Youru Li (李有儒)
Professor, Ph.D Supervisor
Youru Li is a Professor and Ph.D Supervisor in the College of Computer Science, Beijing University of Technology. He serves as an Executive Committee Member of the Digital Medicine Branch of the China Computer Federation. He received his M.E. and Ph.D. degrees in Computer Science from Beijing Jiaotong University in 2020 and 2025, respectively. He previously worked as a Machine Learning Algorithm Engineer and FinTech Algorithm Visiting Researcher at Alibaba and Ant Group. He has been selected for several talent support programs, including the Young Elite Talent Program of Beijing University of Technology's High-level Talent Development Plan and the Doctoral Special Plan of the Young Elite Scientists Sponsorship Program by China Association for Science and Technology.
His research interests include spatio-temporal data mining, large-scale knowledge graph construction and reasoning, personalized information recommendation, large language models, and their applications in digital intelligence services such as clinical medicine and financial security. He has presided over or participated in several research projects, including the National Key R&D Program of China "New Generation Artificial Intelligence" under the Ministry of Science and Technology, National Natural Science Foundation of China, Beijing Natural Science Foundation, and Fundamental Research Funds for the Central Universities.
He has received several research awards, including the Second Prize for Technological Progress of the Chinese Association for Artificial Intelligence (CAAI) WU Wenjun AI Science and Technology Award, the Chinese Institute of Electronics (CIE) Excellent Master Dissertation Award, and the CIE Excellent Doctoral Dissertation Forum Best Poster Award. He has published over 30 academic papers in top-tier journals and conferences in data mining and artificial intelligence, such as TKDE, TPAMI, TIM, TKDD, TOMM, TORS, KDD, AAAI, and MICCAI. His first-authored papers have been selected as ESI Highly Cited Papers, with the highest citation count exceeding 500. He has applied for/been granted more than 10 national invention patents.
Email / Google Scholar / ORCID / DBLP / GitHub
Research Group
Data and Knowledge Computing Research Group
PhD Students
Master Students
Undergraduate Students
News
- 01/2025 I will be supported by the Inaugural Young Elite Scientists Sponsorship Program by CAST, Doctoral Student Special Plan. (Supported by the Chinese Institute of Electronics (CIE)) .
- 08/2024 Our paper has been accepted by ACM TORS.
- 05/2024 Our paper has been accepted by KDD 2024（Research Track）.
- 05/2024 Our paper has been accepted by ACM TOMM.
- 02/2024 Our paper has been accepted by IEEE TIM.
- 01/2024 Our paper has been accepted by ACM TKDD.
- 01/2024 Our project has been honoured the CAAI WU Wenjun AI Science and Technology Award.
- 11/2023 I have been won the CIE Excellent Doctoral Dissertation Forum Best Poster Award.
- 10/2023 Our paper has been accepted by Applied Intelligence.
- 10/2023 Our paper has been accepted by IEEE TPAMI.
- 09/2023 Our paper has been accepted by IEEE TKDE.
- 06/2023 Our paper has been accepted by ACM TKDD.
- 06/2023 Our paper has been accepted by Expert Systems with Applications.
- 06/2023 Our paper has been accepted by Computers in Biology and Medicine.
- 05/2023 Our paper has been accepted by KDD 2023（ADS Track）.
- 12/2022 Our paper has been accepted by Computers in Biology and Medicine.
- 11/2022 Our paper has been accepted by IEEE TKDE.
- 10/2022 Our paper has been selected as the CNKI 2011-2022 High Impact Papers.
- 09/2022 Our paper EA-LSTM has been selected as the ESI Highly Cited Papers.
- 05/2022 Our paper has been accepted by MICCAI 2022.
- 02/2022 Our paper has been accepted by Neural Computing and Applications.
- 12/2021 I have been supported by the Alibaba Innovative Research Foundation (talent plan for Ph.D student).
- 07/2021 Our paper has been accepted by Biomedical Signal Processing and Control.
- 04/2021 Our paper has been accepted accepted by IEEE TKDE.
- 02/2021 My thesis has been honoured the 2020 Chinese Institute of Electronics (CIE) Excellent Master Dissertation Award.
Recent Projects
Efficient and effective delivery of urban information services is key to enhancing the quality of modern service industries. Existing technologies often face challenges such as scarcity of scenario-specific data, insufficient domain knowledge, and limited interaction modalities, leading to imbalanced resource allocation and entrenched information filter bubbles. To address these issues, this project aims to achieve three core objectives: ensuring stability, enabling trustworthy modeling, and facilitating accessible services. Specifically, we propose: An adaptive multi-view graph-enhancement framework that improves the accuracy of service demand forecasting through covariate integration and sample augmentation; A knowledge-augmented pseudo-sample generation and adaptive bias-correction mechanism to mitigate data bias; A generative recommendation system that synergistically combines spatiotemporal knowledge graphs with large language models to precisely align multimodal user intents with spatiotemporal behaviors. The research will focus on three main thrusts: (1) cold-start prediction via data augmentation, (2) trustworthy recommendation through knowledge augmentation, and (3) generative recommendation leveraging spatiotemporal knowledge and multimodal collaboration. The outcomes are expected to overcome traditional limitations of recommender systems in stability, trustworthiness, and accessibility, significantly improving the precision and efficiency of urban information service delivery at scale. This will enhance user experience and engagement, provide critical technical support for governments in building personalized public welfare systems, and advance the digital-intelligent transformation of urban governance—particularly in the capital city.
With the continuous popularization and development of intelligent devices and information collection technologies, more and more structured data become more accessible and play an unprecedented application value in different fields, such as Internet finance, smart transportation, smart agriculture, recommendation marketing, and so on.To address the challenges of complex structured data in information pattern mining and representation learning, such as the low quality of data due to data sparsity, how to self-adaptively utilize or eliminate bias in biased data modeling, how to fully learn the complementary information among different structured data elements in multi-data representation learning, and how to improve interpretability in structured data representation modeling through knowledge-aware approach, this project proposes a framework for knowledge-enhanced structured data representation learning and attempts to systematically give a solution to the challenges.
With the continuous upgrading of national intelligent construction strategy and the fast development of techniques such as real-time positioning, intelligent mobile terminals and portable sensors, spatial-temporal data has become increasingly available nowadays and shows practical application value. Mining valuable knowledge from spatial-temporal data can contribute to effectively solve the problems in real world applications. Accordingly, how to better learn the representation of pattern in spatial-temporal data, and establish accurate prediction model for different tasks, so as to realize discovering of high-value knowledge automatically can be a very valuable research problem.
Research
He is interested in sequence data mining, knowledge graph and their applications in Healthcare Informatics, RecSys and finTech, etc.
Conference Papers:
- FlexCare: Leveraging Cross-Task Synergy for Flexible Multimodal Healthcare Prediction
Muhao Xu, Zhenfeng Zhu, Youru Li, Shuai Zheng, Yawei Zhao, Kunlun He, Yao Zhao
KDD 2024 | paper | code - Learning Joint Relational Co-evolution in Spatial-Temporal Knowledge Graph for SMEs Supply Chain Prediction
Youru Li, Zhenfeng Zhu, Xiaobo Guo, Linxun Chen, Zhouyin Wang, Yinmeng Wang, Bing Han, Yao Zhao
KDD 2023 | paper | code | video - SGT: Scene Graph-Guided Transformer for Surgical Report Generation
Chen Lin, Shuai Zheng, Zhizhe Liu, Youru Li, Zhenfeng Zhu, Yao Zhao
MICCAI 2022 | paper | code - Learning heterogeneous spatial-temporal representation for bike-sharing demand prediction
Youru Li, Zhenfeng Zhu, Deqiang Kong, Meixiang Xu, Yao Zhao
AAAI 2019 | paper - The study on human action recognition with depth video for intelligent monitoring
Xueping Liu, Yibo Li, Youru Li, Shi Yu, Can Tian
IEEE CCDC 2019 | paper - Study on system modeling and optimization of static evaluation based on the computer game of draughts
Li Youru, Liu Xueping, Zhang Hekai, Xi Yuting
IEEE CCDC 2016 | paper - A systematic research about the computer game of checkers based on the decision-making of AI
Youru Li, Liu Xueping, Wang Yajie, Xi Yuting
IEEE CCDC 2015 | paper
Journal Papers:
- Determinantal Point Processes Guided Crowd-wise Mixture-of-Experts for Recommendation in Alipay
Youru Li, Zhenfeng Zhu, Shaohu Chen, Kaiming Shen, Xingxing Zhang Wenliang Zhong and Yao Zhao
ACM Transactions on Recommender Systems 2024 | paper - HKA: A Hierarchical Knowledge Alignment Framework for Multimodal Knowledge Graph Completion
Yunhui Xu, Youru Li, Muhao Xu, Zhenfeng Zhu and Yao Zhao
ACM Transactions on Multimedia Computing, Communications, and Applications 2024 | paper - Multi-Task Learning with Sequential Dependence Towards Industrial Applications: A Systematic Formulation
Huaxin Pang, Shikui Wei, Youru Li, Ting Liu, Huaqi Zhang, Ying Qin and Yao Zhao
IEEE Transactions on Instrumentation and Measurement 2024 | paper - Multi-Task Learning with Sequential Dependence Towards Industrial Applications: A Systematic Formulation
Xiaobo Guo, Mingming Ha, Xuewen Tao, Shaoshuai Li, Youru Li, Zhenfeng Zhu, Zhiyong Shen, Li Ma
ACM Transactions on Knowledge Discovery from Data 2024 | paper - Multi-scale adaptive attention-based time-variant neural networks for multi-step time series forecasting
Changxia Gao, Ning Zhang, Youru Li, Yan Lin and Huaiyu Wan
Applied Intelligence 2023 | paper | code - Node-oriented Spectral Filtering for Graph Neural Networks
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu, Youru Li and Yao Zhao
IEEE Transactions on Pattern Analysis and Machine Intelligence 2023 | paper - Exploring Large-scale Financial Knowledge Graph for SMEs Supply Chain Mining
Youru Li, Zhenfeng Zhu, Linxun Chen, Bin Yang, Yaxi Wu, Xiaobo Guo, Bing Han and Yao Zhao
IEEE Transactions on Knowledge and Data Engineering 2023 | paper | code - HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk Prediction
Youru Li, Zhenfeng Zhu, Xiaobo Guo, Shaoshuai Li, Yuchen Yang and Yao Zhao
ACM Transactions on Knowledge Discovery from Data 2023 | paper | code - Adversarial self-attentive time-variant neural networks for multi-step time series forecasting
Changxia Gao, Ning Zhang, Youru Li, Yan Lin and Huaiyu Wan
Expert Systems with Applications 2023 | paper | code - Cooperative dual medical ontology representation learning for clinical assisted decision-making
Muhao Xu, Zhenfeng Zhu, Youru Li, Shuai Zheng, Linfeng Li, Haiyan Wu and Yao Zhao
Computers in Biology and Medicine 2023 | paper | code - CED: A case-level explainable paramedical diagnosis via AdaGBDT
Zhenyu Guo, Muhao Xu, Yuchen Yang, Youru Li, Haiyan Wu, Zhenfeng Zhu and Yao Zhao
Computers in Biology and Medicine 2022 | paper - Sylvester Equation Induced Collaborative Representation Learning for Recommendation
Xingyuan Li, Zhenfeng Zhu, Shuai Zheng, Zhizhe Liu, Youru Li, Xiaobo Guo, Deqiang Kong and Yao Zhao
IEEE Transactions on Knowledge and Data Engineering 2022 | paper - Self-attention-based time-variant neural networks for multi-step time series forecasting
Changxia Gao, Ning Zhang, Youru Li, Feng Bian and Huaiyu Wan
Neural Computing and Applications 2022 | paper | code - Deep learning based torsional nystagmus detection for dizziness and vertigo diagnosis
Wanlu Zhang, Haiyan Wu, Yang Liu, Shuai Zheng, Zhizhe Liu, Youru Li, Yao Zhao and Zhenfeng Zhu
Biomedical Signal Processing and Control 2021 | paper - Learning Dynamic User Interest Sequence in Knowledge Graphs for Click-Through Rate Prediction
Youru Li, Xiaobo Guo, Wenfang Lin, Mingjie Zhong, Qunwei Li, Zhongyi Liu, Wenliang Zhong, Zhenfeng Zhu
IEEE Transactions on Knowledge and Data Engineering 2021 | paper - DKEN: Deep knowledge-enhanced network for recommender systems
Xiaobo Guo, Wenfang Lin, Youru Li, Zhongyi Liu, Lin Yang, Shuliang Zhao, Zhenfeng Zhu
Information Sciences 2020 | paper - CCAE: Cross-field categorical attributes embedding for cancer clinical endpoint prediction
Youru Li, Zhenfeng Zhu, Haiyan Wu, Silu Ding, Yao Zhao
Artificial Intelligence in Medicine 2020 | paper - EA-LSTM: Evolutionary attention-based LSTM for time series prediction
Youru Li, Zhenfeng Zhu, Deqiang Kong, Hua Han, Yao Zhao
Knowledge-Based Systems 2019 | paper | code (ESI Highly Cited Paper) - GBDT based railway accident type prediction and cause analysis (in Chinese)
Minhui Zhong, Wanlu Zhang, Youru Li, Zhenfeng Zhu, Yao Zhao
Acta Autom. Sin 2022 | paper (CNKI 2011-2022 High Impact Papers) - Fault Diagnosis Technology of Inter-shaft Bearing Based on EMD Fuzzy Entropy and Consultative Decision Fusion Model (in Chinese)
Wang Zhi, Youru Li, Tian Jing, Liu Lili, Li Jikai
Aeroengine 2019 | paper - Fault diagnosis of aero-engine inter-shaft bearing based on Deep-GBM (in Chinese)
Tian Jing, Youru Li, Yanting Ai
Journal of Aerospace Power 2019 | paper - The Application Study on Improved Distributed Genetic Algorithm in Computer Games (in Chinese)
Xueping Liu, Youru Li
Transactions of Beijing Institute of Technology 2017 | paper