CUTE Lab
Compute Technology for Experience Lab
The CUTE Lab (Compute Technology for Experience Lab) is a research lab in the Computer Science Department at William & Mary, directed by Dr. Yixuan (Janice) Zhang. We focus on the intersection of Human-Computer Interaction (HCI), Artificial Intelligence, and social computing to design, build, and evaluate interactive systems that enhance human experiences and well-being.
Hiring
CUTE Lab is actively seeking motivated Ph.D. students and research interns interested in HCI, AI/LLM applications, education technology, and mental health. Please email Dr. Zhang with your CV and research interests.
Research Topics
AI in Education
We explore how Large Language Models (LLMs) and AI systems can enhance learning experiences, from collaborative mathematical problem-solving to peer programming. We study ethical considerations and develop guidelines for integrating AI in educational settings.
AI for Mental Health & Well-being
We investigate how conversational AI can support mental health needs, studying emotional intelligence in AI systems and designing interventions that promote psychological well-being. Our work includes supporting vulnerable populations including older adults and women.
Trust in Technology
We study how trust and distrust emerge, transform, and collapse in human-technology relationships. Our research examines trust in AI systems, LLMs, and digital platforms, developing frameworks to understand and improve how people interact with and rely on technology.
LLM-based Multi-Agent Systems
We design and evaluate LLM-powered agent systems for collaborative decision-making and teamwork. Our MetaAgents framework explores how AI agents can work together and with humans to solve complex problems.
Sponsors
National Science Foundation
Microsoft Research
Commonwealth Cyber Initiative
Lab News
- [Jan 2026] Two full papers on AI peer learning in STEM education and AI in mental health have been accepted by ACM CHI'26!
- [Aug 2025] Received a three-year NSF grant to examine how to enhance AI literacy and resilience through intergenerational digital storytelling among older adults!
- [Apr 2025] Received a grant from COVA CCI (Commonwealth Cyber Initiative) to examine integrated security and privacy solutions for multi-modal AI.
- [Mar 2025] Received SEED Funding from William & Mary to explore K-12 teachers' capacity to integrate AI into Virginia Disciplinary Standards of Learning.
- [Jan 2025] Received a grant from The General Assembly of Virginia to design an interactive AI-enabled learning system for Alzheimer's Disease awareness and care.
- [Dec 2024] Our paper "MetaAgents: Large Language Model Based Agents for Decision-Making on Teaming" got accepted by CSCW'25 (Bergen, Norway)!
- [Aug 2024] Received a 3-year NSF RITEL grant (~$900,000) to develop LLM-powered systems for fostering mathematical modeling competencies through collaborative learning!
- [May 2024] Three papers focused on LLM × HCI got accepted by ICML! Topics include trust in LLM, Emotions in Generative AI, and competition dynamics of LLM-based agents.
- [Apr 2024] Dr. Zhang received the 2024-25 W&M FRC Faculty Research Grant for research on the ethics of Generative AI and LLMs in CS education.
- [Apr 2024] Congrats to Wenhan Lyu and Yimeng Wang (1st year PhD students) for their paper "Evaluating the Effectiveness of LLMs in Introductory Computer Science Education" accepted at L@S '24!
- [Jan 2024] Our paper "Profiling the Dynamics of Trust & Distrust in Social Media" was accepted to CHI'24!
- [Sept 2023] Awarded grants from Microsoft Research (emotional intelligence + LLMs) and The Society of 1918 (conversational AI for mental health).
- [Apr 2023] Our CHI'23 paper "What Do We Mean When We Talk about Trust in Social Media?" won a Best Paper Award! 🏆
- [Apr 2023] Our CHI'23 paper "Synthetic Lies: Understanding AI-Generated Misinformation" received a Best Paper Honorable Mention! 🏅
- [Aug 2022] Dr. Zhang was named a "Rising Star in EECS" 2022!