Jiaxin Bai

Assistant Professor (2026-)
Department of Computer Science
Hong Kong Baptist University

Postdoctoral Researcher (2025-2026)
Department of Computer Science and Engineering
Hong Kong University of Science and Technology

I join the Department of Computer Science at Hong Kong Baptist University as an Assistant Professor in April 2026.

Previously, I am a Postdoctoral Researcher supported by the prestigious RGC Junior Research Fellow Scheme in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology. I completed my Ph.D. supported by the Hong Kong PhD Fellowship Scheme at HKUST from September 2020, under the supervision of Professor Yangqiu Song. I also visited Professor Jeff Pan in University of Edingburgh. I also hold two Bachelor’s degrees in computer science and general business management from HKUST.

I did Applied Scientist summer internships at Amazon Search (previously known as A9) in Palo Alto, California, under the supervision of Dr. Chen Luo. Our work focused on exploring applications of reasoning over structured knowledge.

🔬 Research Focus

My research centers around the complete lifecycle of knowledge in AI systems, spanning three interconnected phases (details in selected publication):

🏗️ Phase 1: Knowledge Creation & Structuring

Building structured knowledge from raw data with automated processes that capture nuanced human intentions (ACL'23; EACL'26), autonomously inducing schemas and large-scale graphs from web corpora without predefined constraints (ACL'26), and aligning graph construction with downstream RAG performance through end-to-end reinforcement learning (ACL'26).

🧠 Phase 2: Complex Knowledge Reasoning

Developing novel methods for reasoning over knowledge graphs to answer complex queries and infer new information (KDD'24), including logical reasoning (NAACL'22 Findings; NeurIPS'23; KDD'23; TMLR'23), unified deductive and abductive reasoning with masked diffusion models (WWW'26), abductive and controllable hypothesis generation on graphs (ACL'24; ICLR'26), and multimodal abductive reasoning in vision-language settings (ACL'26), alongside privacy preservation (KDD'24;TMLR'25), and establishing the next-generation paradigm of Agentic Neural Graph Databases (Data Engineering Bulletin'25).

🤖 Phase 3: Knowledge-Enhanced AI Systems

Exploring the synergy between structured knowledge and large language models (LLMs) (EMNLP'20 Findings), including parametric integration of billion-scale knowledge graphs under tight memory budgets (ICLR'26), creating benchmarks to test robustness and comprehension abilities, benchmarking interactive scientific law discovery in LLM agents (ICLR'26), aligning knowledge graph construction with downstream retrieval-augmented generation via reinforcement learning (ACL'26), and developing methods to enhance factuality (ACL'26) and reasoning capabilities in specialized domains (ACL'25).

🏆 Honors & Awards

• 🎯 RGC Junior Research Fellow Scheme (2025) • Hong Kong Research Grants Council
• 🎓 Hong Kong PhD Fellowship (2020) • University Grants Committee

🎯 Academic Services

Area Chair

• ARR Oct 2024 → NAACL-2025
• ARR Feb 2025 → ACL-2025
• ARR May 2025 → EMNLP-2025

Reviewer & Program Committee Member

• KDD: 2021, 2023, 2024, 2025
• ACL: 2023
• EMNLP: 2021, 2022
• JAIR: Journal
• TKDE: Journal
• NLPCC: 2023
• ARR: Ongoing

Interested in collaboration? Feel free to reach out for research opportunities, academic discussions, or potential partnerships.