Harry Ye headshot
PhD Student & HCI Researcher

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.

Human-AI CollaborationExplainable AIResponsible AIProgramming EducationMixed-Initiative SystemsResearch Tools

Research
Projects

My research focuses on Human-Computer Interaction (HCI) and developing innovative Human-Centered AI systems for educational technologies and research tools.

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.

Explainable AICode GenerationDeveloper ToolsTransparency

Publications

Beyond Autocomplete: Designing CopilotLens Towards Transparent and Explainable AI Coding Agents
Design, Implementation, and Evaluation of Explainable and Trustworthy Coding Agent

Beyond Autocomplete: Designing CopilotLens Towards Transparent and Explainable AI Coding Agents

XLLM-Reason-Plan @COLM 2025

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.

Qualitative ResearchMixed-Initiative SystemsKnowledge WorkInformation Visualization

Publications

ScholarMate: A Mixed-Initiative Tool for Qualitative Knowledge Work and Information Sensemaking
Design, Implementation, and Evaluation of a Reflexive Qualitative Analysis Tool

ScholarMate: A Mixed-Initiative Tool for Qualitative Knowledge Work and Information Sensemaking

CHIWORK 2025

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.

Systematic ReviewLiterature ReviewResearch ToolsUser-Centered Design

Publications

ARC: Automated Review Companion Leveraging User-Centered Design for Systematic Literature Reviews
Design, Implementation, and Evaluation of a Novice Systematic Review Assistant

ARC: Automated Review Companion Leveraging User-Centered Design for Systematic Literature Reviews

In Submission 2024

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.

Human-Computer InteractionArtificial IntelligenceComputer Science EducationPedagogical Prompting

Publications

Improving Student-AI Interaction Through Pedagogical Prompting: An Example in Computer Science Education
Improving Student-AI Interaction Through Pedagogical Prompting

Improving Student-AI Interaction Through Pedagogical Prompting: An Example in Computer Science Education

In Submission 2025

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.

Code ComprehensionVisualizationDeveloper ToolsSoftware EngineeringAST

Publications

TreeReader: A Hierarchical Academic Paper Reader Powered by Language Models
TreeReader: Enhancing Article Comprehension through Hierarchical Tree-based Visualization

TreeReader: A Hierarchical Academic Paper Reader Powered by Language Models

VL/HCC 2025

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

Past ProjectMentored by Majeed Kazemitabaar

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.

Programming EducationLLMEducational AIStudent Support

Publications

CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs
Design and Evaluation of New Programming Tools for Novices using AI Coding Assistants

CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs

CHI 2024

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

Past ProjectMentored by Angela Zavaleta-Bernuy

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
Investigating the Impact of Online Homework Reminders Using Randomized A/B Comparison

Student Interaction with Instructor Emails in Introductory and Upper-Year Computing Courses

SIGCSE 2024

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
Investigating the Impact of Online Homework Reminders Using Randomized A/B Comparison

Do Students Read Instructor Emails? A Case Study of Intervention Email Open Rates

Koli Calling 2023

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
Investigating the Impact of Online Homework Reminders Using Randomized A/B Comparison

Behavioral Consequences of Reminder Emails on Students' Academic Performance: a Real-world Deployment

🏆 Best Paper
SIGITE 2022

Ye, 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

SIGITE2022

Recognition for student email intevention in educational systems.

Latest Updates

Recent milestones, publications, and research activities.

Paper Accepted at VL/HCC 2025

2025-10

Our work on LLM-enabled Hierarchical Academic Paper Reader has been accepted for publication.

Paper Accepted at COLM 2025 Workshop

2025-10

Our work on Explainable Coding Agent, has been accepted to the XLLM-Reason-Plan workshop.

Paper Accepted at CHIWORK 2025

2025-06

Our work on a visual tool for qualitative knowledge work and information sensemaking has been accepted for publication.

Started PhD at University of Toronto

2024-09

Joined the Dynamic Graphics Project Lab under the supervision of Prof. Michael Liut and Prof. Carolina Nobre.

Paper Accepted at CHI 2024

2024-03

Our work on AI-assisted programming education has been accepted for publication.

Research Internship at Oracle

2024-06

Completed 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.