
My research aims to leverage multi-modal analytics and design data-driven human-AI algorithmic systems for smart classrooms of the future, that
- respect stakeholders’ (teachers and students) boundaries, agency, and preferences,
- augment educators' abilities to distribute their limited attention to where it is needed the most,
- achieve effective, self-paced personalized learning that suit students’ individual needs.
I’ve also worked on and broadly interested in social computing (e.g., crowdsourcing), XR, robotics, NLP, and their application in education. I am well versed in qualitative, quantitative, and human-centered design research methods, including surveys, interviews, prototyping, focus groups, participatory design, usability testing, think-aloud protocol, field testing, AB testing, log-data analysis, statistical modeling and experiment design. I published first-authored papers in HCI and education venues including CHI, CSCW, AIED, EDM and EC-TEL.