Additional Campus Affiliations
Professor, Computer Science
Professor, Coordinated Science Lab
Professor, Center for Digital Agriculture, National Center for Supercomputing Applications (NCSA)
Recent Publications
Jung, Y., Hockenmaier, J., & Golparvar-Fard, M. (2024). Transformer language model for mapping construction schedule activities to uniformat categories. Automation in Construction, 157, Article 105183. https://doi.org/10.1016/j.autcon.2023.105183
Wang, Q., Li, M., Chan, H. P., Huang, L., Hockenmaier, J., Chowdhary, G., & Ji, H. (2023). Multimedia Generative Script Learning for Task Planning. In Findings of the Association for Computational Linguistics, ACL 2023 (pp. 986-1006). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). Association for Computational Linguistics (ACL).
Amer, F., Hockenmaier, J., & Golparvar-Fard, M. (2022). Learning and critiquing pairwise activity relationships for schedule quality control via deep learning-based natural language processing. Automation in Construction, 134, Article 104036. https://doi.org/10.1016/j.autcon.2021.104036
Ren, L., Sun, C., Ji, H., & Hockenmaier, J. (2021). HySPA: Hybrid Span Generation for Scalable Text-to-Graph Extraction. In C. Zong, F. Xia, W. Li, & R. Navigli (Eds.), Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 4066-4078). (Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021). Association for Computational Linguistics (ACL).
Xiong, J., Haldar, R., Hockenmaier, J. C., & Wu, L. (2021). Multi-perspective, multi-task neural network model for matching text to program code. (U.S. Patent No. 11132512).