臧天梓，2023年博士毕业于上海交通大学计算机科学与技术专业，导师朱燕民教授(被引次数：10417，h指数：52.，i10指数：195)，获上海交通大学优秀毕业生称号，同年入职南京航空航天大学计算机科学与技术学院。主要研究方向为数据挖掘、深度学习，累计发表高水平学术期刊和会议论文26篇，均为SCI或EI收录论文，其中包括CCF A类期刊论文6篇，CCF B类期刊和会议论文12篇。担任IEEE TMC、AAAI、SIGIR、ECML/PKDD、ICPADS等顶级期刊和会议审稿人。

现招收计算机科学与技术、电子信息硕士研究生，欢迎对数据挖掘和深度学习感兴趣的同学报考我的研究生，也欢迎本科生参与到我的研究课题中！

个人邮箱：zangtianzi@nuaa.edu.cn

办公地点：计算机科学与技术学院204室

部分代表性论文：

1. Tianzi Zang, Yanmin Zhu, Haobing Liu, Ruohan Zhang, Jiadi Yu: “A Survey on Cross-domain Recommendation: Taxonomies, Methods, and Future Directions”. ACM TOIS (2023) (CCF A)

2. Tianzi Zang, Yanmin Zhu, Ruohan Zhang, Chunyang Wang, Ke Wang, Jiadi Yu: "Contrastive Multi-View Interest Learning for Cross-Domain Sequential Recommendation". ACM TOIS (2023) (CCF A)

3. Ke Wang, Yanmin Zhu, Tianzi Zang, Chunyang Wang, Kuan Liu, Peibo Ma: “Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation”. ACM TOIS (2023) (CCF A)

4. Mengyuan Jing, Yanmin Zhu, Tianzi Zang, Ke Wang: “Contrastive Self-supervised Learning in Recommender Systems: A Survey”. ACM TOIS (2023) (CCF A)

5. Ke Wang, Yanmin Zhu, Tianzi Zang, Chunyang Wang, Mengyuan Jing: "Review-Enhanced Hierarchical Contrastive Learning for Recommendation". AAAI (2024) (CCF A)

6. Xian Zhou, Yanyan Shen, Linpeng Huang, Tianzi Zang, Yanmin Zhu: “Multi-Level Attention Networks for Multi-Step Citywide Passenger Demands Prediction. IEEE TKDE (2021) (CCF A)

7. Tianzi Zang, Yanmin Zhu, Yanan Xu, Jiadi Yu: “Jointly Modeling Spatio-Temporal Dependencies and Daily Flow Correlations for Crowd Flow Prediction.” ACM TKDD (2021) (CCF B)

8. Tianzi Zang, Yanmin Zhu, Chen Gong, Haobing Liu, Bo Li: “Modeling Dynamic Social Behaviors with Time-Evolving Graphs for User Behavior Predictions.” DASFAA (2021) (CCF B)

9. Tianzi Zang, Yanmin Zhu, Jing Zhu, Yanan Xu, Haobing Liu: “MPAN: Multi-parallel attention network for session-based recommendation.” Neurocomputing  (2022) (中科院二区)

10. Tianzi Zang, Yanmin Zhu, Xinrui Huang, Xinchen Yang, Qiuxia Chen, Jiadi Yu, Feilong Tang: “Enhancing length of stay prediction by learning similarity-aware representations for hospitalized patients.” Artificial Intelligence in Medicine (2023) (CCF C)

11. Ke Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Chunyang Wang: “Learning Aspect-Aware High-Order Representations from Ratings and Reviews for Recommendation.” ACM TKDD (2023) (CCF B)

12. Mengyuan Jing, Yanmin Zhu, Yanan Xu, Haobing Liu, Tianzi Zang, Chunyang Wang, Jiadi Yu: “Learning Shared Representations for Recommendation with Dynamic Heterogeneous Graph Convolutional Networks.” ACM TKDD (2023) (CCF B)

13. Chunyang Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Ke Wang, Jiadi Yu: “Multifaceted Relation-aware Meta-learning with Dual Customization for User Cold-start Recommendation.” ACM TKDD (2023) (CCF B)

14. Ruohan Zhang, Tianzi Zang, Yanmin Zhu, Chunyang Wang, Ke Wang, Jiadi Yu: “Disentangled Contrastive Learning for Cross-Domain Recommendation.” DASFAA (2023) (CCF B)

15. Haobing Liu, Yanmin Zhu, Tianzi Zang, Yanan Xu, Jiadi Yu, Feilong Tang: “Jointly Modeling Heterogeneous Student Behaviors and Interactions among Multiple Prediction Tasks.” ACM TKDD (2022) (CCF B)

16. Ke Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Chunyang Wang, Kuan Liu: “Inter- and Intra-Domain Relation-Aware Heterogeneous Graph Convolutional Networks for Cross-Domain Recommendation.” DASFAA (2022) (CCF B)

17. Mengyuan Jing, Yanmin Zhu, Tianzi Zang, Jiadi Yu, Feilong Tang: “Graph Contrastive Learning with Adaptive Augmentation for Recommendation.” ECML/PKDD (2022) (CCF B)

18. Chunyang Wang, Yanmin Zhu, Haobing Liu, Wenze Ma, Tianzi Zang, Jiadi Yu: “Enhancing User Interest Modeling with Knowledge-Enriched Itemsets for Sequential Recommendation.” CIKM (2021) (CCF B)

19. Chunyang Wang, Yanmin Zhu, Tianzi Zang, Haobing Liu, Jiadi Yu: “Modeling Inter-station Relationships with Attentive Temporal Graph Convolutional Network for Air Quality Prediction.” WSDM (2021) (CCF B)

20. Haobing Liu, Yanmin Zhu, Tianzi Zang, Jiadi Yu, Haibin Cai: “Jointly Modeling Individual Student Behaviors and Social Influence for Prediction Tasks.” CIKM (2020) (CCF B)

• 2018.9 -- 2023.6

  上海交通大学       博士研究生毕业

• 2014.9 -- 2018.6

  西北工业大学       大学本科毕业

• [1]神经网络、推荐系统
• [2]城市计算，时空数据挖掘
• [3]人工智能、数据挖掘、深度学习