Contact Information
2116 Siebel Center
201 N Goodwin
M/C 258
Urbana, IL 61801
Research Areas
Additional Campus Affiliations
Donald Biggar Willett Professor, Siebel School of Computing and Data Science
Donald Biggar Willett Faculty Scholar, Siebel School of Computing and Data Science
Professor, Siebel School of Computing and Data Science
Professor, Statistics
Professor, School of Information Sciences
Professor, Carl R. Woese Institute for Genomic Biology
Recent Publications
Alvarez, D. E., & Zhai, C. X. (2025). TINK: Text Information Navigation Kit. In SIGIR 2025 - Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 4056-4060). (SIGIR 2025 - Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval). Association for Computing Machinery. https://doi.org/10.1145/3726302.3730141
Balog, K., Bernard, N., Zerhoudi, S., & Zhai, C. X. (2025). Theory and Toolkits for User Simulation in the Era of Generative AI: User Modeling, Synthetic Data Generation, and System Evaluation. In SIGIR 2025 - Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 4138-4141). (SIGIR 2025 - Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval). Association for Computing Machinery. https://doi.org/10.1145/3726302.3731697
Chan, M. P. S., Jung, H., Morales, A., Zhang, A., O'Keefe, D., Joseph, S., Hron, A., Davis, J., Terry, T., Peterson, T., Herrman, C., Phillips, M., Osborne, J., Mcbride, K. G., Hensley, M., Todorov, A., Morrissette, A., Watson, G., Knox, E., ... Albarracin, D. (2025). Living health-promotion campaigns for communities in the United States: Decentralized content extraction and sharing through AI. PNAS Nexus, 4(6), Article pgaf171. https://doi.org/10.1093/pnasnexus/pgaf171
Li, J., Han, R., Zeng, J., Sun, D., Sun, C., Tong, H., Zhai, C., Szymanski, B. K., & Abdelzaher, T. (2025). Learning to Slice: Self-Supervised Interpretable Hierarchical Representation Learning with Graph Auto-Encoder Tree. In KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 1388-1399). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. 2). Association for Computing Machinery. https://doi.org/10.1145/3711896.3737023
Liu, J., Huang, Z., Liu, Q., Ma, Z., Zhai, C., & Chen, E. (2025). Knowledge-Centered Dual-Process Reasoning for Math Word Problems With Large Language Models. IEEE Transactions on Knowledge and Data Engineering, 37(6), 3457-3471. https://doi.org/10.1109/TKDE.2025.3556367