytical process by reducing the effort and programming skills users need. We achieve this by employing AI techniques, such as LLMs, to identify and predict underlying data structures and representations, and by integrating human-centered design principles to ensure seamless interaction between humans and AI. Our goal is to make advanced real-time data analysis more accessible and efficient for everyone by simplifying complex computational processes.

I am looking for students to join me to design the future intelligent programming assistance. If you are interested in working with me, complete this form!

Bio

Yan Chen is an Assistant Professor of Computer Science at Virginia Tech (USA) where he directs the Programming with Intelligent Machines & Environments Lab (PRIME) PRIME Logo. Yan is active in the Human-Computer Interaction (HCI) research community. His research spans programming support tools, learning at scale, real-time data analysis, and CS education. His work has been published at top HCI conferences, including ACM CHI, UIST, and CSCW. He received the Best Short Paper award at VL/HCC 2020, the Best Paper at L@S 2024, and the Best Paper Honorable Mention Award at CHI 2023, and UIST 2022. Yan was a Postdoctoral Fellow at the University of Toronto (Canada). He received his Ph.D. degree from the University of Michigan (USA), and BS and MS degrees in Applied Math and Electrical & Computer Engieering from the University of Colorado, Boulder (USA).

Travel

News

(2024.10) One paper is accepted to ACM GROUP'25. Congrats to Tong.
(2024.9) One paper is accepted to SIGCSE'25. Congrats to Tong, Xiaohang, Sam, and Xi.
(2024.8) Welcome Adeline and Panayu to the Prime lab.
(2424.7) VizGroup is conditionally accepted to UIST'24. Congrats to Xiaohang, Sam, Kevin, and Xi!
(2024.4) CFlow received the Best Paper Award at L@S'24 🏆. Congrats to Ashley, Xiaohang!

Team


Adeline (Xinran) Li
PhD, VT CS (Fall'24-)
Panayu Keelawat
PhD, VT CS (Fall'24-)
Xiaohang Tang
PhD, VT CS (Fall'23-)
Rexime Abulikemu
PhD, VT CS (Fall'23-)
Tong Wu
PhD,VT CS (Fall'23-)
Ashley Zhang
PhD, Umich (Summer'22-)
Kevin Pu
PhD, UofT (Fall'21-)
David Barron
MS, VT. (Fall'24-)
Sam Wong
MS, UWash. (Summer'23-)
Susan He
BS, UVA CS (Summer'24-)
Bogdan Perlroth
BS, VT CS (Summer'24-)
Marcus Huynh
BS, VT CS (Summer'24-)
Xi Chen
BS, VT CS (Summer'23-)
Tejas Navada
BS, VT CS (Fall'23-)
You?
Join us!

Publications


Tong Wu, Xiaohang Tang, Sam Wong, Xi Chen, Cliff Shaffer, Yan Chen. The Impact of Group Discussion and Formation on Student Performance: An Experience Report in a Large CS1 Course. SIGCSE 2025

Xiaohang Tang, Sam Wong, Kevin Pu, Xi Chen, Yalong Yang, Yan Chen. VizGroup: An AI-Assisted Event-Driven System for Real-Time Collaborative Programming Learning Analytics. UIST 2024

Listen to a two-host podcast about VizGroup. The content is generated by NotebookLM, and verified by the authors.

Ashley Zhang, Xiaohang Tang, Steve Oney, Yan Chen. CFlow: Supporting Semantic Flow Analysis of Students' Code in Programming Problems at Scale. ACM Learning @ Scale 2024 (L@S) '24. (🏆 Best Paper)

Tianjia Wang, Daniel Vargas Diaz, Chris Brown, Yan Chen. Exploring the Role of AI Assistants in Computer Science Education: Methods, Implications, and Instructor Perspectives. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2023.

Kevin Pu, Jim Yang, Angel Yuan, Minyi Ma, Rui Dong, Xinyu Wang, Yan Chen, Tovi Grossman. DiLogics: Creating Web Automation Programs with Diverse Logics. ACM Symposium on User Interface Software and Technology (UIST), 2023.

Ashley Ge Zhang, Yan Chen, Steve Oney. RunEx: Augmenting Regular-Expression Code Search with Runtime Values IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2023.

Ashley Zhang, Yan Chen, Steve Oney. VizProg: Identifying Misunderstandings by Visualizing Students' Coding Progress. ACM Conference on Human Factors in Computing Systems (CHI), 2023. (🏅Best Paper Honorable Mention)

VizProg presents an innovative, real-time visualization system that meaningfully displays class-wide students' coding progress, making it simple for programming instructors to pinpoint issues and mistakes.

Thoughts: The challenge of delivering programming education at scale is exacerbated by factors such as real-time instruction, a large student population, novice learners, and the complexity of the material being taught. To enhance the classroom experience for students and simplify the task for instructors, how can we make programming education more engaging and manageable?

Kevin Pu, Rainey Fu, Rui Dong, Xinyu Wang, Yan Chen, Tovi Grossman. SemanticOn: Specifying Content-Based Semantic Conditions for Web Automation Programs. ACM Symposium on User Interface Software and Technology (UIST), 2022. (🏅Best Paper Honorable Mention)

SemanticOn enables users to specify visual and textual semantic conditions in web automation programs by natural language description and content highlighting.

Thoughts: SemanticOn only considers 1-1 mapping between user intents and UI actions. How can we support other kinds of mappings? How can we design PbD systems are more trustworthy?

April Wang*, Yan Chen*, John Joon Young Chung, Christopher Brooks, Steve Oney. PuzzleMe: Leveraging Peer Assessment for In-Class Programming Exercises. ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2021 (* == equal contribution).

To scale programming support in a large live classroom, PuzzleMe coordinates students to help each other by exchanging test cases and problem-solving approaches for coding exercises.

Karthik Mahadevan, Yan Chen, Maya Cakmak, Anthony Tang, Tovi Grossman. Mimic: In-Situ Recording and Re-Use of Demonstrations to Support Robot Teleoperation. ACM Symposium on User Interface Software and Technology (UIST), 2022.

Teleoperators can use Mimic to program robots by demonstration and reuse demonstrations in new context

Rui Dong, Zhicheng Huang, Ian Iong Lam, Yan Chen, Xinyu Wang. WebRobot: Web Robotic Process Automation using Interactive Programming-by-Demonstration. ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2022.
[ACM ]


Jiannan Li, Mauricio Sousa, Chu Li, Jessie Liu, Yan Chen, Ravin Balakrishnan, Tovi Grossman. ASTEROIDS: Exploring Swarms of Mini-Telepresence Robots for Physical Skill Demonstration. ACM Conference on Human Factors in Computing Systems (CHI), 2022.

Asteroids explores a new space of remote physical task learning via telepresence robots

Yan Chen, Walter S. Lasecki, Tao Dong. Towards Supporting Programming Education at Scale via Live Streaming. ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2020.

Explores the motivations/barriers/opportunities of live streaming programming as compared to pre-recorded video through interviews with 14 streamers & 12 viewers.

Thoughts: What can we do to enhance the learning experience in an online environment by adopting the in-person social features that a physical library has? What can be done to support different social needs in an online learning context in order to enhance learning outcomes?

Yan Chen, Tovi Grossman. Umitation: Retargeting UI Behavior Examples for Website Design. ACM Symposium on User Interface Software and Technology (UIST), 2021

Umitation enables web developers to perform "copy-and-paste" (retarget) interaction on web front-end UI behaviors with a trigger-object-response framework.

Yan Chen, Sang Won Lee, Steve Oney. CoCapture: Effectively Communicating UI Behaviors on Existing Websites by Demonstrating and Remixing. ACM Conference on Human Factors in Computing Systems (CHI), 2021.

CoCapture allows designers to create UI behavior mockups on existing web interfaces by demonstrating and remixing, and to accurately describe their requests to developers by referencing the resulting mockups using hypertext.

Yan Chen, Jaylin Herskovitz, Walter S. Lasecki, Steve Oney. A Hybrid Crowd-Machine Workflow for Program Synthesis. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2020.

Bashon introduces a crowdsourcing approach to help make program synthesis systems more robust, reliable, and trustworthy, and reduces the cost of downstream data collection for training a program synthesis system.

Yan Chen, Jaylin Herskovitz, Gabriel Matute, April Wang, Sang Won Lee, Walter S. Lasecki, Steve Oney. EdCode: Towards Personalized Support at Scale for Remote Assistance in CS Education. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2020. (🏆 Best Short Paper)

EdCode applies a semi-asychronous on-demand help seeking model in a learning setting, aiming towards provide more personalized support at scale.

Yan Chen, Maulishree Pandey, Jean Y. Song, Walter S. Lasecki, Steve Oney. Improving Crowd-Supported GUI Testing with Structural Guidance. ACM Conference on Human Factors in Computing Systems (CHI), 2020.

Two techniques, interactive event-flow graphs and GUI-level guidance, that guide GUI testers to discover more test cases and avoid duplicate test cases.

Yan Chen, Andrés Monroy-Hernández, Ian Wehrman, Steve Oney, Walter S. Lasecki, Rajan Vaish. Sifter: A Hybrid Workflow for Theme-based Video Curation at Scale. ACM Conference on Interactive Media Experiences (IMX), 2020.

Sifter improves the video curation process by combining automated techniques with a human-powered two-stage pipeline that browses, selects, and reaches an agreement.

Yan Chen, Sang Won Lee, Yin Xie, YiWei Yang, Walter Lasecki, and Steve Oney. Codeon: On-Demand Software Development Assistance. ACM Conference on Human Factors in Computing Systems (CHI), 2017.
[local pdf | full video | 30s preview | BibTeX ]

CodeOn enables effective task hand-offs between developers and remote helpers by allowing asynchronous responses to on-demand requests.

Sang Lee, Yan Chen, Noah Klugman, Sai R. Gouravajhala, Angela Chen, and Walter S. Lasecki. Exploring Coordination Models for Ad Hoc Programming Teams ACM Conference on Human Factors in Computing Systems Late Breaking Work (CHI), 2017.

Explore the types and causes of the coordination costs for transient software teams when using existing collaborative programming tools: a VCS and a shared editor.

Yan Chen, Steve Oney and Walter Lasecki. Towards Providing On-Demand Expert Support for Software Developers. ACM Conference on Human Factors in Computing Systems (CHI), 2016.
[pdf | ACM DL | 30s preview | talk | BibTeX ]

Two studies that present the opportunities and the design recommendations of on-demand remote support systems for developers.





Other Publications

Xiaohang Tang, Xi Chen, Sam Wong, Yan Chen. VizPI: A Real-Time Visualization Tool for Enhancing Peer Instruction in Large-Scale Programming Lectures. ACM Symposium on User Interface Software and Technology (UIST Poster), 2023.

Yan Chen, Jasmine Jones, and Steve Oney.
The New Future of Work  Microsoft Research 2020
Yan Chen
VL/HCC Graduate Consortium 2019
pdf  
Sang Lee, Yan Chen, and Walter S. Lasecki.
HCOMP WIP 2017
pdf  
Yan Chen, Steve Oney and Walter Lasecki.
Collective Intelligence 2016. Oral Presentation.
pdf ·  BibTeX
Esther Vasiete, Yan Chen, Ian Char, Tom Yeh, Vishal Patel, Larry Davis, and Rama Chellappa.
Mobile HCI Poster 2014
pdf ·  ACM DL
Vishal Patel, Tom Yeh, M Salem, Yangmuzi Zhang, Yan Chen, Rama Chellappa, Larry Davis.
IT Professional 2013
pdf ·  IEEE
Yan Chen, Harvey Segur
Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences.
pdf



Lab & School