Currently, I am a Senior Scientist at CFRA, IHPC, A*STAR, Singapore. I obtained my Ph.D. degree from the School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore in 2018. My supervisors are Prof. Zhang Jie and Dr. Xu Chi. My research topic is artificial intelligence, specializing in recommender systems. I mainly focus on applying data mining and machine learning techniques (e.g., deep learning) to design effective algorithms to enhance the performance of recommender systems in various domains, such as e-commerce, location-based social networks (LBSNs), multi-media, smart learning and so forth.  

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Research Interests:

• Recommender Systems, User Modelling and Social Network Analysis

• Machine Learning (Deep Learning and Reinforcement Learning) and Data Mining

Publications:

2024

• Zhu Sun, Hongyang Liu, Xinghua Qu, Kaidong Feng, Yan Wang,Yew Soon Ong. Large Language Models for Intent-Driven Session Recommendations. The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2024

• Zhu Sun, Kaidong Feng, Jie Yang, Xinghua Qu, Hui Fang, Yew-Soon Ong,Wenyuan Liu. Adaptive In-Context Learning with Large Language Models for Bundle Generation. The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2024

• Huizhong Guo, Dongxia Wang, Zhu Sun, Haonan Zhang, Jinfeng Liu, Jie Zhang. Configurable Fairness for New Item Recommendation Considering Entry Time of Items. The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2024

• Lu Zhang, Chen Li, Yu Lei, Zhu Sun and Guanfeng Liu. An Empirical Analysis on Multi-turn Conversational Recommender Systems. The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2024

• Youchen Sun, Zhu Sun, Yingpeng Du, Jie Zhang, Yew-Soon Ong. Self-Supervised Denoising through Independent Cascade Graph Augmentation for Robust Social Recommendation. The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024

• Yingpeng Du, Ziyan Wang, Zhu Sun, Yining Ma, Hongzhi Liu, Jie Zhang. Disentangled Multi-interest Representation Learning for Sequential Recommendation. The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024

• Zhu Sun, Kaidong Feng, Jie Yang, Hui Fang, Xinghua Qu, Yew-Soon Ong, Wenyuan Liu. Revisiting Bundle Recommendation for Intent-aware Product Bundling. ACM Transactions on Recommender Systems (TORS), 2024

• Xinghua Qu, Zhu Sun, Shanshan Feng, Caishun Chen, Tian Tian. Breaking the Silence: Whisper-Driven Emotion Recognition in AI Mental Support Models. IEEE Conference on Artificial Intelligence (CAI), 2024

• Shanshan Feng, Haoming Lyu, Fan Li, Zhu Sun, Caishun Chen. Where to Move Next: Zero-shot Generalization of LLMs for Next POI Recommendation. IEEE Conference on Artificial Intelligence (CAI), 2024

• Shuang Wang, He Zhang, Michael Sheng, Xiaoping Li, Zhu Sun, Taotao Cai, Wei Emma Zhang, Jian Yang, Qing Gao. A Survey on Truth Discovery: Concepts, Methods, Applications and Opportunities. IEEE Transactions on Big Data (TBD), 2024 (Impact Factor: 7.2)

2023

• Zhu Sun, Yu Lei, Lu Zhang, Chen Li, Yew-Soon Ong, Jie Zhang. A Multi-Channel Next POI Recommendation Framework with Multi-Granularity Check-in Signals. ACM Transactions on Information Systems (TOIS), 2023 (Impact Factor: 4.797) [Accepted]

• Yatong Sun, Xiaochun Yang, Zhu Sun, Bin Wang. BERD+: A Novel Sequential Recommendation Framework For Combating Unreliable Data. ACM Transactions on Information Systems (TOIS), 2023 (Impact Factor: 4.797) [Accepted]

• Qin Ying, Hui Fang, Zhu Sun, Yew Soon Ong. Understanding Diversity in Session-based Recommendation. ACM Transactions on Information Systems (TOIS), 2023 (Impact Factor: 4.797) [Accepted]

• Yatong Sun, Xiaochun Yang, Zhu Sun, Bin Wang, Yan Wang. Theoretically Guaranteed Bidirectional Data Rectification for Robust Sequential Recommendation.  The 37th Annual Conference on Neural Information Processing Systems (NeurIPS), 2023

• Youchen Sun, Zhu Sun, Xiao Sha, Jie Zhang, Yew-Soon Ong. Disentangling Motives behind Item Consumption and Social Connection for Mutually-enhanced Joint Prediction. The 17th ACM Conference on Recommender  Systems (RecSys), 2023

• Jiajie Zhu, Yan Wang, Feng Zhu, Zhu Sun. Domain Disentanglement with Interpolative Data Augmentation for Dual-Target Cross-Domain Recommendation. The 17th ACM Conference on Recommender Systems (RecSys), 2023 

• Xinghua Qu, Hongyang Liu, Zhu Sun, Xiang Yin, Yew-Soon Ong, Lu Lu, Zejun Ma. Towards Building Voice-based Conversational Recommender Systems: Datasets, Potential Solutions, and Prospects. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023 [Accepted]

• Huizi Wu, Hui Fang, Zhu Sun, Cong Geng, Yew-Soon Ong. A Generic Reinforced Explainable Framework with Knowledge Graph for Session-based Recommendation. IEEE International Conference on Data Engineering (ICDE), 2023 [Accepted]

• Jinze Wang, Lu Zhang, Zhu Sun, Yew-Soon Ong. Meta-Learning Enhance Next POI Recommendation with Auxiliary Cities. The 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2023 [Accepted]  (🏅 Best Student Paper Nomination and Student Registration Award)

2022

• Zhu Sun, Jie Yang, Kaidong Feng, Hui Fang, Xinghua Qu, Yew-Soon Ong. Revisiting Bundle Recommendation: Datasets, Tasks, Challenges and Opportunities for Intent-aware Product Bundling. The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022. [PDF]

• Zhu Sun, Hui Fang, Jie Yang, Xinghua Qu, Hongyang Liu, Di Yu, Yew-Soon Ong, Jie Zhang. DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 (Impact Factor: 24.31) [arXiv Preprints] (🏅Journal Paper of the Year Award, RecSys 2023)

• Lu Zhang, Zhu Sun, Ziqing Wu, Jie Zhang, Ong Yew Soon, Xinghua Qu. Next Point-of-Interest Recommendation with Inferring Multi-step Future Preference. The 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022 [PDF].

• Lu Zhang, Zhu Sun, Jie Zhang, Yiwen Wu, Yunwen Xia. Conversation-based Adaptive Relational Translation Method for Next POI Recommendation with Uncertain Check-ins. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022 (Impact Factor: 14.26) [PDF]. 

• Xiao Sha, Zhu Sun, Jie Zhang, Yew Soon Ong. Who Wants to Shop with You: Joint Product-Participant Recommendation for Group-Buying Service. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022 (Impact Factor: 14.26) [PDF].

• Xinghua Qu, Pengfei Wei, Mingyong Gao, Zhu Sun, Yew-Soon Ong, Zejun Ma. Synthesizing Audio Adversarial Examples for Automatic Speech Recognition. The 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022 [PDF].

• Xinghua Qu, Ong Yew Soon, Abhishek Gupta, Pengfei Wei, Zhu Sun. Importance Prioritized Policy Distillation. The 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022 [PDF].

• Zhuoyi Lin, Sheng Zang, Rundong Wang, Zhu Sun, Chee Keong Kwoh, Chi Xu. Attention over Self-attention: Dynamic Re-ranking with User Intentions for Recommendation. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2022 (Impact Factor: 6.977). [Accepted, arXiv Preprints]

2021

• Zhu Sun, Chen Li, Yu Lei, Lu Zhang, Jie Zhang, Shunpan Liang. Point-of-Interest Recommendation for Users-Businesses with Uncertain Check-ins. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2021 (Impact Factor: 4.935). [PDF]

• Yatong Sun, Bin Wang, Zhu Sun, Xiaochun Yang. Does Every Data Instance Matter? Enhancing Sequential Recommendation by Eliminating Unreliable Data. The 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021 (13.9% of acceptance). [PDF]

• Xinghua Qu, Yew Soon Ong, Abhishek Gupta,  Zhu Sun. Adversary Agnostic Robust Deep Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 (Impact Factor: 8.793) [Accepted]. 

• Hongyang Liu, Zhu Sun, Xinghua Qu, Fuyong Yuan.  Top-aware Recommender Distillation with Deep Reinforcement Learning. Information Sciences (INS), 2021 (Impact Factor: 6.795). [PDF]

• Xiao Sha, Zhu Sun, Jie Zhang. Hierarchical Attentive Knowledge Graph Embedding for Personalized Recommendation. Electronic Commerce Research and Applications (ECRA), 2021 (Impact Factor: 6.014). [PDF] [arXiv Preprints]

• Xiao Sha, Zhu Sun, Jie Zhang. Disentangling Multi-facet Social Relations for Recommendation. IEEE Transactions on Computational Social Systems (IEEE TCSS), 2021 (Impact Factor: 5.360). [PDF]

2020

• Zhu Sun, Di Yu, Hui Fang, Jie Yang, Xinghua Qu, Jie Zhang. Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison. The 14th ACM Conference on Recommender Systems (RecSys), 2020 (18% of acceptance). [PDF]

• Lu Zhang, Zhu Sun, Jie Zhang, Yu Lei, Chen Li, Ziqing Wu. An Interactive Multi-Task Learning Framework for Next POI Recommendation with Uncertain Check-ins. The 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020 (12.6% of acceptance). [PDF]

• Qing Guo, Zhu Sun, Jie Zhang, Yin Leng Theng. An Attentional Recurrent Neural Network for Personalized Next Location Recommendation. The 34th AAAI Conference on Artificial Intelligence (AAAI), 2020 (20.6% of acceptance).[PDF]

• Lu Zhang, Zhu Sun, Jie Zhang, Horst Kloeden, Felix Klanner. Modeling Hierarchical Category Transition for Next POI Recommendation with Uncertain Check-ins. Information Sciences (INS), 2020 (Impact Factor: 5.524). [PDF]

• Xinghua Qu, Zhu Sun, Yew Soon Ong, Pengfei Wei, Abhishek Gupta. Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policy. IEEE Transactions on Cognitive and Developmental Systems (TCDS), 2020 (Impact Factor: 2.755). [PDF]

• Xin Zhou, Zhu Sun, Guibing Guo, Yuan Liu. Modelling Temporal Dynamics and Repeated Behaviors for Recommendation. The 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020 (21% of acceptance). [PDF]

• Guibing Guo, Xin Zhou, Zhu Sun, Yuan Liu. Multi-facet User Preference Learning for Fine-grained Item Recommendation. Neurocomputing (NeuCom), 2020 (Impact Factor: 4.072). [PDF]

2019

• Zhu Sun, Qing Guo, Jie Yang, Hui Fang, Guibing Guo, Jie Zhang, Robin Burke. Research Commentary on Recommendations with Side Information: A Survey and Research Directions. Electronic Commerce Research and Applications (ECRA), 2019 (5-Year Impact Factor: 3.661). [PDF]

• Qing Guo, Zhu Sun, Jie Zhang, Yin Leng Theng. Modeling Heterogeneous Influences for Point-of-Interest Recommendation in Location-Based Social Networks. The 19th International Conference on Web Engineering (ICWE), 2019 (Short Paper). [PDF]

• Qing Guo, Zhu Sun, Yin Leng Theng. Exploiting Side Information for Recommendation. The 19th International Conference on Web Engineering (ICWE), 2019 (Tutorial). [PDF]

2018

• Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, Longkai Huang, Chi Xu. Recurrent Knowledge Graph Embedding for Effective Recommendation. The 12th ACM Conference on Recommender Systems (RecSys), 2018 (17.7% of acceptance). [PDF] [Code]

• Yun Liu, Huihuai Qiu, Guibing Guo, Zhu Sun, Jie Zhang, Hai Thanh Nguyen. BPRH: Bayesian Personalized Ranking for Heterogeneous Implicit Feedback. Information Sciences (INS), 2018 (Impact Factor: 5.524). [PDF]

2017

• Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, Yu Chen, Chi Xu. MRLR: Multi-level Representation Learning for Personalized Ranking in Recommendation. The 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017 (26.0% of acceptance). [PDF] [Code]

• Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon. Exploiting both Vertical and Horizontal Dimensions of Feature hierarchy for Effective Recommendation. The 31st AAAI Conference on Artificial Intelligence (AAAI), 2017 (24.6% of acceptance). [PDF] [Code]

• Chang Xu, Jie Zhang, Zhu Sun. Online Reputation Fraud Campaign Detection in User Ratings. The 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017 (26% of acceptance). [PDF]

• Wenjie Pei, Jie Yang, Zhu Sun, Jie Zhang, Alessandro Bozzon, David Tax. Interactive Attention-Gated Recurrent Networks for Recommendation. The 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017 (21% of acceptance). [PDF]

• Zhu Sun, Guibing Guo, Jie Zhang. Learning Hierarchical Category Influence on both Users and Items for Effective Recommendation. The 32nd ACM Symposium on Applied Computing (SAC), 2017 (24% of acceptance). [PDF] [Code]

• Zhu Sun, Guibing Guo, Jie Zhang, Chi Xu. A Unified Latent Factor Model for Effective Category-Aware Recommendation. The 25th ACM Conference on User Modeling, Adaptation and Personalization (UMAP), 2017 (Extended Abstract). [PDF]

• Qing Guo, Zhu Sun, Jie Zhang, Qi Chen, Yin-Leng Theng. Aspect-Aware Point-of-Interest Recommendation with Geo-Social Influence. The 25th ACM Conference on User Modeling, Adaptation and Personalization (UMAP), 2017 (Late Breaking Results). [PDF]

• Jie Yang, Zhu Sun, Alessandro Bozzon, Jie Zhang, Martha Larson. CitRec 2017: International Workshop on Recommender Systems for Citizens. 

2016

• Jie Yang, Zhu Sun, Alessandro Bozzon, Jie Zhang. Learning Hierarchical Feature Influence for Recommendation by Recursive Regularization. The 10th ACM Conference on Recommender Systems (RecSys), 2016 (18.2% of acceptance). [PDF] [Code]

• Zhu Sun, Guibing Guo, Jie Zhang. Effective Recommendation with Category Hierarchy. The 24th ACM Conference on User Modelling, Adaptation and Personalization (UMAP), 2016 (Extended Abstract). [PDF]

• Huihuai Qiu, Jie Zhang, Guibing Guo, Zhu Sun, Haithanh Nguyen. TBPR: Trinity Preference based Bayesian Personalized Ranking for Multivariate Implicit Feedback. The 24th ACM Conference on User Modelling, Adaptation and Personalization (UMAP), 2016 (Extended Abstract). [PDF]

2015

• Zhu Sun, Guibing Guo, Jie Zhang. Exploiting Implicit Item Relationships for Recommender Systems. The 23rd International Conference on User Modeling, Adaptation and Personalization (UMAP), 2015 (28% of acceptance). [PDF] [Code] 

• Zhu Sun. Exploiting Item and User Relationships for Recommender Systems. The 23rd International Conference on User Modeling, Adaptation and Personalization (UMAP), 2015 (Doctoral Consortium). [PDF]

• Guibing Guo, Jie Zhang, Zhu Sun, Neil Yorke-Smith. LibRec: A Java Library for Recommender Systems. The 23rd International Conference on User Modeling, Adaptation and Personalization (UMAP), 2015 (Demo Paper). [PDF] 

Ph.D. Thesis:

• Exploiting Item Relationships for Effective Recommendation. 2018 [PDF]

Academic Services:

Conference Program Committee (PC) Member:

• Senior PC of IUI; PC of AAAI, IJCAI, KDD, CIKM, SIGIR, RecSys, UMAP, 2024

• Local Chair of RecSys; Senior PC of TheWebConf, IUI; PC of AAAI, IJCAI, KDD, CIKM, SIGIR, RecSys, UMAP, SDM 2023; 

• Senior PC of IUI; PC of AAAI, IJCAI, SIGIR, KDD, CIKM, RecSys, UMAP, ICWE, WISE 2022

• Senior PC of IJCAI, ACM IUI, PC of IJCAI Demo track, AAAI, ACM CIKM, RecSys, IUI, UMAP, ICWE, IEEE ICTAI 2021

• IJCAI (Main track and Demo track), CIKM (Main track and Demo track), RecSys, UMAP, IUI 2020

• IJCAI (Main track and Demo track), CIKM, RecSys, ICWE,  UMAP, SAC, AI 2019

• Local Chair of UMAP; PC Member of SAC, WI 2018 

• The organizer of ACM RecSys 2017 Workshop on Recommender Systems for Citizens (CitRec 2017)

• ACM UMAP 2016 Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization (IFUP 2016)

Journal Reviewer:

• Associate Editor with ACM Transactions on Recommender Systems (TORS)

• Associate Editor with Electronic Commerce Research and Applications (ECRA)

• IEEE Transactions on Knowledge and Data Engineering (TKDE)

• ACM Transactions on Information Systems (TOIS)

• Journal of Artificial Intelligence

• Information Sciences (INS)

• Knowledge-Based Systems (KBS)

• Engineering Applications of Artificial Intelligence (EAAI)

• Expert Systems With Applications

Student Volunteer:

• IJCAI 2017, AAAI 2017, ACM UMAP 2015 - 2016, WI-IAT 2015

Teaching:

• COMP1000 - Introduction to Computer Programming

• COMP2110 - Web Technology

• COMP3120 - Advanced Web Technology

• COMP7873 - Research Top in Computing

Awards & Honors:

• UMAP 2015-2017, SAC 2017, AAAI 2017 Student Travel Grant

• Provincial Outstanding Graduate 2013, Hebei Province Education Department, China

• National Motivational Scholarship 2012, MOE of China

• National Scholarship 2010 - 2011, MOE of China