In PersAI Lab, we research on human-centered data science, including recommender systems and personalized education problems. Specific themes of our research include:

• Recommender Systems
  • cross-domain recommender systems
  • multi-source and multi-objective recommender systems
  • community-based collaborative filtering
• Learning analytics and educational Data Mining
  • personalized student sequencing
  • student knowledge modeling
  • learning resource recommendations
  • learner behavior modeling and prediction
  • domain knowledge modeling in unstructured contexts

News:

• April 2021: We received NSF CAREER award for the project “CAREER: Time-Aware Multi-Objective Recommendation in Online Learning Environments”
• April 2021: Congrats Chunpai and Siqian for their paper accepted at EDM’2021 conference, titled “Learning from non-assessed resources: Deep multi-type knowledge tracing”
• April 2021: Congrats Miley and Siqian for their paper accepted at The AIED’2021 conference, titled “Temporal processes associating with procrastination dynamics”
• March 2021: Congrats Chunpai, Siqian, and Laura for their collaborative paper accepted at UMAP’2021 conference, titled “Knowledge tracing for complex problemsolving: Granular rank-based tensor factorization”
• January 2021: Congrats Miley and Siqian for their collaborative paper accepted at The Web’2021 conference, titled “Stimuli-Sensitive Hawkes Processes for Personalized Student Procrastination Modeling”
• December 2020: Congrats Miley and Siqian for their collaborative paper accepted at AAAI’2021 conference, titled “Relaxed clustered hawkes process for procrastination modeling in MOOCs”
• October 2020: Congrats Mehrdad for accepted paper at WI’2020 conference, titled “Sb-dnmf: A structure based discriminative non-negative matrix factorization model for detecting inefficient learning behaviors”
• September 2020: Our paper “TransCrossCF: Transition-based cross-domain collaborative filtering” was accepted in ICMLA 2020!
• August 2020: Congratulations to Dr. Mehrdad Mirzaei for successfully defending his dissertation on “Discriminative Factorization Models for Student Behavioral Pattern Detection and Classification”. He is the first PhD graduate of our lab!