I earned my PhD from SKL-IOTSC.

My research lies at the intersection of artificial intelligence (AI), knowledge representation, transportation, and healthcare. I focus on developing algorithms and techniques that enable knowledge-driven transportation systems and smart healthcare solutions. My interests span deep learning, reinforcement learning, and generative AI, with applications in prediction, recognition, decision-making, planning, and human-machine interaction. To date, I have published over 30 papers in top-tier AI, IOT, transportation, and healthcare journals and conferences.

🔥 News

• 2026.01:  🎉🎉 One paper has been accepted by WWW 2026.
• 2025.12:  🎉🎉 I serve as a Guest Editor for a Special Issue of IEEE IOTJ.
• 2025.11:  🎉🎉 One paper has been accepted by AAAI 2026.
• 2025.08:  🎉🎉 One paper has been accepted by IEEE IOTJ.
• 2025.06:  🎉🎉 One paper has been accepted by IEEE T-KDE.
• 2025.05:  🎉🎉 One paper has been accepted by ACL 2025.
• 2025.04:  🎉🎉 One paper has been accepted by BMC Public Health.
• 2025.02:  🎉🎉 One paper has been accepted by IEEE T-ITS.
• 2024.12:  🎉🎉 One paper has been accepted by TR-C.
• 2024.12:  🎉🎉 One paper has been accepted by IEEE T-ITS.
• 2024.12:  🎉🎉 Two papers have been accepted by AAAI 2025.
• 2024.10:  🎉🎉 One paper has been accepted by EAAI.
• 2024.09:  🎉🎉 One paper has been accepted by IEEE T-ITS.
• 2024.09:  🎉🎉 One paper has been accepted by Information Fusion.
• 2024.05:  🎉🎉 One paper has been accepted by ACL 2024.
• 2024.05:  🎉🎉 One paper has been accepted by IEEE T-CSVT.
• 2023.09:  🎉🎉 One paper has been accepted by IEEE T-KDE.
• 2023.07:  🎉🎉 One paper has been accepted by ACMMM 2023.

📝 Publications

Highlights

KnowLCP: Knowledge Augmented Lane Change Prediction for Autonomous Driving

Yuhuan Lu, Pengpeng Xu, Wei Wang, Zhen Zhang, Han Liu, Xiping Hu

AAAI, 2026

Paper

• We propose KnowLCP, a knowledge-augmented model for joint lane change intention and trajectory prediction.

HyperFM: Fact-Centric Multimodal Fusion for Link Prediction over Hyper-Relational Knowledge Graphs

Yuhuan Lu, Weijian Yu, Xin Jing, Dingqi Yang

ACL, 2025

Paper

• We propose HyperFM, a hyper-relational fact-centric multimodal fusion technique for link prediction tasks over multimodal hyper-relational KGs.

Schema-Aware Hyper-Relational Knowledge Graph Embeddings for Link Prediction

Yuhuan Lu, Dingqi Yang, Pengyang Wang, Paolo Rosso, Philippe Cudre-Mauroux

IEEE Transactions on Knowledge and Data Engineering, 2024

Paper

• We propose sHINGE, a schema-aware hyper-relational KG embedding model, which learns from hyper-relational facts directly and their corresponding hyper-relational schema in a KG.

HELIOS: Hyper-Relational Schema Modeling from Knowledge Graphs

Yuhuan Lu, Bangchao Deng, Weijian Yu, Dingqi Yang

ACMMM, 2023

Paper

• We propose HELIOS, a hyper-relational schema model designed to subtly learn from hyper-relational schema tuples by capturing not only the correlation between multiple types of a single entity, but also the correlation between types of different entities and relations in a schema tuple.

HyperCL: A Contrastive Learning Framework for Hyper-Relational Knowledge Graph Embedding With Hierarchical Ontology

Yuhuan Lu, Weijian Yu, Xin Jing, Dingqi Yang

ACL, 2024

Paper

• We propose a universal contrastive learning framework for hyper-relational KG embeddings (HyperCL), which is flexible to integrate different hyper-relational KG embedding methods and effectively boost their link prediction performance.

Dual-View Interaction-Aware Lane Change Prediction for Autonomous Driving

Yuhuan Lu, Zhen Zhang, Rufan Bai, Han Liu, Wei Wang

AAAI, 2025

Paper

• We propose to incorporate the concept of perceived safety into future interaction modeling and design a dual-view interaction-aware lane change prediction model.

Other Publications

• Dynamic Spatiotemporal Graph Convolutional Network Collaborative Pre-training Learning for Traffic Flow Prediction, Haiyang Chi, Yuhuan Lu, Yirong Zhu, Wei Ke, Hanbin Mao, Knowledge-Based Systems, 2025

• SIM-IBN: Surgical Event Time Imputation in Intent-Based Networking for Internet of Medical Things, Yixian Chen, Zhaocheng He, Sen Deng, You Zhou, Ali Kashif Bashir, Norah Saleh Alghamdi, Lin Yao, Yuhuan Lu, Wei Wang, IEEE Internet of Things Journal, 2025

• On Your Mark, Get Set, Predict! Modeling Continuous-Time Dynamics of Cascades for Information Popularity Prediction, Xin Jing, Yichen Jing, Yuhuan Lu, Bangchao Deng, Sikun Yang, Dingqi Yang, IEEE Transactions on Knowledge and Data Engineering, 2025

• Associations of Occupation Categories With Cardiovascular Diseases and All-Cause Mortality: An Analysis of NHANES 2005-2014, Haiyang Chi, Jia Zhou, Chao Li, Yuhuan Lu, Can Xie, Baoyu He, Wei Ke, BMC Public Health, 2025

• CasFT: Future Trend Modeling for Information Popularity Prediction With Dynamic Cues-Driven Diffusion Models, Xin Jing, Yichen Jing, Yuhuan Lu, Bangchao Deng, Xueqin Chen, Dingqi Yang, AAAI (Oral), 2025

• Multi-Node Joint Optimization for Fine-Grained Vehicle Trajectory Reconstruction Using Vehicle Appearance and Identity Data, Mingkai Qiu, Yuhuan Lu, Xiying Li, Transportation Research Part C: Emerging Technologies, 2025

• Spatio-Temporal Attention Based Collaborative Local–Global Learning for Traffic Flow Prediction, Haiyang Chi, Yuhuan Lu, Can Xie, Wei Ke, Bidong Chen, Engineering Applications of Artificial Intelligence, 2025

• Inter-Intra Cluster Reorganization for Unsupervised Vehicle Re-Identification, Mingkai Qiu, Yuhuan Lu, Xiying Li, Qiang Lu, IEEE Transactions on Intelligent Transportation Systems, 2024

• Camera-Aware Differentiated Clustering With Focal Contrastive Learning for Unsupervised Vehicle Re-Identification, Mingkai Qiu, Yuhuan Lu, Xiying Li, Qiang Lu, IEEE Transactions on Circuits and Systems for Video Technology, 2024

• A Crash Feature-Based Allocation Method for Boundary Crash Problem in Spatial Analysis of Bicycle Crashes, Hongliang Ding, Yuhuan Lu, NN Sze, Constantinos Antoniou, Yanyong Guo, Analytic Methods in Accident Research, 2023

• City-Scale Holographic Traffic Flow Data Based on Vehicular Trajectory Resampling, Yimin Wang, Yixian Chen, Guilong Li, Yuhuan Lu, Zhaocheng He, Zhi Yu, Weiwei Sun, Scientific Data, 2023

• Effect of Dockless Bike-Sharing Scheme on the Demand for London Cycle Hire at the Disaggregate Level Using A Deep Learning Approach, Hongliang Ding, Yuhuan Lu, NN Sze, Haojie Li, Transportation Research Part A: Policy and Practice, 2022

• A Deep Generative Approach for Crash Frequency Model With Heterogeneous Imbalanced Data, Hongliang Ding, Yuhuan Lu, NN Sze, Tiantian Chen, Yanyong Guo, Qinghai Lin, Analytic Methods in Accident Research, 2022

• A Resampling Approach to Disaggregate Analysis of Bus-Involved Crashes Using Panel Data With Excessive Zeros, Tiantian Chen, Yuhuan Lu, Xiaowen Fu, NN Sze, Hongliang Ding, Accident Analysis and Prevention, 2022

• Missing Traffic Data Imputation and Pattern Discovery With A Bayesian Augmented Tensor Factorization Model, Xinyu Chen, Zhaocheng He, Yixian Chen, Yuhuan Lu, Jiawei Wang, Transportation Research Part C: Emerging Technologies, 2019

🎖 Honors and Awards

• 2025.04 Presentation Award of Postgraduate Forum, University of Macau
• 2025.01 First Prize of Annual Academic Rising Star Award, Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing
• 2024.12 Ultimate Report Award, Southeast University
• 2021.08 UM PhD Assistantship, University of Macau
• 2017.12 Crowdsourcing Program Excellence Award, Key Laboratory of Road and Traffic Engineering of the Ministry of Education
• 2017.06 Outstanding Graduate, Sun Yat-Sen University

💰 Grants

• Research on Driver Behavior Prediction Theory and Method for Autonomous Logistics Transportation. Yunnan Provincial Key Laboratory Open Project, duration: 2025-2026, PI
• Research on Key Technologies of Real-Time Perception and Intelligent Decision Making for Resilient Cities. FDCT-NSFC Joint Funding Project, duration: 2022-2024, Key Participant
• Basic Theory and Key Technologies of Intelligent Transportation Based on Big Data. Key Project of National Natural Science Foundation of China, duration: 2019-2022, Key Participant

📖 Education

• 2021 - 2025, Doctor of Philosophy, Computer Science, University of Macau, Macao
• 2017 - 2020, Master of Science, Transportation Engineering, Sun Yat-Sen University, Guangzhou, China
• 2013 - 2017, Bachelor of Science, Traffic Engineering, Sun Yat-Sen University, Guangzhou, China

📚 Academic Services

Program Committee

• Main Track, ICML
• Main Track, ACMMM
• Artificial Intelligence for Social Impact Track, AAAI
• Web4Good Special Track, WWW
• AI and Social Good Special Track, IJCAI

Journal Reviewer

• IEEE Transactions on Pattern Analysis and Machine Intelligence
• IEEE Transactions on Knowledge and Data Engineering
• IEEE Transactions on Intelligent Transportation Systems
• IEEE Transactions on Vehicular Technology
• IEEE Internet of Things Journal
• IEEE Transactions on Consumer Electronics
• Machine Intelligence Research
• Transportation Research Part C: Emerging Technologies
• Accident Analysis and Prevention
• IET Intelligent Transport Systems
• Transportation Research Record

👨 Students

Co-Advised

• Haiyang Chi, PhD 2025 from Macao Polytechnic University, current employment: Associate Professor, Kunming University of Science and Technology
• Yixian Chen, PhD 2025 from Sun Yat-Sen University, current employment: Assistant Professor, Foshan University