Xiangyu Zhao   赵翔宇


                  Ph.D. Candidate

            Data Science and Engineering Lab
            Department of Computer Science and Engineering
            Michigan State University (MSU)

Correspondence

Email: zhaoxi35 [at] msu (dot) edu [contact me]
Office: Data Science and Engineering Lab, Engineering Building 3308, 428 South Shaw Lane, East Lansing, MI
Mail: Xiangyu Zhao, Engineering Building 3308, 428 South Shaw Lane, East Lansing, Michigan, USA, 48824
Links: [LinkedIn]     [Google Scholar]

[Biography]           [News]           [Publications]           [Services]           [Awards]           [Teaching]           [Internships]          

Brief Biography

Xiangyu Zhao is a Ph.D. candidate of Computer Science and Engineering at Michigan State University (MSU). His supervisor is Dr. Jiliang Tang. Prior to MSU, he completed his MS at USTC (2017) and BS at UESTC (2014).

His current research interests include data mining and machine learning, especially

  • Reinforcement Learning, AutoML and their applications in Information Retrieval (search, recommendation and advertising)
  • Urban Computing, Human Mobility Modeling, Spatio-Temporal Data Analysis and Location-Based Social Networks
  • Social Computing, Social Network and Complex Network Analysis

    • My [CV] (updated Mar 2021).

    News

    • 04/2021: We will provide tutorial Deep Learning for Recommendations: Fundamentals and Advances @ IJCAI'21
    • 03/2021: Awarded WWW 2021 Student Scholarship Award
    • 03/2021: I will co-host the 2nd Workshop on Deep Reinforcement Learning for Information Retrieval @ SIGIR'21
    • 03/2021: 1 workshop proposal got accepted by SIGIR'21
    • 01/2021: 2 papers got accepted by WWW'21
    • 01/2021: We will provide tutorial Deep Recommender System: Fundamentals and Advances @ WWW'21
    • 01/2021: I will co-host the 2nd Workshop on Deep Reinforcement Learning for Knowledge Discovery @ WWW'21
    • 01/2021: Received the AAAI 2021 Student Travel Award and will serve as volunteer
    • 01/2021: I will serve as the PC Member of RecSys'21
    • 01/2021: I will serve as the PC Member of ICML'21
    • 12/2020: 1 tutorial got accepted by WWW'21
    • 12/2020: I will serve as the Senior PC Member of IJCAI'21
    • 12/2020: Awarded MSU Dissertation Completion Fellowship
    • 12/2020: 1 paper got accepted by AAAI'21
    • 11/2020: Passed my comprehensive exam!
    • 11/2020: I will serve as the PC Member of KDD'21
    • 11/2020: 1 workshop proposal got accepted by WWW'21
    • 11/2020: I will serve as the PC Member of ECIR'21
    • 11/2020: I will serve as the Session Chair of ICONIP'20
    • 10/2020: 1 paper got accepted by WSDM'21
    • 10/2020: 1 paper got accepted by ICDE'21
    • [More]

    Selected Publications


        Tutorial and Workshop Proposals



    1. Weinan Zhang, Xiangyu Zhao, Li Zhao, Dawei Yin, Grace Hui Yang, Alex Beutel, 2nd Deep Reinforcement Learning for Information Retrieval: Fundamentals and Advances, 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2021). [Website]

    2. Xiangyu Zhao, Wenqi Fan, Dawei Yin, Jiliang Tang, Deep Recommender System: Fundamentals and Advances, The Web Conference 2021 (WWW'2021). [Website]

    3. Jiliang Tang, Xiangyu Zhao, Dawei Yin, Long Xia, Huiji Gao, Rui Chen, Jason Gauci, 2nd Deep Reinforcement Learning for Knowledge Discovery, The Web Conference 2021 (WWW'2021). [Website]

    4. Weinan Zhang, Xiangyu Zhao, Li Zhao, Dawei Yin, Grace Hui Yang, Alex Beutel, Deep Reinforcement Learning for Information Retrieval: Fundamentals and Advances, 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2020). [PDF][BibTeX][Website]

    5. Jiliang Tang, Dawei Yin, Long Xia, Alex Beutel, Minmin Chen, Shauki Jain, Xiangyu Zhao, Deep Reinforcement Learning for Knowledge Discovery, 25th ACM SIGKDD Conference on Knowledge Discovery and Data (KDD'2019). [Website]

        Conference and Journal Publications



    1. Xiangyu Zhao, Long Xia, Lixin Zou, Hui Liu, Dawei Yin, Jiliang Tang, UserSim: User Simulation via Supervised Generative Adversarial Network, The Web Conference 2021 (WWW'2021). [PDF][Slides][BibTeX]

    2. Xiangyu Zhao, Haochen Liu, Hui Liu, Jiliang Tang, Weiwei Guo, Jun Shi, Sida Wang, Huiji Gao, Bo Long, AutoDim: Field-aware Embedding Dimension Search in Recommender Systems, The Web Conference 2021 (WWW'2021). [PDF][Slides][BibTeX]

    3. Xiangyu Zhao, Chong Wang, Ming Chen, Xudong Zheng, Xiaobing Liu, Jiliang Tang, AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations. [PDF][BibTeX]

    4. Xiangyu Zhao, Hui Liu, Jiliang Tang, Exploring Spatio-Temporal and Cross-Type Correlations for Crime Prediction. [PDF][BibTeX]

    5. Xiangyu Zhao, Changsheng Gu, Haoshenglun Zhang, Xiwang Yang, Xiaobing Liu, Jiliang Tang, Hui Liu, DEAR: Deep Reinforcement Learning for Online Advertising in Recommender Systems, 35th AAAI Conference on Artificial Intelligence (AAAI'2021). [PDF][Slides][BibTeX]

    6. Yingqiang Ge, Shuchang Liu, Ruoyuan Gao, Yikun Xian, Yunqi Li, Xiangyu Zhao, Changhua Pei, Fei Sun, Junfeng Ge, Wenwu Ou, Yongfeng Zhang, Towards Long-term Fairness in Recommendation, 13th International Conference on Web Search and Data Mining (WSDM'2021). [PDF][BibTeX]

    7. Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li, Attacking Black-box Recommendations via Copying Cross-domain User Profiles, 37th IEEE International Conference on Data Engineering (ICDE'2021). [PDF][BibTeX]

    8. Xiangyu Zhao, Long Xia, Lixin Zou, Dawei Yin, Hui Liu, Jiliang Tang, Whole-Chain Recommendations, 29th ACM International Conference on Information and Knowledge Management (CIKM'2020). [PDF][Slides][BibTeX]

    9. Xiangyu Zhao, Xudong Zheng, Xiwang Yang, Xiaobing Liu, Jiliang Tang, Jointly Learning to Recommend and Advertise, 26th ACM SIGKDD Conference on Knowledge Discovery and Data (KDD'2020). [PDF][Slides][BibTeX]

    10. Xiangyu Zhao*, Haochen Liu*, Chong Wang, Xiaobing Liu, Jiliang Tang, Automated Embedding Size Search in Deep Recommender Systems, 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2020). [PDF][Slides][BibTeX]

    11. Lixin Zou, Long Xia, Yulong Gu, Xiangyu Zhao, Weidong Liu, Jimmy Xiangji Huang, Dawei Yin, Neural Interactive Collaborative Filtering, 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2020). [PDF][Slides][BibTeX]

    12. Xiangyu Zhao, Liang Zhang, Long Xia, Zhuoye Ding, Dawei Yin, Jiliang Tang, Deep Reinforcement Learning for List-wise Recommendations, 1st Workshop on Deep Reinforcement Learning for Knowledge Discovery (DRL4KDD'2019). [PDF][BibTeX][Code 1 2 3]

    13. Xiangyu Zhao, Long Xia, Jiliang Tang, Dawei Yin, Deep Reinforcement Learning for Search, Recommendation, and Online Advertising: A Survey, ACM SIGWEB Newsletter (SIGWEB), 2019, Issue Spring: Article No.4. [PDF][BibTeX]

    14. Xiangyu Zhao, Long Xia, Liang Zhang, Zhuoye Ding, Dawei Yin, Jiliang Tang, Deep Reinforcement Learning for Page-wise Recommendations, 12th ACM Recommender Systems Conference (RecSys'2018). [PDF][Slides][Poster][BibTeX]

    15. Xiangyu Zhao, Liang Zhang, Zhuoye Ding, Long Xia, Jiliang Tang, Dawei Yin, Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning, 24th ACM SIGKDD Conference on Knowledge Discovery and Data (KDD'2018). [PDF][Poster][BibTeX]

    16. Xiangyu Zhao, Jiliang Tang, Crime in Urban Areas: A Data Mining Perspective, ACM SIGKDD Explorations Newsletter (SIGKDD Explorations), 2018, 20(1): 1-12. [PDF][BibTeX]

    17. Xiangyu Zhao, Jiliang Tang, Modeling Temporal-Spatial Correlations for Crime Prediction, 26th ACM International on Conference on Information and Knowledge Management (CIKM'2017). [PDF][Slides][BibTeX]

    18. Xiangyu Zhao, Tong Xu, Yanjie Fu, Enhong Chen, Hao Guo, Incorporating Spatio-Temporal Smoothness for Air Quality Inference, 17th International Conference on Data Mining (ICDM'2017). [PDF][Slides][BibTeX]

    19. Xiangyu Zhao, Jiliang Tang, Exploring Transfer Learning for Crime Prediction, 17th International Conference on Data Mining (ICDM'2017), Ph.D. Forum. [PDF][BibTeX]

    20. Tong Xu, Hengshu Zhu, Xiangyu Zhao, Qi Liu, Hao Zhong, Enhong Chen, Hui Xiong, Taxi Driving Behavior Analysis in Latent Vehicle-to-Vehicle Networks: A Social Influence Perspective, 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2016). [PDF][Slides][Video][BibTeX]

    21. Xiangyu Zhao, Tong Xu, Qi Liu, Hao Guo, Exploring the Choice under Conflict for Social Event Participation, 21st International Conference on Database Systems for Advanced Applications (DASFAA'2016). [PDF][Slides][BibTeX]

    22. Hao Guo, Xin Li, Ming He, Xiangyu Zhao, Guiquan Liu, Guandong Xu, CoSoLoRec: Joint Factor Model with Content, Social, Location for Heterogeneous Point-of-Interest Recommendation, 9th International Conference on Knowledge Science, Engineering and Management (KSEM'2016). [PDF][Slides][BibTeX]

    23. Xiangyu Zhao, Bin Huang, Ming Tang, Haifeng Zhang, Duanbing Chen, Identifying Effective Multiple Spreaders by Coloring Complex Networks, Europhysics Letters (EPL), 2015, 108(6): 68005. (SCI IF: 2.095) [PDF][BibTeX]

    24. Bin Huang, Xiangyu Zhao, Kai Qi, Ming Tang, Younghae Do, Coloring the Complex Networks and its Application for Immunization Strategy, Acta Physica Sinica (APS), 2013, 62(21): 218902-218902. (SCI IF: 0.845) [PDF][BibTeX]

    Services

    • Organizer
    • Conference Program Committee Member
      • 2021: KDD, AAAI, IJCAI (SPC), ICML, ICLR, RecSys, ECIR
      • 2020: AAAI, IJCAI, ICLR, CIKM, ICONIP, IEEE BigData, AI4EDU@AAAI'20, IRS@KDD'20
      • 2019: IEEE BigData, RecSys, NLPCC, RL4RealLife@ICML'19
      • 2018: IEEE BigData
    • Conference Reviewer
      • 2021: WWW, SIGIR, ACL
      • 2020: KDD, SIGIR, WSDM, ICWSM
      • 2019: KDD, AAAI, WWW, SIGIR, CIKM, ICWSM, EMNLP, ASONAM
      • 2018: KDD, AAAI, WWW, SIGIR, CIKM, WSDM, ICWSM, RecSys, ASONAM, CHI
      • 2017: AAAI, SIGIR, CIKM, SDM, RecSys, ICWSM, DASFAA, ASONAM
      • 2016: KDD, CIKM, ICDM, RecSys, DASFAA, PAKDD, WAIM, KSEM, ASONAM
      • 2015: KSEM, ASONAM, AAAI BigData
    • Journal Reviewer
      • IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE)
      • ACM Transactions on Knowledge Discovery from Data (ACM TKDD)
      • ACM Transactions on Information Systems (ACM TOIS)
      • ISPRS International Journal of Geo-Information (IJGI)
      • Journal of Computer Science and Technology
      • IEEE Intelligent Systems
      • Journal of Big Data
      • Machine Learning
      • ETRI Journal
      • IEEE Access
    • Student Membership
      • Institute of Electrical and Electronics Engineers (IEEE)
      • Special Interest Group on Information Retrieval (SIGIR)
      • Association for the Advancement of Artificial Intelligence (AAAI)
      • Society for Industrial and Applied Mathematics (SIAM)
    • Conference Volunteer
      • 2021: AAAI
      • 2020: KDD
      • 2019: KDD
      • 2018: KDD, RecSys
      • 2011: CCCN

    Honors and Awards

    • MSU:
      • 2021, WWW 2021 Student Scholarship Award
      • 2021, AAAI 2021 Student Travel Award
      • 2021, MSU Dissertation Completion Fellowship
      • 2020, CIKM 2020 Student Travel Award
      • 2020, KDD 2020 Student Travel Award
      • 2019, KDD 2019 Student Travel Award
      • 2018, Bytedance Research Collaboration Award (PI: Dr. Jiliang Tang, based on my research)
      • 2018, RecSys 2018 Student Travel Award
      • 2018, KDD 2018 Student Travel Award
      • 2018, Criteo Faculty Research Award (PI: Dr. Jiliang Tang, based on my research)
      • 2018, SDM 2018 Student Travel Award
      • 2017, CIKM 2017 Student Travel Award
    • USTC:
      • 2018, Outstanding Master's Thesis Award of Anhui Computer Federation (Top 15 in Anhui Province)
      • 2017, Outstanding Graduate Award of USTC
      • 2016, National Scholarship for Graduate Students of China (Highest National Scholarship)
      • 2016, Graduate Student First-class Academic Scholarship
      • 2015, Graduate Student First-class Academic Scholarship
      • 2014, Graduate Student First-class Academic Scholarship
    • UESTC:
      • 2014, Outstanding Graduate Award of UESTC
      • 2014, Outstanding Graduation Thesis (1% in university, 1/205 in department)
      • 2012, First Prize of Contemporary Undergraduate Mathematical Contest in Modeling of China (Sichuan)
      • 2012, First Prize of Mathematical Contest in Modeling (3/200, only freshman team)
      • 2011, Futong Scholarship (3/600)

    Teaching

    • 2021 Aug, Conference Tutor, Deep Learning for Recommendations: Fundamentals and Advances, IJCAI'21
    • 2021 Apr, Conference Tutor, Deep Recommender System: Fundamentals and Advances, WWW'21
    • 2020 Nov, Conference Tutor, Deep Reinforcement Learning for Online Advertising, INFORMS'20
    • 2019 Nov, Guest Lecturer, Urban Security and Crime Prediction, East China Normal University
    • 2019 Aug, Guest Lecturer, Deep Reinforcement Learning for Online Advertising, Shandong University
    • 2019 Jul, Guest Lecturer, Urban Security and Crime Prediction, Beijing University of Chemical Technology
    • 2019 Jul, Invited Talk, Deep Reinforcement Learning based Recommendations, TAL Education Group
    • 2018 Nov, Lecturer, Deep Reinforcement Learning for E-commerce, Leiphone Online Course
    • 2018 Aug, Invited Talk, Deep Reinforcement Learning based Recommendations, Kuaishou.com
    • 2015 Fall, Teaching Assistant, Machine Learning and Knowledge Discovery (for graduate students in USTC)
    • 2013 Spring, Teaching Assistant, Computer Science Research (for undergraduate students in UESTC)

    Internships

    • 2021 Jan-Apr, Research Intern, RL and AutoML for Recommendation/Advertising, AML Research@Bytedance
    • 2020 May-Aug, Research Engineer Intern, AutoML and RL for Search/Rec/Ads DNN Search, AI Foundation@Linkedin
    • 2019 May-Dec, Research Intern, RL and AutoML for Recommendation/Advertising, Applied Machine Learning@Bytedance
    • 2018 Sep, Invited Visiting Scholar, Reinforcement Learning Based Computational Advertising, Data-Advertising@Bytedance
    • 2018 May-Aug, Research Intern, Reinforcement Learning Based Recommender System, Data Science Lab@JD.com
    • 2017 Jun-Aug, Research Intern, Deep Learning Based Recommender System, Data Science Lab@JD.com