Bohan LI

Associate Professor, Master's Supervisor
College of Artificial Intelligence
Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China

Email: bhli@nuaa.edu.cn
[Official NUAA Homepage]

[DBLP] [Semantic Scholar] [Google Scholar]

I am an Associate Professor and master's supervisor at the College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics. I received my B.E. degree in Computer Science and Applications and my M.E. and Ph.D. degrees in Computer Application Technology from Harbin University of Science and Technology between 1998 and 2009. From 2016 to 2017, I was a visiting scholar at the School of Information Technology and Electrical Engineering (ITEE), The University of Queensland, Australia. My research interests include databases, spatio-temporal information management, knowledge graphs, recommender systems, and intelligent information processing.

Research Interests:

Databases and Spatio-temporal Information Management: database systems, geographic information systems (GIS), and spatio-temporal data management.
Knowledge Graphs and Large Language Models: knowledge graph construction and reasoning, retrieval-augmented generation (RAG), and complex question answering.
Recommender Systems and User Modeling: cross-domain recommendation, session-based recommendation, point-of-interest recommendation, and graph learning.
Intelligent Applications: the Internet of Things, blockchain, human-computer interaction, and interdisciplinary applications.

Prospective Students:

I am looking for master's students in Computer Science and Technology, Software Engineering, and Electronic Information. Students with strong academic motivation and an interest in databases, knowledge graphs, large language models, or recommender systems are welcome to contact me.

Put words into action through knowledge and diligence. To be a supervisor, to be a companion!

Selected Publications:

The following are selected recent publications. For a complete list, please visit Google Scholar.

“U-NIAH: Unified RAG and LLM Evaluation for Long Context Needle-in-a-Haystack”
Yunfan Gao, Yun Xiong, Wenlong Wu, Bohan Li, Yijie Zhong, Haofen Wang
ACM Transactions on Information Systems (TOIS), 44(3), Article 55, 1–30, 2026. [Paper]
“PPA++: Preference Prototype-Aware Learning with Large Language Model for Universal Cross-Domain Recommendation”
Yuxi Zhang, Ji Zhang, Feiyang Xu, Lvying Chen, Bohan Li, Ning Wang, Huawei Tu, Lei Guo, Hongzhi Yin
Data Science and Engineering, 11(1): 213–229, 2026. [Paper]
“MultiRAG: A Knowledge-Guided Framework for Mitigating Hallucination in Multi-Source Retrieval Augmented Generation”
Wenlong Wu, Haofen Wang, Bohan Li, Peixuan Huang, Xinzhe Zhao, Lei Liang
IEEE International Conference on Data Engineering (ICDE), 3070–3083, 2025. [Paper]
“GoT-R: Enhancing Large Language Models for Complex Question Answering with Graph-of-Thought Guided Reasoning”
Peixuan Huang, Bohan Li, Wenlong Wu, Haofen Wang, Mengfei Xu, Chen Chen, Lei Liang, Meng Wang
International Conference on Database Systems for Advanced Applications (DASFAA), 305–320, 2025. [Paper]
“HBS-KGLLM: A General Framework for Generating Knowledge Graphs for Jailbreaking”
Xinzhe Zhao, Bohan Li, Junnan Zhuo, Wenlong Wu, Ruilong Huang, Yuanrui Liu, Haofen Wang, Hua Dai, Quoc Viet Hung Nguyen
International Conference on Database Systems for Advanced Applications (DASFAA), 431–446, 2025. [Paper]
“Self-supervised Dual Graph and Intention Association for Session-Based Recommendation”
Junnan Zhuo, Bohan Li, Sujie Yu, Shuai Xu, Xinzhe Zhao, Zekun Xu, Guan Yuan
International Conference on Database Systems for Advanced Applications (DASFAA), 151–167, 2025. [Paper]
“TiDGRec: Dual-Graph Modeling with Target-Intention Filtering for Session-Based Recommendation”
Junnan Zhuo, Bohan Li, Sujie Yu, Shuai Xu, Yicong Li, Xinzhe Zhao, Guan Yuan
World Wide Web, 28(6): 61, 2025. [Paper]
“Preference Prototype-Aware Learning for Universal Cross-Domain Recommendation”
Yuxi Zhang, Ji Zhang, Feiyang Xu, Lvying Chen, Bohan Li, Lei Guo, Hongzhi Yin
ACM International Conference on Information and Knowledge Management (CIKM), 3290–3299, 2024. [Paper]
“Identifying Disinformation from Online Social Media via Dynamic Modeling across Propagation Stages”
Shuai Xu, Jianqiu Xu, Shuo Yu, Bohan Li
ACM International Conference on Information and Knowledge Management (CIKM), 2712–2721, 2024. [Paper]
“Disentangled Representations for Cross-Domain Recommendation via Heterogeneous Graph Contrastive Learning”
Xinyue Liu, Bohan Li, Yijun Chen, Xiaoxue Li, Shuai Xu, Hongzhi Yin
International Conference on Database Systems for Advanced Applications (DASFAA), 35–50, 2024. [Paper]
“Next POI Recommendation Based on Adaptive Graph Learning and Future Preferences”
Xiaoxue Li, Bohan Li, Yijun Chen, Xinyue Liu, Shuai Xu, Meng Wang
International Conference on Database Systems for Advanced Applications (DASFAA), 374–384, 2024. [Paper]
“Knowledge Enhancement for Contrastive Multi-Behavior Recommendation”
Hongrui Xuan, Yi Liu, Bohan Li, Hongzhi Yin
ACM International Conference on Web Search and Data Mining (WSDM), 195–203, 2023. [Paper]
“Efficient Multi-source Contact Event Query Processing for Moving Objects”
Pengyue Li, Hua Dai, Yu Chen, Bohan Li, Geng Yang
IEEE International Conference on Data Mining (ICDM), 1109–1114, 2023. [Paper]

Research Grants & Projects:

Young Scientists Fund of the National Natural Science Foundation of China (41301407), Research on Key Issues in Micro-geographic Information Management Supporting Weak-Link Awareness, 2014–2016.
Young Scientists Fund of the Natural Science Foundation of Jiangsu Province (BK20130819), Research on Key Technologies for Spatio-temporal Weak-Availability Information Management, 2013–2016.
China Postdoctoral Science Foundation (20100481133), Research on Key Issues in Spatio-temporal Multi-category Queries and Cost Models with Obstacles in Sensor Networks, 2011–2012.
Ford Motor Company University Research Program (URP), UMN: Mapless Autonomous Navigation Based on Deep Reinforcement Learning Perception Networks, 2020–2021.
Huawei Innovation DB IRP Project, Research and Implementation of High Availability and Survivability for GaussDB in New Hardware Environments, 2020–2021.