Qiaozhu Mei
Professor, School of Information
Studies information retrieval, text mining and social network analysis, with applications to biomedical informatics.
Qiaozhu Mei's lab at Michigan works on graph mining & networks, recommendation, search & web and medical image analysis. 30 papers since 2023, 16 at top venues, mostly KDD and WWW. Applications close .
At a glance
- papers, 2023–2026
- 8/ year
- at T1 venues
- 53%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 4 papers2026 · T1 2 · collecting
- 6 papers2025 · T1 2
- 12 papers2024 · T1 8
- 8 papers2023 · T1 4
T1 venuesOtherVenues: KDD, WWW, ACL, ICWSM, NeurIPS
Research focuspaper titles that use each topic's words
- Graph mining & networks5 papers
- Medical image analysis2 papers
- Recommendation, search & web0 papers
- biomedical informatics0 papers
- social network0 papers
Paper list
From DBLP.
20264 papers
- KDD (T1)Distributional Alignment for Social Simulation with LLMs: A Mixture Modeling Approach (opens in a new tab)
- EACLExAnte: A Benchmark for Ex-Ante Inference in Large Language Models (opens in a new tab)
- WWW (T1)Pathways of Thoughts: Multi-Directional Thinking for Long-form Personalized Question Answering (opens in a new tab)
- Trans. Mach. Learn. Res.Through the Judge's Eyes: Inferred Thinking Traces Improve Reliability of LLM Raters (opens in a new tab)
20256 papers
- PAKDDLeveraging Group-Level Signals for Robust Many-Domain Generalization (opens in a new tab)
- KDD (T1)MapExplorer: New Content Generation from Low-Dimensional Visualizations (opens in a new tab)
- Findings of NAACLMASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows (opens in a new tab)
- NeurIPS (T1)Position: Towards Bidirectional Human-AI Alignment (opens in a new tab)
- J. Biomed. InformaticsSemNovel - A new approach to detecting semantic novelty of biomedical publications using embeddings of large language models (opens in a new tab)
- Trans. Mach. Learn. Res.Why is constrained neural language generation particularly challenging? (opens in a new tab)
202412 papers
- ACM Trans. WebAdoption of Recurrent Innovations: A Large-Scale Case Study on Mobile App Updates (opens in a new tab)
- ACL (T1)Bridging the Preference Gap between Retrievers and LLMs (opens in a new tab)
- Trans. Mach. Learn. Res.Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why? (opens in a new tab)
- ICWSMEmoji Promotes Developer Participation and Issue Resolution on GitHub (opens in a new tab)
- WWW (T1)Learning to Rewrite Prompts for Personalized Text Generation (opens in a new tab)
- WWW (T1)Low Mileage, High Fidelity: Evaluating Hypergraph Expansion Methods by Quantifying the Information Loss (opens in a new tab)
- AI OpenPM2.5 forecasting under distribution shift: A graph learning approach (opens in a new tab)
- ACL (T1)PRewrite: Prompt Rewriting with Reinforcement Learning (opens in a new tab)
- EMNLP (T1)Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach (opens in a new tab)
- KDD (T1)The First Workshop on AI Behavioral Science (opens in a new tab)
- SIGIR (T1)The Second Workshop on Large Language Models for Individuals, Groups, and Society (opens in a new tab)
- WSDM (T1)WSDM 2024 Workshop on Large Language Models for Individuals, Groups, and Society (opens in a new tab)
20238 papers
- NeurIPS (T1)A Metadata-Driven Approach to Understand Graph Neural Networks (opens in a new tab)
- WWW (T1)A Prompt Log Analysis of Text-to-Image Generation Systems (opens in a new tab)
- Trans. Mach. Learn. Res.Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (opens in a new tab)
- ICLR (T1)How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules (opens in a new tab)
- Trans. Mach. Learn. Res.Partition-Based Active Learning for Graph Neural Networks (opens in a new tab)
- Manag. Sci.Putting Teams into the Gig Economy: A Field Experiment at a Ride-Sharing Platform (opens in a new tab)
- ICWSMTeam Resilience under Shock: An Empirical Analysis of GitHub Repositories during Early COVID-19 Pandemic (opens in a new tab)
- KDD (T1)The 3rd Workshop on Graph Learning Benchmarks (GLB 2023) (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to MichiganFall 2027
Michigan CSE Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
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- Fee
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Not yet confirmed for this intake.
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Data
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