快速通道
2021070601

刘宏志

  • 博士 教授
  • 金融信息与工程管理系
  • 工程管理硕士教育中心副主任
  • 人力资源大数据实验室负责人
  • Email: liuhz@ss.pku.edu.cn
个人简介
 

刘宏志，北京大学理学博士，教授。主要研究领域：人工智能、大数据、金融科技。已在Journal of Machine Learning Research (JMLR)、IEEE Trans. Knowledge & Data Engineering (TKDE)、ACM Trans. Architecture & Code Optimization (TACO)、 IEEE Trans. Circuits and Systems for Video Technology (TCSVT)、AAAI、IJCAI、KDD、WWW等国际知名期刊和会议上发表学术论文70多篇，并编著出版《推荐系统》、《数据分析：方法与应用》等多部教材。已申请专利10多项。参与和主持多项国家自然科学基金、重点研发计划、科技支撑计划、国际合作和企业合作项目。

中国计算机学会（CCF）杰出会员、数字金融分会执行委员、数据治理发展委员会执行委员；山东省智能油气工业软件重点实验室副主任。多次应邀担任AAAI、IEEE CEC、IEEE ICCI*CC、ICIC、I-SPAN、ICSS等国际会议的Co-Chair、Session Chair和PC Member。是IEEE TKDE、ACM TKDD、DMKD、Machine Learning等国际知名期刊的审稿人，国际期刊Journal of Interconnection Networks编委。2010年至2012年在哥伦比亚大学（美国）做访问研究。曾担任腾讯、看准网等公司顾问。

主讲课程
 
  1. 《推荐技术与应用》（MOOC： https://www.icourse163.org/learn/PKU-1464038187）
  2. 《金融大数据专题》
  3.  《量化投资策略与技术》
编著教材
 
  1. 刘宏志，吴中海 编著.《推荐系统》(第2版). 北京：机械工业出版社. 2024
  2. 刘宏志，吴中海 编著. 《数据分析：方法与应用》. 北京：高等教育出版社. 2023
  3. 刘宏志 编著.《推荐系统》. 北京：机械工业出版社. 2020
  4. 刘宏志 编著.《数据、模型与决策》. 北京：机械工业出版社. 2019
研究方向
 
  1. 推荐系统

  2. 量化投资

  3. 数据分析方法及应用

  4. 机器学习理论及应用

期刊论文
 
  1. Hongrui Guo, Tianqi Sun, Hongzhi Liu*, Zhonghai Wu. Adaptive Ensemble Learning with Category-Aware Attention and Local Contrastive Loss. IEEE Transactions on Circuits and Systems for Video Technology, 2024 (DOI: 10.1109/TCSVT.2024.3479313) (CCF B类国际期刊)
  2. Hongzhi Liu, Yao Zhu, Zhonghai Wu. Knowledge Graph-Based Behavior Denoising and Preference Learning for Sequential Recommendation. IEEE Transactions on Knowledge and Data Engineering, 36(6):2490 – 2503, 2024 (CCF A类国际期刊)
  3. Yingpeng Du, Hongzhi Liu*, Zekai Wang, Yang Song, Zhonghai Wu. Sequential ensemble learning for next item recommendation. Knowledge-Based Systems, 277, 110809: 1-11, 2023 (中科院一区, Impact Factor: 8.8)

  4. Hongzhi Liu, Yingpeng Du, Zhonghai Wu. Generalized Ambiguity Decomposition for Ranking Ensemble Learning [J]. Journal of Machine Learning Research, 23(88):1-36, 2022 (http://jmlr.org/papers/v23/20-843.html) (CCF A类国际期刊)

  5. Hongzhi Liu, Jie Luo, Ying Li, Zhonghai Wu. Iterative Compilation Optimization Based on Metric Learning and Collaborative Filtering [J]. ACM Transactions on Architecture and Code Optimization, 19(1), Article No.: 2, pp 1–25, 2022 (https://doi.org/10.1145/3480250) (CCF A类国际期刊)

  6. Hongzhi Liu, Yingpeng Du, Zhonghai Wu. AEM: Attentional Ensemble Model for Personalized Classifier Weight Learning, Pattern Recognition, 96, 10697: 1-8, 2019 (中科院一区, Top期刊，Impact Factor: 8.518)

  7. Hongzhi Liu, Zhengshen Jiang, Yang Song, Tao Zhang, Zhonghai Wu. User Preference Modeling Based on Meta Paths and Diversity Regularization in Heterogeneous Information Networks, Knowledge-Based Systems, 181, 104784: 1-10, 2019 (中科院一区, Top期刊，Impact Factor: 8.139)

  8. Hongzhi Liu, Zhonghai Wu, Xing Zhang. CPLR: Collaborative pairwise learning to rank for personalized recommendation, Knowledge-Based Systems, 148: 31-40, 2018  (中科院一区, Top期刊，Impact Factor: 8.139)

  9. Chang Guo, Ying Li, Hongzhi Liu, Zhonghai Wu. An application-oriented Cache Allocation and Prefetching Method for Long-running Applications in Distributed Storage Systems, Chinese Journal of Electronics, 28(4):773-780, 2019 (SCI，Impact Factor: 1.014)

  10. Shuxia Wang, Yuwei Qi, Bin Fu, Hongzhi Liu*. Credit Risk Evaluation Based on Text Analysis. International Journal of Cognitive Informatics and Natural Intelligence, 10(1):1-11, 2016. (EI, SCI)

  11. Hongzhi Liu, Zhonghai Wu, Xing Zhang, D. Frank Hsu. A Skeleton Pruning Algorithm Based on Information Fusion, Pattern Recognition Letters, 34(10): 1138-1145, 15 July 2013 (JCR二区,Impact Factor: 4.757)

  12. Hongzhi Liu, Zhonghai Wu, D. Frank Hsu, Bradley S. Peterson, Dongrong Xu. On the generation and pruning of skeletons using generalized Voronoi diagrams, Pattern Recognition Letters, 33(16): 2113–2119, 1 December 2012 (JCR二区, Impact Factor:4.757)

  13. Zhenyu Zhou, Xunheng Wang, Nelson J. Klahr, Wei Liu, Diana Arias, Hongzhi Liu, Karen M. von Deneen, Ying Wen, Zuhong Lu, Dongrong Xu, Yijun Liu. A Conditional Granger Causality Model Approach for Group Analysis in Functional Magnetic Resonance Imaging.  Magnetic Resonance Imaging, 29(3):  418-433, 2011 (SCI, Impact Factor: 3.13)

  14. 姜正申, 刘宏志*, 付彬, 吴中海, 集成学习的泛化误差和AUC分解理论及其在权重优化中的应用，计算机学报，42(1): 1-15，2019  (CCF A类中文期刊)

会议论文
 
  1. Yingpeng Du, Ziyan Wang, Zhu Sun, Yining Ma, Hongzhi Liu, Jie Zhang. Disentangled Multi-interest Representation Learning for Sequential Recommendation. The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), Barcelona, Spain, August 25-29, 2024 (CCF A类会议)
  2. Wenxuan Zhang, Hongzhi Liu*, Zhijin Dong, Yingpeng Du, Chen Zhu, Yang Song, Hengshu Zhu & Zhonghai Wu. Bridging the Information Gap Between Domain-Specific Model and General LLM for Personalized Recommendation. Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data (APWeb-WAIM 2024), Jinhua, China, August 30-September 1, 2024 (CCF C类会议）
  3. Yingpeng Du, Di Luo, Rui Yan , Xiaopei Wang, Hongzhi Liu*, Hengshu Zhu, Yang Song, Jie Zhang. Enhancing Job Recommendation through LLM-Based Generative Adversarial Networks. The 38th AAAI Conference on Artificial Intelligence (AAAI 2024),Vancouver, Canada, February 22-25, 2024 (CCF A类会议)
  4. Tianqi Sun, Hongrui Guo, Zihan Zhang, Hongzhi Liu*, Zhonghai Wu. Exploiting Multifaceted Nature of Items and Users for Session-based Recommendation. SIAM International Conference on Data Mining (SDM 2024), Houston, USA, Apr 18, 2024 - Apr 20, 2024 (CCF B类会议)
  5. Jiaxing Chen, Hongzhi Liu*, Hongrui Guo, Yingpeng Du, Zekai Wang, Yang Song, Zhonghai Wu. Bilateral Sequential Hypergraph Convolution Network for Reciprocal Recommendation. IEEE International Conference on Data Mining (ICDM 2023), Shanghai, China, December 1-4, 2023 (CCF B类会议)

  6. Jiaxing Chen, Hongzhi Liu*, Yingpeng Du, Zekai Wang, Yang Song, Zhonghai Wu*. Sequential Hypergraph Convolution Network for Next Item Recommendation. The 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), April 17-20, 2023 (CCF B类会议)

  7. Yusen Zhang, Zhongli Li, Qingyu Zhou, Ziyi Liu, Chao Li, Mina Ma, Yunbo Cao, Hongzhi Liu. AiM: Taking Answers in Mind to Correct Chinese Cloze Tests in Educational Applications. The 29th International Conference on Computational Linguistics (COLING 2022), Gyeongju, Republic of Korea, October 12–17, 2022 (CCF B类会议)

  8. Yingpeng Du, Hongzhi Liu*, & Zhonghai Wu. M^3-IB: A Memory-augment Multi-modal Information Bottleneck Model for Next-item Recommendation. The 27th International Conference on Database Systems for Advanced Applications (DASFAA 2022), April 11-14, 2022 (CCF B类会议)

  9. Bin Fu, Hongzhi Liu*, Hui Zhao, Yang Song, Tao Zhang, & Zhonghai Wu. Market-aware Dynamic Person-Job Fit with Hierarchical Reinforcement Learning. The 27th International Conference on Database Systems for Advanced Applications (DASFAA 2022), April 11-14, 2022 (CCF B类会议)

  10. Zhongli Li, Wenxuan Zhang, Chao Yan, Qingyu Zhou, Chao Li, Hongzhi Liu, & Yunbo Cao. Seeking Patterns, Not just Memorizing Procedures: Contrastive Learning for Solving Math Word Problems. Findings of the Association for Computational Linguistics: ACL 2022, May 22-27, 2022

  11. Yao Zhu, Hongzhi Liu*, Zhonghai Wu, & Yingpeng Du. Relation-Aware Neighborhood Matching Model for Entity Alignment. The 35th AAAI Conference on Artificial Intelligence (AAAI-21), Vancouver, British, February 2-9, 2021 (CCF A类会议)

  12. Yao Zhu, Hongzhi Liu*, Yingpeng Du，& Zhonghai Wu*. An Information Fusion-based Framework for Spam Review Detection. The 30th International World Wide Web Conference (WWW 2021), Ljubljana, Slovenia, April 19-23, 2021 (CCF A类会议)

  13. Yingpeng Du, Hongzhi Liu*, Zhonghai Wu*. Modeling Multi-factor and Multi-faceted Preferences over Sequential Networks for Next Item Recommendation. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2021), Bilbao, Spain, September 13-17, 2021 (CCF B类会议).

  14. Bin Fu, Hongzhi Liu*, Yang Song, Tao Zhang, & Zhonghai Wu*. Beyond Matching: Modeling Two-Sided Multi-Behavioral Sequences For Dynamic Person-Job Fit. The 26th International Conference on Database Systems for Advanced Applications (DASFAA 2021), April 11-14, 2021. (CCF B类会议) 

  15. Zekai Wang, Hongzhi Liu*, Yingpeng Du, Zhonghai Wu, & Xing Zhang. Unified Embedding Model over Heterogeneous Information Network for Personalized Recommendation. The 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), August 10-16, 2019, Macao, China, August 10-16, 2019 (CCF A类会议)

  16. Yao Zhu, Hongzhi Liu*, Zhonghai Wu, Yang Song, & Tao Zhang. Representation Learning with Ordered Relation Paths for Knowledge Graph Completion. 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019), Hong Kong, China, November 3-7, 2019 (CCF B类会议)

  17. Zhen Dong, Shizhao Sun, Hongzhi Liu, Jian-Guang Lou, & Dongmei Zhang. Data-Anonymous Encoding for Text-to-SQL Generation. 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019), Hong Kong, China, November 3-7, 2019 (CCF B类会议)   

  18. Yingpeng Du, Hongzhi Liu*, Zhonghai Wu, & Xing Zhang. Hierarchical Hybrid Feature Model For Top-N Context-Aware Recommendation. IEEE International Conference on Data Mining (ICDM 2018), Singapore, November 17-20, 2018: 109-116 (CCF B类会议)
  19. Zhengshen Jiang, Hongzhi Liu*, Bin Fu, Zhonghai Wu*, & Tao Zhang. Recommendation in Heterogeneous Information Networks Based on Generalized Random Walk Model and Bayesian Personalized Ranking. The Eleventh ACM International Conference on Web Search and Data Mining (WSDM 2018), Marina Del Rey, CA, USA, February 5-9, 2018: 288-296. (CCF B类会议)

  20. Zhengshen Jiang, Hongzhi Liu*, Bin Fu, & Zhonghai Wu*. Generalized Ambiguity Decompositions for Classification with Applications in Active Learning and Unsupervised Ensemble Pruning, Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), San Francisco, California, USA, February 4-9, 2017: 2073-2079. (CCF A类会议)

主要项目
 
  1. 河北省重大科技专项，基于人工智能的中医医方挖掘和临床路径优化，课题负责人，2024~2027
  2. 长沙市重大科技专项，科创企业信用风险数智化评估技术及应用研究，负责人，2024-2026
  3. 企业合作项目，风险识别模型研究，负责人，2023-2024
  4. 国家重点研发计划项目，基于区块链的卫生健康数据可信共享技术及示范应用，骨干成员，2022-2025
  5. 国家重点研发计划课题，知识融合关键技术研究，骨干成员，2019 -2021
  6. 北京大学教育大数据研究项目，基于数据融合的个性化课程推荐，负责人，2020-2021
  7. 国家重点研发计划，面向智慧城市的智能化集成化软件互操作平台，国家重点研发计划，骨干成员，2017-2020
  8. 企业合作项目，基于机器学习的高效边缘节点代码生成，负责人，2018-2021
  9. 国家自然科学基金重点项目，云存储的隐私保护与安全保障机制，参与人，2013.1－2017.12
  10. 国家863计划主题，云安全的可信服务及在教育云的示范验证，参与人，2015.1-2017.12
  11. 企业合作项目，基于大数据的岗位推荐，负责人，2015.8－2017.7
  12. 教育部产学合作协同育人项目，大数据专题，负责人，2016.9-2017.8
  13. CCF-犀牛鸟基金项目，基于用户线上线下信息融合的信用评级研究，负责人，2014.9－2015.10
  14. 国家科技支撑计划项目，新媒体资源编解码关键技术研究，任务负责人，2012.1－2014.12
  15. 丹麦科技创新部重点，情境感知服务，参与人，2010.1-2013.4
  16. 国家自然科学基金面上项目，基于互联网协同实时编辑软件的可测性与自动化测试技术，参与人，2010.1-2012.12
社会服务
 
  1. CCF杰出会员、CCF数字金融分会执行委员、CCF数据治理发展委员会执行委员、CCF大数据专委委员、CCF人工智能与模式识别专委委员

  2. 多次担任AAAI、IEEE CEC, ICCI*CC，ICIC，I-SPAN、ICSS等国际会议的Co-Chair、Session Chair和PC Member 

  3. IEEE Transactions on Knowledge and Data Engineering (TKDE)、ACM Transactions on Knowledge Discovery from Data (TKDD)、Data Mining and Knowledge Discovery (DMKD)、Machine Learning等国际知名期刊的审稿人

  4. 国际期刊Journal of Interconnection Networks编委