1. Paper 'Math Education with LLMs' accepted to AIED'25.
2. Paper 'Human Creativity in the Age of LLMs' received Honorable Mention award at CHI'25.
3. Paper 'LLM Agents for Improving Engagement with Behavior Change Interventions' accepted to CSCW'25.
4. Paper 'Transparency Disclosures and Reliability Disclaimers for Learner-LLM Interactions' accepted to HCOMP'24.
5. Paper 'Supporting Self-Reflection at Scale with Large Language Models' accepted to Learning@Scale'24.
6. Presented 3 ongoing works at IC2S2 in Philadelphia.
7. 'Math Education with Large Language Models: Peril or Promise?' featured in the Microsoft 'New Future of Work' report for 2023.
Research Experience
1. Graduate Research Assistant, University of Toronto (September 2021 - Present): Designing LLM-based educational tools to enhance student comprehension, using reinforcement learning methods to personalize LLM experiences.
2. Research Intern, Microsoft Research (Summer 2023 & 2024): Investigated the potential of Large Language Models to augment human cognition, focusing on how they can be utilized to teach Mathematics.
Education
Degree: PhD; School: University of Toronto; Advisor: Dr. Ashton Anderson; Time: September 2021 - Present; Major: Computer Science.
Background
Research interests: Artificial Intelligence, Human-Computer Interaction, Computational Social Science. Background: Fourth-year PhD student in the Department of Computer Science at the University of Toronto, supervised by Dr. Ashton Anderson. Research focuses on developing algorithms and systems for social good, particularly in cognition, mental health, and education.