James Caverlee

Educational Background

Ph.D., Computer Science, Georgia Institute of Technology – 2007
M.S., Computer Science, Stanford University – 2001
M.S., Engineering-Economic Systems & Operations Research, Stanford University – 2000
B.A., Economics magna cum laude, Duke University – 1996

- Recommender systems
- Large language models
- Data mining
- Trustworthy machine learning
- Information retrieval

Association of Former Students Distinguished Achievement Award in Teaching (College Level) – 2023-2024
Special Interest Group on Information Retrieval (SIGIR) Test of Time Award Honorable Mention – 2022
Conference on Information and Knowledge Management (CIKM) Test of Time Award – 2020
National Science Foundation CAREER Award – 2012
Air Force Office of Scientific Research (AFOSR) Young Investigator Award – 2012
Montague-CTE (Center for Teaching Excellence) Scholar for excellence in undergraduate teaching – 2011-2012
Defense Advanced Research Projects Agency (DARPA) Young Faculty Award – 2010

Maria Teleki, Anna Seo Gyeong Choi, Anne Duray, Haoran Liu, Junyan Zhang, Xiangjue Dong, Dilma Da Silva, Allison Koenecke, James Caverlee. 2026. “The Due Process Deficit: Auditing AI Governance in US Higher Education.” ACM Conference on Fairness, Accountability, and Transparency (FAccT).
Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H Chi, James Caverlee, Julian McAuley, Derek Cheng. 2026. “How to Train Data-Efficient LLMs.” The International Conference on Learning Representations (ICLR).
Xiangjue Dong, Cong Wang, Maria Teleki, Millennium Bismay, James Caverlee. 2026. “CHOIR: Collaborative Harmonization fOr Inference Robustness.” Annual Meeting of the Association for Computational Linguistics (ACL).
Chengkai Liu, Yangtian Zhang, Jianling Wang, Rex Ying, James Caverlee. 2025. “Flow Matching for Collaborative Filtering.” ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).
Jinhao Pan, James Caverlee, Ziwei Zhu. 2025. “Combating Heterogeneous Model Biases in Recommendations via Boosting.” ACM International Conference on Web Search and Data Mining (WSDM).