Prof. Bai received his BEng degree in computer science and his BBA degree in general business management from the Hong Kong University of Science and Technology (HKUST), and his PhD degree in computer science from HKUST, where he was supported by the Hong Kong PhD Fellowship Scheme and advised by Prof. Yangqiu Song. He was a Postdoctoral Researcher in the Department of Computer Science and Engineering at HKUST, supported by the Research Grants Council Junior Research Fellow Scheme, and visited the University of Edinburgh hosted by Jeff Pan. He also completed Applied Scientist summer internships at Amazon Search (A9), Palo Alto, working on reasoning over structured knowledge. His research has been published in leading international conferences and journals, including ACL, ICLR, WWW, KDD, NeurIPS, TMLR, and IEEE Data Engineering Bulletin. He has served as Area Chair through the ACL Rolling Review process (for NAACL, ACL, and EMNLP) and as a reviewer or program committee member for venues such as KDD, ACL, EMNLP and TPAMI. He joins the Department of Computer Science at Hong Kong Baptist University as an Assistant Professor in 2026.

• J. Bai, W. Fan, Q. Hu, Q. Zong, C. Li, H. T. Tsang, H. Luo, Y. Yim, H. Huang, X. Zhou, F. Qin, T. Zheng, X. Peng, X. Yao, H. Yang, L. Wu, Y. Ji, G. Zhang, R. Chen, and Y. Song. "AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corpora." Proc. the 64th Annual Meeting of the Association for Computational Linguistics (ACL '26), 2026.
• H. T. Tsang, J. Bai, H. Huang, Q. Xiao, T. Zheng, B. Xu, S. Liu, and Y. Song. "AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction." Proc. the 64th Annual Meeting of the Association for Computational Linguistics (ACL '26), 2026.
• J. Bai, Z. Wang, Y. Zhou, H. Yin, W. Fei, Q. Hu, Z. Deng, J. Cheng, T. Zheng, H. T. Tsang, Y. Gao, Z. Xie, Y. Li, L. Fan, B. Yuan, W. Wang, L. Chen, X. Zhou, and Y. Song. "Top Ten Challenges Towards Agentic Neural Graph Databases." IEEE Data Engineering Bulletin, March 2025.
• J. Bai, Y. Wang, T. Zheng, Y. Guo, X. Liu, and Y. Song. "Advancing Abductive Reasoning in Knowledge Graphs through Complex Logical Hypothesis Generation." Proc. the 62nd Annual Meeting of the Association for Computational Linguistics (ACL '24), Bangkok, Thailand, 2024.
• J. Bai, C. Luo, Z. Li, Q. Yin, and Y. Song. "Understanding Inter-Session Intentions via Complex Logical Reasoning." Proc. the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24), Barcelona, Spain, 2024.
• J. Bai, X. Liu, W. Wang, C. Luo, and Y. Song. "Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints." Proc. the 37th Conference on Neural Information Processing Systems (NeurIPS '23), New Orleans, LA, USA, 2023.
• J. Bai, C. Luo, Z. Li, Q. Yin, B. Yin, and Y. Song. "Knowledge Graph Reasoning over Entities and Numerical Values." Proc. the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '23), Long Beach, CA, USA, 2023.
• J. Bai, T. Zheng, and Y. Song. "Sequential Query Encoding For Complex Query Answering on Knowledge Graphs." Transactions on Machine Learning Research (TMLR), 2023.
• J. Bai, Z. Wang, H. Zhang, and Y. Song. "Query2Particles: Knowledge Graph Reasoning with Particle Embeddings." Proc. the 60th Annual Meeting of the Association for Computational Linguistics (NAACL '22), Findings of the Association for Computational Linguistics: NAACL 2022, Seattle, WA, USA, 2022.