Kexin 'Bella' Yang
Kexin Yang

My research aims to leverage multi-modal analytics and design data-driven human-AI algorithmic systems for smart classrooms of the future, that

  1. respect stakeholders’ (teachers and students) boundaries, agency, and preferences,
  2. augment educators' abilities to distribute their limited attention to where it is needed the most,
  3. 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.

Publications

Educational Tool Design and Development

Computer-supported Collaborative Learning

Human-AI Interaction

Data Mining, Visualization and Simulation

Natural Language Processing

Social Computing and Crowdsourcing

Human-Centered Design Methods