HCIR Lab

Human-Computer Interaction & Recommendation Lab

The Human-Computer Interaction and Recommendation (HCIR) Lab at the University of Wisconsin–Milwaukee's School of Information Studies investigates how people interact with information, search and recommendation systems, and artificial intelligence. Our research brings together information retrieval, human-computer interaction, cognitive psychology, and machine learning to understand and support human information seeking, judgment, and decision-making.

A central focus of our work is understanding how human cognitive limitations, biases, and heuristics interact with the capabilities and limitations of AI systems. We develop behavioral models, evaluation methods, experimental platforms, and interventions to make generative and agentic AI systems more reliable, equitable, and supportive of human judgment.

Our research covers human-centered AI evaluation, conversational and generative information retrieval, cognitive vulnerability and digital resilience, AI-assisted decision-making, and responsible personalization. We combine computational modeling and machine learning with controlled experiments, human evaluation, and participatory research methods.

Founded in 2020, the HCIR Lab is directed by Dr. Jiqun Liu, Associate Professor specializing in AI and Data Science in the School of Information Studies at the University of Wisconsin–Milwaukee. The lab was originally established at the University of Oklahoma and transitioned to UWM in 2026.

Lab News

2026

  • October 2026 – Communications of the ACM: Our article “Bounded Minds, Generative Machines: Envisioning Conversational AI that Works with Human Heuristics and Reduces Bias Risk” was published in Communications of the ACM.
  • 2026 – NeurIPS: Our paper “Stability Regimes for Framing-Sensitive Fine-Tuning in Language Models” (with Victor De Lima and Grace Hui Yang) was accepted to NeurIPS 2026.
  • September 16, 2026 – UWM News Feature: UWM’s School of Information Studies featured Dr. Liu’s FOX6 interview on AI regulation and legislative guardrails.
  • September 14, 2026 – FOX6 Milwaukee Interview: Dr. Jiqun Liu appeared on FOX6 Milwaukee to discuss whether artificial intelligence needs legislative guardrails and the role of regulation in responsible AI development.
  • August 2026 – HCIR Lab Transition: Dr. Jiqun Liu joined the School of Information Studies at the University of Wisconsin–Milwaukee as a tenured Associate Professor through the AI and Data Science cluster hiring initiative. The HCIR Lab’s research program continues at UWM, building on previous research and collaborations at OU.
  • PhD student Ziyang Xu received ICAST Graduate Student Researcher Award for his research project “Evaluating and mitigating cognitive biases in large language models: A comparative study against human baselines” under Dr. Liu’s supervision. Congratulations!
  • Excited to share that our open-source research platform ECHO is covered by OU News! Read the story
  • Graduate Student Nischal Dinesh will join I-CCEW Software Business Accelerator at OU as a Software Developer Intern. Congratulations!
  • PhD Candidate Mahdieh (Maddy) Nazari received Graduate College Bullard Dissertation Completion Fellowship. Congratulations!
  • New Grant: DFCAS Collaborative Research Fellowship award: “Data Science for Public Health: Designing and Evaluating LLM-based Conversational AI for Intimate Partner Violence Prevention”. $25,000, PI: Dr. Yu Lu, Health Sciences; co-PI: Dr. Jiqun Liu.
  • New Grant: DISC Nexus Seed Funding: “AI-enabled Time-series Modeling of Daily Functional Organization to Support Early ADRD Care”. $25,000. PI: Dr. Ziming Liu (CS). co-PIs: Dr. Jiqun Liu, Dr. Yi Wu (CS), Dr. Tara Kalinedinst (HSC), Dr. Clarie Nouh (HSC).
  • We are excited to release ECHO, an open, low-code research platform for reproducible evaluation of conversational AI and Web search! ECHO enables researchers and students across IR and HCI, social sciences, and humanities to rapidly design and run end-to-end user studies, combining chat, search, surveys, and fine-grained interaction logging, with little to no coding. An intro tutorial video is available here.

2025

  • PhD candidate Ben Wang has successfully defended his dissertation titled “LLM-based Long-Term Life Task Planning to Reduce Human Uncertainty”. He is now working as an Applied Scientist at Amazon. Congratulations!
  • New Grant: Institute of Museum and Library Services (IMLS) NLG award: “Gauging Library Needs for Integrating Generative AI into Children’s Maker-based Learning”. ($150,000, PI: Dr. Jiqun Liu, co-PI: Dr. Yong Ju Jung).
  • PhD student Maddy Nazari passed her General Exam. Congratulations!
  • Our paper “Re-rankers are effective reference judgment predictors” (with Chuan Meng, Jiqun Liu, Mohammad Aliannejadi, Fengran Mo, and Maarten de Rijke) accepted to LLM4EVAL workshop at ACM SIGIR 2025!
  • Our project “Syllabi and Activities for AI-Assisted Maker Education: Design and Evaluation” received a funding award of $9,964 from OU DISC Summer AI Project Seed Funding program.
  • PhD Candidate Ben Wang passed his dissertation proposal (titled “LLM-based long-term task planning to reduce human uncertainty”) defense! Congratulations!
  • We (Drs. Anett Hoppe, Ran Yu, Jiqun Liu, and Nilavra Bhattacharya) co-organized the 5th International Workshop on Investigating learning during Web search (IWILDS 2025) at WSDM (March 14, 2025).
  • Our Special issue “AI in education: transforming teaching and learning” published at Information and Learning Sciences. (Guest editors: Drs. Dania Bilal, Jiangen He, Jiqun Liu).
  • New grant: Faculty Investment Program (FIP) Award: Making mistakes like humans: Detecting biased judgments of artificial intelligence, University of Oklahoma Office of the Vice President for Research and Partnerships ($15,000, PI: Jiqun Liu).

2024

  • Award: Jamshed Karimnazarov received Undergraduate Research Opportunities Program award. Congratulations!
  • Award: The research proposal titled “Enhancing AI Literacy through Maker-based Learning with Generative AI”, co-authored by Dr. Yong Ju Jung and Dr. Jiqun Liu, has received the Elfreda A. Chatman Research Award 2024 from ASIS&T SIG USE.
  • New grant: Project titled “Functional fixedness evaluation in human-large language model (LLM) interaction” received funding support from Microsoft Research ($20,000, PI: Jiqun Liu).

Join Us

We are actively looking for self-motivated students to join the lab and work on cutting-edge problems at the intersection of people, information, and AI. Research opportunities are available at both undergraduate and graduate levels. We are especially interested in students with backgrounds or interests in any of the following:

  • Human-Computer Interaction and Information Retrieval, including interactive search, conversational AI, and recommender systems;
  • Machine Learning and Natural Language Processing (NLP), including large language model (LLM) evaluation and auditing;
  • Behavioral experiments and user studies, drawing on cognitive psychology, behavioral economics, or quantitative and qualitative methods;
  • Human-centered and responsible AI, including AI literacy, fairness, and the societal impacts of AI.

If you are interested, please email jiqunliu@uwm.edu with your CV and a brief description of your previous research experiences and current research interests.