
Harry Ye叶 润龙
I'm a 1st year PhD student in Dynamic Graphics Project (DGP) Lab at the University of Toronto, advised by Prof. Michael Liut and Prof. Carolina Nobre. My research focuses on developing responsible and explainable AI systems, with a particular emphasis on applications in education and research methodologies.
Previously, I had the privilege of collaborating with Profs. Tovi Grossman, Michelle Craig, and Tingting Zhu.
Research
Projects
Current Projects
Ongoing research initiatives exploring the frontiers of HCI and AI
Design, Implementation, and Evaluation of Explainable and Trustworthy Coding Agent
Developing CopilotLens, a framework that transforms AI code generation from opaque suggestions into transparent, explainable interactions. By providing post-hoc summaries and on-demand explanations, we aim to foster more trustworthy human-AI collaboration in software development.
Publications

Beyond Autocomplete: Designing CopilotLens Towards Transparent and Explainable AI Coding Agents
Ye, R., Zhang, Z., Almazroua, B., Liut, M.
Design, Implementation, and Evaluation of a Reflexive Qualitative Analysis Tool
ScholarMate is an interactive system that augments qualitative research by blending AI assistance with human oversight. The tool enables researchers to work on a visual canvas, organizing and connecting text snippets while maintaining critical engagement and control over the analysis process.
Publications

ScholarMate: A Mixed-Initiative Tool for Qualitative Knowledge Work and Information Sensemaking
Ye, R., Lee, P. Y. K., Varona, M., Huang, O., Nobre, C.
Design, Implementation, and Evaluation of a Novice Systematic Review Assistant
ARC is an open-source tool designed to streamline systematic literature reviews in computing research. Developed through user-centered design with 20 experienced researchers, it automates literature searches, data extraction, and reference tracking while maintaining transparency and reproducibility standards.
Publications

ARC: Automated Review Companion Leveraging User-Centered Design for Systematic Literature Reviews
Ye, R., Sibia, N., Zavaleta Bernuy, A., Zhu, T., Nobre, C., Liut, M.
Improving Student-AI Interaction Through Pedagogical Prompting
This work introduces pedagogical prompting, a theoretically-grounded concept to teach students how to effectively prompt LLMs to improve their learning. An interactive system was designed and developed with scenario-based instruction to train these skills.
Publications

Improving Student-AI Interaction Through Pedagogical Prompting: An Example in Computer Science Education
Xiao, R., Hou, X.*, Ye, R.*, Kazemitabaar, M.*, Diana, N., Liut, M., Stamper, J.
*contributed equally
TreeReader: Enhancing Article Comprehension through Hierarchical Tree-based Visualization
TreeReader revolutionizes academic paper navigation by transforming linear documents into an interactive, hierarchical tree, allowing users to selectively expand and collapse sections and sub-sections on the tree base on user intension. This structure, combined with on-demand access to source text and contextual information, offers a more focused and efficient way to engage with complex scholarly literature beyond summarization.
Publications

TreeReader: A Hierarchical Academic Paper Reader Powered by Language Models
Zhang, Z., Chen, P., Du, F., Ye, R., Huang, O., Liut, M., Aspuru-Guzik, A.
Past Projects
Completed research that has contributed to the field
Design and Evaluation of New Programming Tools for Novices using AI Coding Assistants
CodeAid is an LLM-based AI programming assistant deployed in a university classroom of 700 students. Through analysis of 8,000 usages, student surveys, and educator feedback, we investigated how AI programming tools can balance educational value with practical support.
Publications

CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs
Kazemitabaar, M., Ye, R., Wang, X., Henley, A., Denny, P., Craig, M., Grossman, T.
Investigating the Impact of Online Homework Reminders Using Randomized A/B Comparison
OnTrack investigates how email reminders affect student learning behaviors through randomized A/B testing. Using multi-armed bandit algorithms, we optimize intervention strategies to support student engagement while measuring behavioral impacts on academic performance.
Publications

Student Interaction with Instructor Emails in Introductory and Upper-Year Computing Courses
Zavaleta Bernuy, A., Ye, R., Sibia, N., Nalluri, R., Williams, J. J., Petersen, A., Smith, E., Simion, B., Liut, M.

Do Students Read Instructor Emails? A Case Study of Intervention Email Open Rates
Zavaleta Bernuy, A., Ye, R., Tran, E., Mandal, A., Shaikh, H., Simion, B., Petersen, A., Liut, M., Williams, J. J.

Behavioral Consequences of Reminder Emails on Students' Academic Performance: a Real-world Deployment
🏆 Best PaperYe, R., Chen, P., Mao, Y., Wang-Lin, A., Shaikh, H., Zavaleta Bernuy, A., Williams, J. J.
Awards & Recognition
Recognition for contributions to research
Best Paper
SIGITE • 2022
Recognition for student email intevention in educational systems.
Latest Updates
Recent milestones, publications, and research activities.
Paper Accepted at VL/HCC 2025
2025-10Our work on LLM-enabled Hierarchical Academic Paper Reader has been accepted for publication.
Paper Accepted at COLM 2025 Workshop
2025-10Our work on Explainable Coding Agent, has been accepted to the XLLM-Reason-Plan workshop.
Paper Accepted at CHIWORK 2025
2025-06Our work on a visual tool for qualitative knowledge work and information sensemaking has been accepted for publication.
Started PhD at University of Toronto
2024-09Joined the Dynamic Graphics Project Lab under the supervision of Prof. Michael Liut and Prof. Carolina Nobre.
Paper Accepted at CHI 2024
2024-03Our work on AI-assisted programming education has been accepted for publication.
Research Internship at Oracle
2024-06Completed year-long full-stack software development internship.
Get in Touch
Let's discuss research collaborations.
Let's Start a Conversation
Interested in research collaboration or have questions about my work? I'd be happy to connect with you.
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