Jie Cao

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Jie Cao

Assistant Professor

Email: jie.cao@ou.edu
Office: Devon Energy Hall 210-B
Website: nlp.cs.ou.edu

Education

PhD, Computer Science
University of Utah

MS, Computer Science
Huazhong University of Science and Technology

BS, Information Security
Huazhong University of Science and Technology

Research Focus

Natural Language Processing
Machine Learning
Dialogue and Discourse
Structured Prediction
Large Language Models and Agentic Systems
Trustworthy AI for Education, Healthcare, Science

Experience

Assistant Professor, School of Computer Science, University of Oklahoma, 2024 - present
Postdoctoral Research Associate, NSF AI Institute for Student-AI Teaming (iSAT) at the University of Colorado Boulder, 2022-2024
Research Scientist Interns at WeChat AI, Amazon, Software Engineer at Baidu, Alibaba, Sohu

About

Dr. Jie Cao is an assistant professor at the School of Computer Science at the Gallogly College of Engineering, University of Oklahoma. Before joining OU, he was a post-doctoral researcher at the NSF AI Institute for Student-AI Teaming (iSAT) at the University of Colorado Boulder. He obtained his Ph.D. from the Kahlert School of Computing at the University of Utah.

Dr. Cao's research primarily focuses on natural language processing(NLP), machine learning, and agentic systems. His research aims to facilitate modularized AI systems tailored for future large-scale AI projects that demand increasing collaboration and adaptability, which covers fundamental research on formal language representation, neuro-symbolic methods, latent discrete structures, multimodal/multiagent modeling, etc. His research has been applied to multiple interdisciplinary projects beyond NLP, such as representation learning on database workloads, psychotherapy observers for motivational interviews, AI partners in collaborative learning, math teaching/tutoring settings, multimodal machine learning for materials science, and agentic systems for hydrology and other science domains. His work includes publications in Nature Machine Intelligence, ACL, NAACL, EMNLP, COLING, VLDB, and other AI conferences.

Selected Publications

Yiming Liu, Ziyue Zhang, Zhichao Xu, Xin Yu, Yingheng Tang, Tianyu Jiang, and Jie Cao. 2026. Beyond Supervised Clarification: Input Rewriting with LLMs for Dialogue Discourse Parsing. In Proceedings of the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL 2026).

Zilong Li and Jie Cao. 2026. Translation via Annotation: A Computational Study of Translating Classical Chinese into Japanese. In Vera Demberg, Kentaro Inui, and Lluís Marquez, editors, Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 6031–6045, Rabat, Morocco, March. Association for Computational Linguistics.

Yingheng Tang, Wenbin Xu, Jie Cao, Weilu Gao, Steven Farrell, Benjamin Erichson, Michael W. Mahoney, Andy Nonaka, and Zhi Jackie Yao. 2026. A Multimodal Large Language Model for Materials Science. Nature Machine Intelligence, April.

Songkun Yan, Zhi Li, Siyu Zhu, Yixin Wen, Mofan Zhang, Mengye Chen, Jie Cao, and Yang Hong. 2025. AQUAH: Automatic Quantification and Unified Agent in Hydrology. 1st Workshop on Sustainability with Earth Observation and AI (co-located with ICCV 2025).

Jie Cao, Abhijit Suresh, Jennifer Jacobs, Charis Clevenger, Amanda Howard, Chelsea Brown, Brent Milne, Tom Fischaber, Tamara Sumner, and James H. Martin. 2025. Enhancing Talk Moves Analysis in Mathematics Tutoring through Classroom Teaching Discourse. In The 31st International Conference on Computational Linguistics.

Jie Cao, Ananya Ganesh, Jon Cai, Rosy Southwell, Magerate Perkoff, Michael Regan, Katharina Kann, James Martin, Martha Palmer, and Sideny D’Mello. 2023. A Comparative Analysis of Automatic Speech Recognition Errors in Small Group Classroom Discourse. Proceedings of the 31st ACM Conference on User Modeling Adaptation and Personalization.

E. Margaret Perkoff, Abhidip Bhattacharyya, Jon Cai, and Jie Cao. 2023. Comparing Neural Question Generation Architectures for Reading Comprehension. 18th Workshop on Innovative Use of NLP for Building Educational Applications, 2023.

Debjyoti Paul*, Jie Cao*, Feifei Li, and Vivek Srikumar. 2021. Database Workload Characterization with Query Plan Encoders. Proceedings of the VLDB Endowment, 15(4):923–935.

Jie Cao and Yi Zhang. 2021. A Comparative Study on Schema-Guided Dialogue State Tracking. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 782–796.

Jie Cao, Yi Zhang, Adel Youssef, and Vivek Srikumar. 2019. Amazon at MRP 2019: Parsing Meaning Representations with Lexical and Phrasal Anchoring. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the Conference on Natural Language Learning, pages 138–148.

Jie Cao, Michael Tanana, Zac Imel, Eric Poitras, David Atkins, and Vivek Srikumar. 2019. Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.