快速通道

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，威廉希尔亚洲公司理学博士，教授。主要研究领域：人工智能、大数据、金融科技。已在JMLR、ACM TACO、PR、KBS、IJCAI、AAAI、WWW、WSDM、EMNLP等国际知名期刊和会议上发表学术论文60多篇，并编著出版教材2本。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。

目前是IEEE、ACM和CCF会员。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TKDE、KBS、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. 《数据、模型与决策》
  2. 《推荐技术与应用》（MOOC： https://www.icourse163.org/learn/PKU-1464038187）
  3. 《金融大数据专题》
  4.  《量化投资策略与技术》
编著教材
 
  1. 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. 2022（出版中）
  2. 刘宏志 编著.《推荐系统》. 北京：机械工业出版社. 2020
  3. 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. 数据挖掘

  4. 群体智能

期刊论文
 

  1. 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)

  2. 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 B类国际期刊)

  3. 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: 7.74)

  4. 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: 8.038)

  5. 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: 8.038)

  6. 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)

  7. 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)

  8. 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: 3.756)

  9. 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:3.756)

  10. 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: 2.546)

  11. 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, 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)

  2. 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)

  3. 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

  4. 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)

  5. 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)

  6. 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).

  7. 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) 

  8. Bin Fu, Hongzhi Liu*, Yang Song, Tao Zhang, & Zhonghai Wu*. Generalized Collaborative Personalized Ranking for Recommendation, The 4th APWeb-WAIM Joint Conference on Web and Big Data (APWeb-WAIM 2020), Tianjin, China, September 18-20, 2020: 517-532. (CCF C类会议)

  9.  Zekai Wang, Hongzhi Liu*, Yingpeng Du, Zhonghai Wu, & Xing Zhang. Unified Embedding Model over Heterogeneous Information Network for 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)

  10. 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)

  11. 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)   

  12.  Hao Sun, Xu Tan, Jun-Wei Gan, Hongzhi Liu, Sheng Zhao, Tao QIN, Tie-Yan Liu. Token-Level Ensemble Distillation for Grapheme-to-Phoneme Conversion. The 20th Annual Conference of the International Speech Communication Association (INTERSPEECH 2019), Graz, Austria, September 15-19, 2019 (CCF C类会议)

  13. 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)
  14. 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)

  15. Hongzhi Liu, Yingpeng Du, & Zhonghai Wu. Collaborative Probability Metric Learning, The Second APWeb-WAIM Joint Conference on Web and Big Data (APWeb-WAIM 2018), Macau, China, July 23-25, 2018: 198-206. (CCF C类会议)

  16.  Yuanhang Qu, Hongzhi Liu*, Yingpeng Du, & Zhonghai Wu. A Hybrid Ranking Algorithm for Reciprocal Recommendation. The 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2018), Nanjing, China, August 28-31, 2018: 445-463. (CCF C类会议)

  17. Yingpeng Du, Hongzhi Liu*, Yuanhang Qu, & Zhonghai Wu. Online Personalized Next-Item Recommendation via Long Short Term Preference Learning. The 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2018), Nanjing, China, August 28-31, 2018: 915-927. (CCF C类会议)

  18. 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)

发明专利
 
  1. 刘宏志、江振滔、赵鹏、吴中海、张兴，一种基于人才流动的学校与公司共同排名方法及装置, 专利申请号：201710142777.5
  2. 刘宏志、江振滔、赵鹏、吴中海、张兴，一种基于人才流动分析的学校排名方法及装置，专利申请号：201710104626.0 
  3. 刘宏志、姜正申、易晖、赵鹏、吴中海、张兴，一种基于主动学习和模型剪枝的集成学习方法及装置，专利申请号：201611060500.X  
  4. 刘宏志、江振滔、赵鹏、易晖、付彬、吴中海、张兴，一种基于人才流动迭代模型的公司等级排名方法及装置，专利申请号：201610769693.X
  5. 刘宏志、江振滔、赵鹏、易晖、付彬、吴中海、张兴，一种启发式的工作岗位分级方法及装置，专利申请号：201610773434.4
  6. 刘宏志、蒋杰、王巨宏、管刚、吴中海、张兴，一套基于文本分析的信用风险评估方法及装置，专利申请号：201510695316.1
  7. 刘宏志、蒋杰、王巨宏、吴中海、张兴，数据离散化的方法和装置，专利申请号：201510271649.1
  8. 刘宏志，李浩，吴中海，张兴，针对Intel移动平台的实时AVS软编码方法，专利号：201410355678.1，授权日期：2017-05-04
  9. 曹喜信，曹健，刘宏志，于敦山，张兴，彭春干，一种分水岭图像分割处理方法, 专利号：200710120550.7，授权日期：2009-06-24 
  10. 曹喜信,刘宏志，一种电子桩考系统, 专利号：2006201242475，授权日期：2008-03-19
主要项目
 
  1. 威廉希尔亚洲公司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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 企业合作项目，基于大数据的岗位推荐，负责人，2015.8－2017.7
  7. 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
  8. 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
  9. 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
  10. 丹麦科技创新部重点，情境感知服务，参与人，2010.1-2013.4
  11. 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. IEEE会员、ACM会员、CCF会员

  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)、Knowledge-Based Systems (KBS)、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