University of Toronto · Department of Computer Science
I build tools that help people think with AI, not hand thinking over to it.
Currently, I study AI attribution in programming education, reflexive qualitative analysis, and transparent research tools for literature review and knowledge work.
Selected work
Projects
Research systems and studies across human-AI collaboration, AI education, explainability, and mixed-initiative knowledge work.
AI literacy and academic integrity
Understanding AI Disclosure and Attribution in Educational Contexts
How should students disclose, explain, and learn from AI help instead of hiding it or treating it as magic?
Sensemaking and reflexivity
Mixed-Initiative and Responsible AI in Qualitative Analysis
AI support for qualitative researchers that helps them interpret, question, and document decisions.
Literature review tooling
AI-Infused Systematic Literature Review Assistant
A transparent review companion for searching, extracting, and tracing evidence across literature reviews.
AI learning skills
Improving Student-AI Interaction Through Pedagogical Prompting
Scenario-based instruction that teaches students to prompt AI as part of active learning.
Developer experience
Explainable and Trustworthy AI Coding Agent
Explanations for coding agents that help developers understand what changed and why.
Classroom AI deployment
Design and Evaluation of New Programming Tools for Novices using AI Coding Assistants
A large classroom study of how novice programmers actually use AI help when stakes are real.
Learning analytics
Investigating the Impact of Online Homework Reminders Using Randomized A/B Comparison
Field experiments on which course reminders students read and how those nudges affect behavior.