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Jiqun Liu

Jiqun Liu

Jiqun Liu.

Assistant Professor

Email: jiqunliu@ou.edu
Office: Bizzell Library 118B
Campus: Norman


Dr. Jiqun Liu is an Assistant Professor of Data Science and Affiliated Assistant Professor of Psychology at the University of Oklahoma (OU). He holds a PhD in Information Science from Rutgers iSchool. He currently works with students from diverse backgrounds in his Human-Computer Interaction and Recommendation (HCIR) Lab.

His research focuses on the intersection of human-centered data science, interactive information seeking/retrieval, and cognitive psychology, and seeks to apply the knowledge learned about people interacting with information in adaptive recommendation and debiasing, user education and intelligent nudging. His recent projects focus on: 1) Psychology-Informed Intelligent Information Systems: investigating the impacts of users’ cognitive states and preferences on their decision-making and evaluations of information system performances, with the ultimate goal of making intelligent systems more sensitive to diverse needs, values and biases; 2) Bias-aware Adaptive Recommendations and Human-centered Fairness Evaluation: understanding user biases and bounded rationality that affect and contextualize human-information interaction and leveraging the knowledge about biases on both user and system sides in developing and evaluating fair, sustainable, and ethical system recommendations. Our work is possible thanks to National Science Foundation, Data Institute for Societal Challenges, and OU VPRP.

 


Courses Commonly Taught:   

  • LIS 4/5213 Social Informatics
  • LIS 4/5673 Intro to Information Visualization
  • LIS 5053 Informaiton Seeking and Use
  • LIS 4/5970 Information Retrieval and Text Mining

For a current listing of courses please visit: https://classnav.ou.edu/


Research Areas:

  • Human-centered data science.
  • Human-AI interaction and collaboration.
  • Bounded rationality.
  • Intelligent information retrieval and recommendation.
  • Fairness, diversity, and ethics in computing.
  • Psychology-informed user modeling.