Weike Pan Ph.D. (HKUST, 2012), Professor Software Engineering Research Center College of Computer Science and Software Engineering Shenzhen University Email: panweike(at)szu(dot)edu(dot)cn or weikep(at)gmail(dot)com Address: RM724, Zhiteng Building (College of Computer Science and Software Engineering), Canghai Campus of Shenzhen University, 3688# Nanhai Avenue, Nanshan District, Shenzhen, 518060, P.R. China

Biography

Dr. Weike Pan is currently a Professor with the College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, P.R. China. He received the B.Eng. degree in Computer Science from Zhejiang University, Hangzhou, P.R. China, in 2005, and the Ph.D. degree in Computer Science and Engineering from the Hong Kong University of Science and Technology, Kowloon, Hong Kong, P.R. China, in 2012. He was a senior engineer at Baidu Inc. and a post-doctoral research fellow at Hong Kong Baptist University.

His research interests include data mining and artificial intelligence, with a particular focus on transfer learning, federated learning, recommender systems and machine learning. He has published a Chinese textbook entitled Intelligent Recommendation Technology, and research papers in SCIENTIA SINICA Informationis, AIJ, TBD, TIIS, TIST, TKDE, TOIS, AAAI, CIKM, IJCAI, RecSys, SDM, SIGIR, WSDM, etc. He has served as an associate editor or editorial board member of ACM Transactions on Recommender Systems (ACM TORS), Neurocomputing and Frontiers in Big Data - Recommender Systems, an associate conference co-chair for virtual operations of AAAI 21, a senior PC of RecSys 21-23, etc. He is a senior member of ACM, CCF and IEEE.

中文主页 (in Chinese)

Research Interests

• Data Mining and Artificial Intelligence: Transfer Learning, Federated Learning, Recommender Systems and Machine Learning.
• Single-Behavior Recommendation
• Multi-Behavior Recommendation
• Sequential Recommendation
• Federated Recommendation
• Multi-Source Recommendation
• Trustworthy and Responsible Recommendation

Work Experience

• December 2022 -, Professor, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, P.R. China.
• December 2016 - December 2022, Associate Professor, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, P.R. China.
• 11 July 2013 - December 2016, Lecturer (research oriented, a.k.a., Assistant Professor), College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, P.R. China.
• 15 August 2012 - 14 June 2013, Post-doctoral Research Fellow, Department of Computer Science, Hong Kong Baptist University, Kowloon, Hong Kong, P.R. China.
• 18 June 2012 - 19 July 2012, Senior Engineer, NLP Group, Baidu Inc., Shenzhen, P.R. China.

Visiting and Intern Experience

• February 2012 - June 2012 (full/part time), Intern, NLP Group, Baidu Inc.
• June 2011 - December 2011 (full/part time), Intern, Data Mining Group, Tencent Inc.
• May 2010 - August 2010, Intern, NLP Group, Baidu Inc.
• February 2006 - June 2006, Intern, Speech Group, Microsoft Research Asia (MSRA).
• April 2005 - June 2005, Oversea Scholarship Student, Institute of Medical Informedics, Luebeck University.

Education

• 15 August 2007 - 15 June 2012, Ph.D. Student/Candidate (Thesis Advisor: Prof. Qiang Yang), Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong, P.R. China.
• 1 September 2005 - 30 June 2007, Ph.D. Student, College of Computer Science, Zhejiang University, Hangzhou, P.R. China.
• 1 September 2001 - 30 June 2005, Bachelor Student, College of Computer Science, Zhejiang University, Hangzhou, P.R. China.

Selected Publications (Full List)

Conference Papers

• Qianzhen Rao, Yang Liu, Weike Pan* and Zhong Ming*. BVAE: Behavior-aware Variational Autoencoder for Multi-Behavior Multi-Task Recommendation [C]. In: Proceedings of the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 18-22, 2023.
• Zitao Xu, Weike Pan* and Zhong Ming*. A Multi-view Graph Contrastive Learning Framework for Cross-Domain Sequential Recommendation [C]. In: Proceedings of the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 18-22, 2023.
• Dugang Liu#, Pengxiang Cheng#, Hong Zhu, Xing Tang, Yanyu Chen, Xiaoting Wang, Weike Pan*, Zhong Ming* and Xiuqiang He. DIWIFT: Discovering Instance-wise Influential Features for Tabular Data [C]. In: Proceedings of the The Web Conference 2023 (TheWebConf 2023, formerly WWW 2023), Austin, Texas, USA, pages 1673-1682, April 30-May 4, 2023.
• Dugang Liu, Yang Qiao, Xing Tang, Liang Chen, Xiuqiang He, Weike Pan* and Zhong Ming*. Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation [C]. In: Proceedings of the 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023), Tianjin, China, pages 580-592, April 17-20, 2023.
• Jinwei Luo, Mingkai He, Xiaolin Lin, Weike Pan* and Zhong Ming*. Dual-Task Learning for Multi-Behavior Sequential Recommendation [C]. In: Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), Atlanta, Georgia, USA (Hybrid Conference), pages 1379-1388, October 17-21, 2022.
• Weixin Chen, Mingkai He, Yongxin Ni, Weike Pan*, Zhong Ming* and Li Chen. Global and Personalized Graphs for Heterogeneous Sequential Recommendation by Learning Behavior Transitions and User Intentions [C]. In: Proceedings of the 16th ACM Conference on Recommender Systems (RecSys 2022), Seattle, WA, USA (Hybrid Conference), pages 268-277, September 18-23, 2022.
  
• Wei Cai, Weike Pan, Jingwen Mao, Zhechao Yu and Congfu Xu*. Aspect Re-distribution for Learning Better Item Embeddings in Sequential Recommendation [C]. In: Proceedings of the 16th ACM Conference on Recommender Systems (RecSys 2022), Seattle, WA, USA (Hybrid Conference), pages 49-58, September 18-23, 2022.
  
• Dugang Liu, Mingkai He, Jinwei Luo, Jiangxu Lin, Meng Wang, Xiaolian Zhang, Weike Pan* and Zhong Ming*. User-Event Graph Embedding Learning for Context-Aware Recommendation [C]. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), Washington DC, USA, pages 1051–1059, August 14-18, 2022.
  
• Wanqi Ma, Xiancong Chen, Weike Pan* and Zhong Ming*. VAE++: Variational AutoEncoder for Heterogeneous One-Class Collaborative Filtering [C]. In: Proceedings of the 15th International Conference on Web Search and Data Mining (WSDM 2022), Phoenix, Arizona, USA (Virtual Conference), pages 666-674, February 21-25, 2022.
• Dugang Liu#, Pengxiang Cheng#, Hong Zhu, Zhenhua Dong, Xiuqiang He, Weike Pan* and Zhong Ming*. Mitigating Confounding Bias in Recommendation via Information Bottleneck [C]. In: Proceedings of the 15th ACM Conference on Recommender Systems (RecSys 2021), Amsterdam, Netherlands (Virtual Conference), pages 351–360, September 27-October 1, 2021.
• Feng Liang, Weike Pan* and Zhong Ming*. FedRec++: Lossless Federated Recommendation with Explicit Feedback [C]. In: Proceedings of 35th AAAI Conference on Artificial Intelligence (AAAI 2021), Vancouver, Canada, Virtual Event, pages 4224-4231, February 2-9, 2021.
• Jing Lin, Weike Pan* and Zhong Ming*. FISSA: Fusing Item Similarity Models with Self-Attention Networks for Sequential Recommendation [C]. In: Proceedings of the 14th ACM Conference on Recommender Systems (RecSys 2020), Rio de Janeiro, Brazil, Virtual Event, pages 130-139, September 22-26, 2020.
• Dugang Liu, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Weike Pan* and Zhong Ming*. A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data [C]. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China, pages 831-840, July 25-30, 2020.
  
• Weike Pan and Li Chen. GBPR: Group Preference based Bayesian Personalized Ranking for One-Class Collaborative Filtering [C]. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013). Beijing, China, pages 2691-2697, August 3-9, 2013.
• Weike Pan and Li Chen. CoFiSet: Collaborative Filtering via Learning Pairwise Preferences over Item-sets [C]. In: Proceedings of the SIAM International Conference on Data Mining (SDM 2013). Austin, Texas, USA, pages 180-188, May 2-4, 2013. Nominee of Best Paper Award
  
• Weike Pan, Evan W. Xiang and Qiang Yang. Transfer Learning in Collaborative Filtering with Uncertain Ratings [C]. In: Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI 2012). Toronto, Ontario, Canada, pages 662-668, July 22-26, 2012.
• Weike Pan, Nathan N. Liu, Evan W. Xiang and Qiang Yang. Transfer Learning to Predict Missing Ratings via Heterogeneous User Feedbacks [C]. In: Proceedings of the 22rd International Joint Conference on Artificial Intelligence (IJCAI 2011). Barcelona, Catalonia, Spain, pages 2318-2323, July 16-22, 2011.
• Weike Pan, Evan W. Xiang, Nathan N. Liu and Qiang Yang. Transfer Learning in Collaborative Filtering for Sparsity Reduction [C]. In: Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI 2010). Atlanta, Georgia, USA, pages 230-235, July 11-15, 2010.

Journal and Magazine Papers

• Dugang Liu, Pengxiang Cheng, Zinan Lin, Xiaolian Zhang, Zhenhua Dong, Rui Zhang, Xiuqiang He, Weike Pan* and Zhong Ming*. Bounding System-Induced Biases in Recommender Systems with A Randomized Dataset [J]. ACM Transactions on Information Systems (ACM TOIS), 41(4):108:1-108:26, April, 2023.
• Jing Lin, Mingkai He, Weike Pan* and Zhong Ming*. Collaborative Filtering with Sequential Implicit Feedback via Learning Users' Preferences over Item-Sets [J]. Information Sciences (INS), 621:136-155, April 2023.
• Dugang Liu, Pengxiang Cheng, Hong Zhu, Zhenhua Dong, Xiuqiang He, Weike Pan* and Zhong Ming*. Debiased Representation Learning in Recommendation via Information Bottleneck [J]. ACM Transactions on Recommender Systems (ACM TORS), 1(1):5:1-5:27, January 2023.
• Jinwei Luo, Mingkai He, Weike Pan* and Zhong Ming. BGNN: Behavior-aware Graph Neural Network for Heterogeneous Session-based Recommendation [J]. Frontiers of Computer Science (FCS), 17(5):175336, 2023.
• Dugang Liu, Pengxiang Cheng, Zinan Lin, Jinwei Luo, Zhenhua Dong, Xiuqiang He, Weike Pan* and Zhong Ming*. KDCRec: Knowledge Distillation for Counterfactual Recommendation via Uniform Data [J]. Transactions on Knowledge and Data Engineering (IEEE TKDE), Accepted on August 7, 2022.
• Mingkai He, Jing Lin, Jinwei Luo, Weike Pan* and Zhong Ming*. FLAG: A Feedback-aware Local and Global Model for Heterogeneous Sequential Recommendation [J]. ACM Transactions on Intelligent Systems and Technology (ACM TIST), 14(1):14:1-14:22, February 2023.
  
• Zhaohao Lin, Weike Pan*, Qiang Yang* and Zhong Ming*. A Generic Federated Recommendation Framework via Fake Marks and Secret Sharing [J]. ACM Transactions on Information Systems (ACM TOIS), 41(2):40:1-40:37, April 2023.
• Mingkai He, Weike Pan* and Zhong Ming*. BAR: Behavior-Aware Recommendation for Sequential Heterogeneous One-Class Collaborative Filtering [J]. Information Sciences (INS), 608:881-889, August 2022.
• Wanqi Ma#, Xiaoxiao Liao#, Wei Dai, Weike Pan* and Zhong Ming*. Holistic Transfer to Rank for Top-N Recommendation [J]. ACM Transactions on Interactive Intelligent Systems (ACM TiiS), 11(1):8:1-8:23, March 2021.

• Guanyu Lin#, Feng Liang#, Weike Pan* and Zhong Ming*. FedRec: Federated Recommendation with Explicit Feedback [J]. IEEE Intelligent Systems (IEEE IS), 36(5):21-30, 22 October 2021.
• Wei Dai, Qing Zhang, Weike Pan* and Zhong Ming*. Transfer to Rank for Top-N Recommendation [J]. IEEE Transactions on Big Data (IEEE TBD), 6(4):770-779, December 2020.
• Xiancong Chen#, Lin Li#, Weike Pan* and Zhong Ming*. A Survey on Heterogeneous One-Class Collaborative Filtering [J]. ACM Transactions on Information Systems (ACM TOIS), 38(4):35:1-35:54, August 2020.
• Lin Li, Weike Pan* and Zhong Ming*. CoFi-points: Collaborative Filtering via Pointwise Preference Learning on User/Item-Set [J]. ACM Transactions on Intelligent Systems and Technology (ACM TIST), 11(4):41:1-41:24, May 2020.
  
• Zijie Zeng, Jing Lin, Lin Li, Weike Pan*, Zhong Ming*. Next-Item Recommendation via Collaborative Filtering with Bidirectional Item Similarity [J]. ACM Transactions on Information Systems (ACM TOIS), 38(1):7:1-7:22, December 2019.
• Weike Pan, Li Chen* and Zhong Ming*. Personalized Recommendation with Implicit Feedback via Learning Pairwise Preferences over Item-sets [J]. Knowledge and Information Systems (KAIS), 58(2):295–318, February 2019.
• Weike Pan, Qiang Yang*, Wanling Cai, Yaofeng Chen, Qing Zhang, Xiaogang Peng* and Zhong Ming*. Transfer to Rank for Heterogeneous One-Class Collaborative Filtering [J]. ACM Transactions on Information Systems (ACM TOIS), 37(1):10:1-10:20, January 2019.
• Weike Pan and Zhong Ming*. Collaborative Recommendation with Multiclass Preference Context [J]. IEEE Intelligent Systems (IEEE IS), 32(2):45-51, March 2017.
• Weike Pan, Qiang Yang*, Yuchao Duan, Ben Tan and Zhong Ming*. Transfer Learning for Behavior Ranking [J]. ACM Transactions on Intelligent Systems and Technology (ACM TIST), 8(5):65:1-65:23, July 2017.
• Weike Pan, Mengsi Liu and Zhong Ming*. Transfer Learning for Heterogeneous One-Class Collaborative Filtering [J]. IEEE Intelligent Systems (IEEE IS), 31(4):43-49, July 2016.
  
• Weike Pan and Qiang Yang. Transfer Learning for Behavior Prediction [J]. IEEE Intelligent Systems (IEEE IS), 31(2):86-88, March 2016. Invited Paper for Trends & Controversies on Uncovering and Predicting Human Behaviors.
• Weike Pan, Qiang Yang*, Yuchao Duan and Zhong Ming*. Transfer Learning for Semi-Supervised Collaborative Recommendation [J]. ACM Transactions on Interactive Intelligent Systems (ACM TiiS), 6(2):10:1-10:21, July 2016. ACM TiiS 2016 Best Paper Award
• Weike Pan, Shanchuan Xia, Zhuode Liu, Xiaogang Peng and Zhong Ming*. Mixed Factorization for Collaborative Recommendation with Heterogeneous Explicit Feedbacks [J]. Information Sciences (INS), 332:84–93, 1 March 2016.
• Weike Pan and Zhong Ming*. Interaction-Rich Transfer Learning for Collaborative Filtering with Heterogeneous User Feedback [J]. IEEE Intelligent Systems (IEEE IS), 29(6):48-54, December 2014.
• Congfu Xu, Baojun Su, Yunbiao Cheng, Weike Pan* and Li Chen. An Adaptive Fusion Algorithm for Spam Detection [J]. IEEE Intelligent Systems (IEEE IS), 29(4):2-8, August 2014.
  
• Weike Pan and Qiang Yang*. Transfer Learning in Heterogeneous Collaborative Filtering Domains [J]. Artificial Intelligence (AIJ), 197:39–55, April 2013.

Journal and Magazine Papers (in Chinese)

• 羊恩跃,潘微科,杨强,明仲. 联邦学习和推荐系统[J]. 中国计算机学会通讯, 2022,18(9):19-27.
  
• 梁锋#,羊恩跃#,潘微科*,杨强*,明仲*. 基于联邦学习的推荐系统综述[J]. 中国科学:信息科学, 2022, 52(5):713-741.
• 林子楠,刘杜钢,潘微科*,明仲. 面向推荐系统中有偏和无偏一元反馈建模的三任务变分自编码器[J]. 信息安全学报, 2021, 6(5):110-127.

Edited Special Issue

• Weike Pan, Qiang Yang, Charu Aggarwal and Christoph Koch. Big Data. Guest Editors' Introduction, Special Issue on Big Data, IEEE Intelligent Systems (IEEE IS), 32(2):7-8, March 2017.

Book Chapters

• Weike Pan and Guangneng Hu. Transfer Learning in Recommender Systems [M]. Transfer Learning, Qiang Yang, Yu Zhang, Wenyuan Dai and Sinno Jialin Pan, Cambridge University Press, pages 279-288, United Kingdom 2020. Book Chapter.
• Weike Pan, Erheng Zhong and Qiang Yang. Transfer Learning for Text Mining [M]. Mining Text Data, Charu C. Aggarwal and Chengxiang Zhai, Springer, pages 223-257, Germany 2012. Book Chapter.

Book (in Chinese)

• 潘微科,林晶,明仲 著. 智能推荐技术[M]. 清华大学出版社, 2022年4月. ISBN:978-7-302-60010-7. Slides

Book Translation (in Chinese)

• 翻译: 倪泳鑫,潘微科,明仲 译. 元分析：数据分析的共识方法和系统模式[M]. 北京:机械工业出版社, 2021年6月. ISSN: 978-7-111-68393-3.
• 翻译: 黎琳,潘微科,明仲 译. 文本机器学习[M]. 北京:机械工业出版社. 2020年5月. ISSN: 978-7-111-64805-5.
• 翻译: 戴薇,潘微科,明仲 译. 统计推荐系统[M]. 北京:机械工业出版社, 2019年9月. ISSN: 978-7-111-63573-4.
• 翻译: 李艳民,吴宾,潘微科,刘淇,蒋凡 等译. 推荐系统：技术、评估及高效算法[M]. 北京:机械工业出版社, 2018年6月. ISBN:978-7-111-60075-6.

Professional Services

• Journal Editorial Board Member/Associate Editor:
• ACM Transactions on Recommender Systems (ACM TORS): Editorial Board, Homepage, Digital Library, DBLP, Submission Site, Founding Associate Editor (September 2021 -)
• Neurocomputing: Editorial Board, Homepage, Digital Library, DBLP, Submission Site, Editorial Board Member (December 2017 -)
• Frontiers in Big Data - Recommender Systems: Editorial Board of Recommender Systems (specialty section of Frontiers in Big Data), Homepage, Articles, DBLP, Submission Site, Associate Editor (June 2022 -), Review Editor (April 2021 - June 2022)
• Journal of Information Analysis: Editorial Board, Homepage, Submission Site, Founding Associate Editor (March 2023 -)
• Journal Distinguished Reviewer:
• ACM Transactions on Interactive Intelligent Systems (ACM TiiS): Distinguished Reviewers, Homepage, Digital Library, DBLP, Submission Site, Distinguished Reviewer (June 2019 -)
• Journal Co-Guest Editor:
• Special Issue on Big Data (PDF, HTML), IEEE Intelligent Systems: Homepage, Digital Library, Submission Site, Co-Guest Editor (December 2015 - October 2016), Guest Editors' Introduction
• Journal Information Officer:
• ACM Transactions on Intelligent Systems and Technology (ACM TIST): Homepage, Assistant to the Editor-in-Chief (October 2009 - October 2015)
• Associate Conference Co-Chair for Virtual Operations
• 35th AAAI Conference on Artificial Intelligence (AAAI'21), Homepage, Big Thanks to Technical Volunteers
• Conference Tutorial Co-Chair
• 17th ACM Conference on Recommender Systems (RecSys'23)
• Conference PC Member:
• AAAI: 23/22/21/20/19/18/17
• ICLR: 23/22/21/20/19
• ICML (reviewer): 23/22/21/20/19/18
• IJCAI: 23/22/21(SPC)/20/19/18/17/16/15/13
• KDD: 22/21/20/19/18/16
• NeurIPS (reviewer): 22/21/20/19/18/17/16
• RecSys: 23(SPC)/22(SPC)/21(SPC)/20/19
• WWW: 23/22/21/20/19/18/17/15/14
More ...