Scholar
Jiqun LIU
Google Scholar ID: SSkPeogAAAAJ
Associate Professor, Data Science, University of Oklahoma
Citations & Impact
Citations
839
H-index
18
i10-index
26
Publications
20
Co-authors
9
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Recent achievements include:
- - Serving as an Associate Editor for Information Processing and Management
- - Receiving support from National Science Foundation, Microsoft, Institute of Museum and Library Services, Data Institute for Societal Challenges, and OU VPRP
- - Project 'Guaging library needs for integrating Generative AI into children’s maker-based learning' funded by IMLS ($150,000)
- - Papers accepted at SIGIR2025, CHIIR2025, and ACM TOIS
- - Organizing IWILDS’25 - The 5th International Workshop on Investigating Learning during Web Search at ACM WSDM 2025
Research Experience
- Currently an Associate Professor, Data Science/SLIS, and Affiliated Faculty, Psychology at the University of Oklahoma (OU). Also an affiliated faculty member at the Data Institute for Societal Challenges. Works with students at the Human-Computer Interaction and Recommendation (HCIR) Lab at OU. Serves as Associate Editor for Information Processing and Management (IP&M) and ACM Transactions on Information Systems (ACM TOIS).
Education
- PhD in Information Science from Rutgers iSchool
Background
- Research interests include Large Language Model (LLM), Information Retrieval (IR), and Cognitive Psychology. Focuses on applying the knowledge learned about boundedly rational users interacting with information in conversational information retrieval and generation, proactive recommendation, and intelligent nudging. Recent projects focus on: Human-Centered Language Models and Intelligent Information Systems, Cognitive Impacts of Generative AI, and Machine Psychology.
Miscellany
- Actively looking for self-motivated research and visiting students to join his Human-Computer Interaction and Recommendation group at OU. Interested in students with backgrounds in Human-Computer Interaction, Interactive Information Retrieval/Recommendation, UX Design/Research, Cognitive Psychology or Experimental Economics, Machine Learning (ML), Natural Language Processing (NLP), Large Language Model (LLM) development and evaluation, LLMs-as-Judges, and Generative Artificial Intelligence (GenAI).
