Nuoku: Nengjun

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Nengjun Zhu is currently with the School of Computer Engineering and Science, Shanghai University. He is a master supervisor, CCF YOCSEF Shanghai AC Secretary, CCF TCCC Executive Member, and PRIJCAI 2022 Local Chair. He received a bachelor degree from Sichuan University and a Ph.D. degree from Shanghai Jiao Tong University, both in computer science and technology. Nengjun Zhu has been a visiting Ph.D. student in the Management Science and Information Systems Department at Rutgers, the State University of New Jersey, and an intern researcher at Baidu Research. His research interests include recommender systems, data mining, and decision support systems, which are supported by many national and provincial government research grants as well as industry partners. (version: 2022-10)

* Students who are interested in doing research in these fields are welcome to join our team! Welcome to contact me. However, there is no plan to recruit an international student this year.

We organize a workshop on ICDM 2022. April 23, 2022, NeuRec

Nengjun Zhu is as one of the Local and Virtual Conference Chair to co-organize PRIJCAI2022. March 31, 2022, PRICAI2022

We got one paper, entitled "Predicting a Person's Next Activity Region with a Dynamic Region-Relation-Aware Graph Neural Network", accepted by TKDD. March 31, 2022

Our paper entitled "Learning a Hierarchical Intent Model for Next-Item Recommendation" is available on TOIS. September 27, 2021

Shanghai University, Lecturer (2021.06 - Now ). Shanghai University

Baidu Research Intern (2019.10 - 2020.04). Baidu Research, Baidu Inc.

Visiting Ph.D. Student (2018.09 - 2019.09). Rutgers, the State University of New Jersey

Shanghai Jiao Tong University (SJTU), Shanghai, China

2015.09 – 2021.03

Ph.D. student in Dept. of Computer Science and Engineering

Sichuan University (SCU), Chengdu, China

2011.09 – 2015.06

Bachelor in College of Computer Science

Research on Recommendation Approach based on Fusion Learning of Intent and Preference Representation. National Natural Science Foundation of China under Grant No. 62202282.

2023 – 2025

Intention and Preference Fusion Modeling-based Recommender Systems. Shanghai Youth Science and Technology Talents Sailing Program (No. 22YF1413700)

2022 – 2025

Multi-level Learning of Social Perception Data-based Service Recommendations. China National Science Foundation (No.61472253)

2015 – 2021

Participator, Leader: Jian Cao

Research and Implementation of Patient Information Sharing Platform. Shanghai Committee of Science and Technology, China (No.15411952502)

2016 – 2021

Participator, Leader: Jian Cao
Products => MDT:Multi-Disciplinary Treatment System [Homepage Link] | BCDB:Breast Cancer Database [Homepage Link]

Publications Google Scholar

Yuan Sui, Shanshan Feng, Huaxiang Zhang, Jian Cao, Liang Hu, Nengjun Zhu. "Learning Causal Representations for Multi-Hop Question Answering over Knowledge Graphs." Knowledge-Based Systems. 2022. Accepted. (中科院一区)

Nengjun Zhu, Jian Cao, Xinjiang Lu, Chuanren Liu, Hao Liu, Yanyan Li, Xiangfeng Luo, Hui Xiong. "Predicting a Person’s Next Activity Region with a Dynamic Region-Relation-Aware Graph Neural Network." ACM Transactions on Knowledge Discovery from Data (TKDD). 2022. Accepted. (CCF-B)

Nengjun Zhu, Jian Cao, Xinjiang Lu, Hui Xiong. "Learning a Hierarchical Intent Model for Next-Item Recommendation." ACM Transactions on Information Systems (TOIS). 2021. vol. 40(2), pp. 1-28 (CCF-A)

Nengjun Zhu, Jian Cao, Xinjiang Lu, Qi Gu. "Leveraging pointwise prediction with learning to rank for top-N recommendation." World Wide Web. Springer US, 2020. vol. 24 (1), pp. 375-396. (CCF-B)

Nengjun Zhu, Jian Cao, Kunwei Shen, Xiaosong Chen, and Siji Zhu. "A Decision Support System with Intelligent Recommendation for Multi-Disciplinary Medical Treatment." ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM). ACM, 2020. vol. 16 (1s), Article 33. [PDF] (CCF-B)

Yang Yang, Nengjun Zhu, Yifeng Wu, Jian Cao, Dechuan Zhan, and Hui Xiong. "A Semi-Supervised Attention Model forIdentifying Authentic Sneakers." Big Data Mining and Analytics Journal. IEEE, 2020. [PDF] [Homepage Link]

顾扬,曹健, 朱能军, 陈小松,沈坤炜. "多层次个性化临床路径的推荐方法." 计算机集成制造系统:1-18. 2021-12

Nengjun Zhu, Jieyun Huang, Jian Cao, and Shanshan Feng. "Learning User Embeddings based on Long Short-Term User Group Modeling for Next-Item Recommendation." in Proceedings of CCF Conference on Computer Supported Cooperative Work and Social Computing. Springer, 2022. Accepted.

Haoran Xin, Xinjiang Lu, Nengjun Zhu, Tong Xu, Dejing Dou, Hui Xiong "CAPTOR: A Crowd-Aware Pre-Travel Recommender System for Out-of-Town Users." in Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR). ACM, 2022. (CCF-A)

Zhengfei Shen, Jian Cao, Nengjun Zhu. "A New k-Nearest Neighbors Algorithm for Learning from Multiple Experts' Uncertain Decisions." in Proceedings of the IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2021. (CCF-C)

Yang Gu, Jian Cao, Nengjun Zhu. "A Method of Multilevel Personalized Clinical Path Recommendation." in The Chinese Conference on Business Process Management (CBPM2021). 2021.

Nengjun Zhu, Jian Cao. "Enhancing Cross-domain Recommendation through Preference Structure Information Sharing." in Proceedings of the IEEE International Conference on Web Services (ICWS). IEEE, 2020. (CCF-B, Research paper)

Zixuan Yuan, Hao Liu, Yanchi Liu, Denghui Zhang, Fei Yi, Nengjun Zhu, Hui Xiong. "Spatio-temporal dual graph attention network for query-poi matching." in Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR). ACM, 2020. (CCF-A, Research paper)

Nengjun Zhu, Jian Cao, Yanchi Liu, Yang Yang, Haochao Ying, and Hui Xiong. "Sequential Modeling of Hierarchical User Intention and Preference for Next-item Recommendation." in Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM). ACM, 2020. [PDF] (CCF-B, Research paper)

Nengjun Zhu and Jian Cao. "CPL: A Combined Framework of Pointwise Prediction and Learning to Rank for top-N Recommendations with Implicit Feedback." in Proceedings of the International Conference on Web Information Systems Engineering (WISE). Springer, 2019. [PDF] [PPT] (CCF-C, Long paper)

Nengjun Zhu, Jian Cao, and Yang Zhang. "An Adaptive k-NN Classifier for Medical Treatment Recommendation under Concept Drift." in Proceedings of CCF Conference on Computer Supported Cooperative Work and Social Computing. Springer, 2018, pp. 546-556. [PDF] [Poster]

Nengjun Zhu and Jian Cao. "GTRM: A Top-N Recommendation Model for Smartphone Applications." in Proceedings of the IEEE International Conference on Web Services (ICWS). IEEE, 2017, pp. 309-316. [PDF] (CCF-B, Research paper)

Jian Cao, Yijing Lu and Nengjun Zhu. "Service Package Recommendation for Mashup Development Based on a Multi-level Relational Network." in Proceedings of the International Conference on Service-Oriented Computing (ICSOC). Springer, 2016 pp. 666-674. [PDF] (CCF-B, Short paper)

CCF协同计算专委执委、CCF YOCSEF上海AC委员、上海市高校重点创新团队骨干成员

PRICAI2022 Local Chair, IEEE ICDM 2022 - NeuRec Workshop PC Chair

Reviewer：KDD2018, KDD2019, CIKM2018, ICDM2019, PRIJCAI2021, ICDM Workshop 2021, IEEE Intelligent Systems, International Journal of Data Science and Analytics, Wireless Communications and Mobile Computing

NENGJUN ZHU Ph.D./Lecturer

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