Le Zhang   张乐

Researcher
Business Intelligence Lab, Baidu Research, Baidu Inc

Email:   zhangle0202@gmail.com;   laughing@mail.ustc.edu.cn.
Office:   Baidu Campus, No. 10 Shangdi 10th Street, Haidian District, Beijing, China.
Biography

Le Zhang is currently a researcher at Baidu Research, Baidu Inc. He received his B.E. degree in Software Engineering from Dalian University of Technology in 2016. And he received his Ph.D. degree in Computer Science from University of Science and Technology of China (USTC) in 2022 under the supervision of Prof. Hui Xiong and Prof. Enhong Chen. His general research interests are data mining and machine learning, with a focus on spatio-temporal modeling and its applications in business intelligence.

Publications   (Selected)
  1. Han Wu, Le Zhang, Hengshu Zhu, Qi Liu, Enhong Chen, Hui Xiong, Examination Process Modeling for Intelligent Patent Management: A Multi-aspect Neural Sequential Approach , Transactions on Management Information Systems, TMIS, 2025.
  2. Shingming Zhang, Le Zhang*, Jingbo Zhou, Zhi Zheng, Hui Xiong, LLM-Eraser: Optimizing Large Language Model Unlearning through Selective Pruning , In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (KDD'25), Toronto, ON, Canada.
  3. Qian Sun, Le Zhang*, Jingo Zhou, Rui Zha, Yu Mei, Chujie Tian, Hui Xiong, Spatio-Temporal Sequence Modeling for Traffic Signal Control , In Proceedings of 33rd ACM International Conference on Information and Knowledge Management, (CIKM’24), Boise, Idaho, USA, 2024
  4. Le Zhang*, Wenyuan Jiang*, Wenwei Wu*, Zixuan Yuan, Jian Xiang, Jingbo Zhou, Hui Xiong, Killing Two Birds with One Stone: Cross-modal Reinforced Prompting for Graph and Language Tasks, In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (KDD'24), Barcelona, Spain, 2024.
  5. Weijia Zhang, Le Zhang, Jindong Han, Hao Liu, Yanjie Fu, Jingbo Zhou, Yu Mei, Hui Xiong, Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks, In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (KDD'24), Barcelona, Spain, 2024.
  6. Qian Sun, Rui Zha, Le Zhang*, Jingbo Zhou, Yu Mei, Zhiling Li, Hui Xiong*, CrossLight: Offline-to-Online Reinforcement Learning for Cross-City Traffic Signal Control, In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (KDD'24), Barcelona, Spain, 2024.
  7. Yuyang Ye, Hengshu Zhu, Tianyi Cui, Runlong Yu, Le Zhang, Hui Xiong, University Evaluation through Graduate Employment Prediction: An Influence based Graph Autoencoder Approach, In IEEE Transactions on Knowledge and Data Engineering, (IEEE TKDE), 2024.
  8. Leilei Ding, Dazhong Shen, Chao Wang, Tianfu Wang, Le Zhang, Yanyong Zhang, DGR: A General Graph Desmoothing Framework for Recommendation via Global and Local Perspectives, In Proceedings of the 33rd International Joint Conference on Artificial Intelligence, (IJCAI'24), Jeju, 2024.
  9. Rui Zha, Le Zhang, Shuangli Li, Jingbo Zhou, Tong Xu, Enhong Chen, Hui Xiong, Scaling up Multivariate Time Series Pre-Training with Decoupled Spatial-Temporal Representations, In IEEE International Conference on Data Engineering, (ICDE'24), Utrecht, Netherlands, 2024.
  10. Rui Zha, Ying Sun, Chuan Qin, Le Zhang, Tong Xu, Hengshu Zhu, Enhong Chen, Towards Unified Representation Learning for Career Mobility Analysis with Trajectory Hypergraph, In ACM Transactions on Information Systems, (ACM TOIS), 2024.
  11. Ying Sun, Hengshu Zhu, Lu Wang, Le Zhang, Hui Xiong, Large-scale Online Job Search Behaviors Reveal Labour Market Shifts, to appear in Nature Cities, 2024.
  12. Xiaoshan Yu, Chuan Qin, Dazhong Shen, Haiping Ma, Le Zhang, Hengshu Zhu, Xingyi Zhang, Hui Xiong, RDGT: Enhancing Group Cognitive Diagnosis with Relation-Guided Dual-Side Graph Transformer, In IEEE Transactions on Knowledge and Data Engineering, (IEEE TKDE), 2024.
  13. Yunfei Zhang, Chuan Qin, Dazhong Shen, Haiping Ma, Le Zhang, Xingyi Zhang, and Hengshu Zhu, ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness, 23rd IEEE International Conference on Data Mining, (ICDM'23), Shanghai, China, 2023.
  14. Rui Zha, Ding Zhou, Le Zhang, Tong Xu, A Multi-level Attentive Embedding Framework for Proposal Teamwork Analysis in Voting-oriented System, The 7th APWeb-WAIM International Joint Conference on Web and Big Data, (APWeb'23), Wuhan, China, 2023.
  15. Siyuan Hao, Le Dai, Le Zhang*, Shengming Zhang, Chao Wang, Chuan Qin, Hui Xiong, Hybrid Heterogeneous Graph Neural Networks for Fund Performance Prediction, The 16th International Conference on Knowledge Science, Engineering and Management, (KSEM'23), Guangzhou, China, 2023.
  16. Qian Sun, Le Zhang*, Huan Yu, Yu Mei, Hui Xiong, Hierarchical Reinforcement Learning for Dynamic Autonomous Vehicle Navigation at Intelligent Intersections, In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (KDD'23), Long Beach, CA, USA, 2023.[PDF]
  17. Rui Zha, Chuan Qin*, Le Zhang*, Dazhong Shen, Tong Xu, Hengshu Zhu, Enhong Chen, Career Mobility Analysis with Uncertainty-aware Graph Autoencoders: A Job Title Transition Perspective, In IEEE Transactions on Computational Social Systems, (TCSS'23).
  18. Jingci Ming, Le Zhang*, Wei Fan, Weijia Zhang, Yu Mei, Weicen Ling, Hui Xiong, Multi-Graph Convolutional Recurrent Network for Fine-Grained Lane-Level Traffic Flow Imputation, In Proceedings of 2022 IEEE International Conference on Data Mining, (ICDM'22), Orlando, FL, USA.[PDF]
  19. Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong, Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning, In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (KDD'22), Washington DC. [PDF]
  20. Zihao Zhou, Le Zhang, Rui Zha, Qiming Hao, Tong Xu, Di Wu, Enhong Chen, Multi-Relational Graph Convolution Network for Stock Movement Prediction, In Proceedings of the 2022 IEEE World Congress on Computational Intelligence, (IJCNN'22), Padova, Italy.
  21. Huijie Liu, Han Wu, Le Zhang, Runlong Yu, Ye Liu, Chunli Liu, Minglei Li, Qi Liu, Enhong Chen, A Hierarchical Interactive Multi-Channel Graph Neural Network for Technological Knowledge Flow Forecasting, In Knowledge and Information Systems, (KAIS'22).
  22. Zhe Zhang, Tong Xu, Chuan Qin, Le Zhang, Enhong Chen, Hui Xiong, Complex Attributed Network Embedding for Medical Complication Prediction, In Knowledge and Information Systems, (KAIS'22).
  23. Huijie Liu, Han Wu, Le Zhang, Runlong Yu, Ye Liu, Qi Liu, Enhong Chen, Technological Knowledge Flow Forecasting through A Hierarchical Interactive Graph Neural Network, In Proceedings of IEEE International Conference on Data Mining 2021, (ICDM'21), Online, 2021.
  24. Le Zhang, Ding Zhou, Hengshu Zhu, Tong Xu, Rui Zha, Enhong Chen, Hui Xiong, Attentive Heterogeneous Graph Embedding for Job Mobility Prediction, In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'21), Singapore, 2021. [PDF] [code]
  25. Zhe Zhang, Tong Xu, Le Zhang, Yichao Du, Hui Xiong, Enhong Chen, Knowledge Powered Cooperative Semantic Fusion for Patent Classification, In Proceedings of CAAI International Conference on Artificial Intelligence 2021 (CICAI’21), Hangzhou, China, 2021. (Best Student Paper Finalist)
  26. Lintao Fang, Le Zhang, Han Wu, Tong Xu, Ding Zhou, Enhong Chen, Patent2Vec: Multi-view Representation Learning on Patent-Graphs for Patent Classification, In World Wide Web (WWWJ'21).
  27. Chao Ren, Le Zhang, Lintao Fang, Tong Xu, Zhefeng Wang, Senchao Yuan, Enhong Chen, Ontological Concept Structure Aware Knowledge Transfer for Inductive Knowledge Graph Embedding, In Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN'21), Shenzhen, China, 2021.
  28. Qiming Hao, Le Zhang, Rui Zha, Ding Zhou, Zhe Zhang, Tong Xu, Enhong Chen, Urban Crowd Density Prediction Based on Multi-relational Graph, In Proceedings of the 22nd IEEE International Conference on Mobile Data Management (MDM'21), Online, 2021.
  29. Linkang Hu, Weidong He, Le Zhang, Tong Xu, Hui Xiong, Enhong Chen, Detecting Highlighted Video Clips via Emotion-enhanced Audio-Visual Cues, In Proceedings of IEEE International Conference on Multimedia and Expo 2021 (ICME'21), Shenzhen, China, 2021.
  30. Ding Zhou, Hao Liu, Tong Xu, Le Zhang, Rui Zha, Hui Xiong, Transportation Recommendation with Fairness Consideration, In Proceedings of the 26th International Conference on Database Systems for Advanced Applications (DASFAA'21), Taipei, China, 2021, 566-578. [PDF]
  31. Binglei Wang, Tong Xu, Hao Wang, Yanmin Chen, Le Zhang, Lintao Fang, Guiquan Liu, Enhong Chen, Author Contributed Representation for Scholarly Network, In Proceedings of the 4th APWeb-WAIM International Joint Conference on Web and Big Data (APWeb-WAIM'20), Tianjin, China, 2020, 558-573. [PDF]
  32. 秦川, 祝恒书, 庄福振, 郭庆宇, 张琦, 张乐, 王超, 陈恩红, 熊辉, 基于知识图谱的推荐系统研究综述, 《中国科学: 信息科学》, 2020.
  33. Le Zhang, Tong Xu, Hengshu Zhu, Chuan Qin, Qingxin Meng, Hui Xiong, Enhong Chen, Large-Scale Talent Flow Embedding for Company Competitive Analysis, In Proceedings of The Web Conference 2020 (WWW'20), Taipei, China, 2020, 2354-2364. [PDF]
  34. Qingxin Meng, Hengshu Zhu, Keli Xiao, Le Zhang, Hui Xiong, A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction, In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19) , Anchorage, Alaska, 2019, 14-24. [PDF]
  35. Xunxian Wu, Tong Xu, Hengshu Zhu, Le Zhang, Hui Xiong, Enhong Chen, Trend-Aware Tensor Factorization for Job Skill Demand Analysis, In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), Macau, China, 2019, 3891-3897. [PDF]
  36. Le Zhang, Chen Zhu, Hengshu Zhu, Tong Xu, Enhong Chen, Chuan Qin, Hui Xiong, Large-Scale Talent Flow Forecast with Dynamic Latent Factor Model, In Proceedings of The Web Conference 2019 (WWW'19), San Francisco, CA, USA, 2019, 2312-2322. [PDF]
  37. 吴法民, 吕广奕, 刘淇, 何明, 常标, 何伟栋, 钟辉, 张乐. 视频实时评论的深度语义表征方法[J], 计算机研究与发展, 2019, 56(2): 293-305.
  38. Le Zhang, Tianyuan Jin, Tong Xu, Biao Chang, Zhefeng Wang and Enhong Chen, A Markov Chain Monte Carlo Approach for Source Detection in Networks, In Proceedings of Sixth National Conference on Social Media Processing (SMP'17), Beijing, China, 2017, 77-88. [PDF]
Honors & Awards
  • BAIDU :
    • 2022, 百度研究院年度优秀之星
    • 2022, 百度小赞
    • 2023, 百度小赞
  • USTC :
    • 2022, 安徽省优秀毕业生
    • 2021, 国家奖学金
    • 2020, 国睿奖学金
    • 2019, 环球数码奖学金
    • 2017, 环球数码奖学金
    • 2016~2021, 学业奖学金一等
  • DLUT :
    • 2016, 大连市优秀毕业生、大连市三好学生
    • 2015, 大连理工大学凌水奖学金
    • 2013, 辽宁省第五届大学生高等数学竞赛二等奖
    • 2013, 大连市第22届大学生高等数学竞赛一等奖
Academic Services
  • PC Member :
    • The 32nd ACM International Conference on Information and Knowledge Management (CIKM-2023)
    • ECML/PKDD 2023 Research Track (PKDD-2023)
    • The 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2023)
    • The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining（KDD-2023）
    • The AAAI Conference on Artificial Intelligence (AAAI-2023)
    • The 19th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2022)
  • Journal Reviewer :
    • ACM Transactions on Knowledge Discovery from Data (TKDD)
    • Frontiers in Big Data