Chaochao Chen

News

• May 2025. One paper was accepted by ACM TOIS.

• May 2025. Two papers got accepted by KDD'25. 

• May 2025. Two papers got accepted by ICML'25. 

• April 2025. One paper got accepted by IJCAI'25. 

• April 2025. Two papers got accepted by SIGIR'25. 

• February 2025. One paper got accepted by JMLR. 

• January 2025. One paper got accepted by ICLR'25. 

• January 2025. Two papers got accepted by TheWebConf'25. 

• December 2024. Four papers got accepted by AAAI'25. 

• October 2024. One paper was accepted by WSDM'25.

• October 2024. One paper was accepted by Cell Patterns.

• October 2024. One paper was accepted by ACM TOIS.

• September 2024. Four papers got accepted by NeurIPS'24.

• September 2024. One paper got accepted by EMNLP'24.

• August 2024. One paper was accepted by IEEE TKDE.

• July 2024. One paper got accepted by CIKM'24. 

• May 2024. One paper got accepted by KDD'24. 

• May 2024. One paper got accepted by ICWS'24. 

• May 2024. Two papers got accepted by ICML'24. 

• April 2024. I am invited to server as area chair of  NeurIPS'24.

• April 2024. One paper got accepted by IJCAI'22. 

• March 2024. Two papers got accepted by SIGIR'24. 

• February 2024. One paper got accepted by CVPR'24. 

• December 2023. Two papers got accepted by AAAI'24. 

• December 2023. One paper got accepted by ICDE'24. 

• September 2023. One paper got accepted by NeurIPS'23. 

• August 2023. Two papers got accepted by CIKM'23. 

• August 2023. Six papers got accepted by ACM MM'23. 

• July 2023. We released a paper on Federated Large Language Model.

• May 2023. Two papers got accepted by ICWS'23. 

• May 2023. One paper got accepted by ACL'23. 

• April 2023. Three papers got accepted by IJCAI'23. 

• April 2023. One paper got accepted by CHES. 

• March 2023. We launched a special issue named "Advanced Analyses and Algorithms for Trustworthy AI Systems and Applications" on Mathematics (SCI, IF=2.592). 

• January 2023. Four papers got accepted by TheWebConf'23. 

• December 2022. One paper received the Outstanding Paper Award of IEEE UIC'23. 

• December 2022. One paper got accepted by ICDE'23. 

• December 2022. One paper was accepted by IEEE TKDE.

• November 2022. I will give a keynote speech at ICDM NeuRec 2022.

• November 2022. One paper got accepted by AAAI'23.

• October 2022. One paper got accepted by ACM Transactions on the Web (TWEB). 

• October 2022. One paper receives the Best Paper Runner Up Award CIKM'22. 

• October 2022. Our paper receives the Best Paper Award of CIKM-FedGraph’22.

• September 2022. One paper was accepted by IEEE TKDE.

• August 2022. One paper got accepted by CIKM'22. 

• June 2022. One paper got accepted by ACM MM'22. 

• May 2022. One paper got accepted by KDD'22. 

• April 2022. Three papers got accepted by IJCAI'22. 

• April 2022. One paper got accepted by IEEE Transactions on Dependable and Secure Computing. 

• March 2022. Two papers got accepted by SIGIR'22. 

• January 2022. Two papers got accepted by TheWebConf'22. 

• November 2021. One paper got accepted by ICDE'22. 

• November 2021. Our paper  on Privacy Preserving Deep Neural Network was accepted by ACM TIST.

• November 2021. I joined College of Computer Science and Technology of Zhejiang University as a Distinguished Research Fellow. 

Short Bio

Dr. Chaochao Chen is currently a Distinguished Research Fellow at the College of Computer Science and Technology, Zhejiang University. Before that, He was a  Staff Algorithm Engineer at Ant Group, during July 2016 - October 2021. He got his Ph.D in Computer Science and Technology at Zhejiang University in 2016. He was also a visiting scholar at the Computer Science Department of University of Illinois at Urbana-Champaign during Sep. 2014 - Sep. 2015. His research mainly focuses on trustworthy machine learning,  privacy-preserving privacy preserving, and recommender systems. He has published more than 100 papers in peer reviewed journals and conferences. He won the Best Paper runner up award of CIKM'22 and Outstanding Paper award of UIC'22. He has also applied for more than 200 International and Chinese patents, and more than 100 of them have been issued. He is a senior member of IEEE and CCF.

Selected Publications (Full list at [Google Scholar] [Semantic Scholar] [DBLP])

(In the following list, '#' means 'Equal contribution' and '*' denotes 'Corresponding Author'.)

2025

• Zhenghong Lin, Yanchao Tan*, Jiamin Chen, Hengyu Zhang, Chaochao Chen, Shiping Wang, Carl Yang.

Tackling Federated Long-Tailed Learning via Synthetic Feature-Based Decoupled Training. Unified Heterogeneous Hypergraph Construction for Incomplete.

ACM TOIS 2025. (CCF A)  

• Jiajie Su, Chaochao Chen, Weiming Liu, Yuhang Wang, Yihao Wang, Zheqi Lv, Xiaolin Zheng, Jianwei Yin. 

Modality-Aware Diffusion Augmentation with Consistent Subspace Disentanglement for Session-based Recommendation.

KDD 2025. (CCF A)  

• Xiuyuan Wang, Chaochao Chen*, Weiming Liu, Xinting Liao, Fan Wang, Xiaolin Zheng. 

Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization. 

ICML 2025. (CCF A)  

• Xinting Liao, Weiming Liu, Jiaming Qian, Pengyang Zhou, Jiahe Xu, Wenjie Wang, Chaochao Chen, Xiaolin Zheng, Tat-Seng Chua. 

FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models. 

ICML 2025. (CCF A)  

• Huan Liu, Pengfei Jiao, Mengzhou Gao, Chaochao Chen, Di Jin.

Heterogeneous Temporal Hypergraph Neural Network.

IJCAI 2025. (CCF A)  

• Heyuan Huang, Xingyu Lou, Changwang Zhang, Chaochao Chen, Kuiyao Dong, Feng Lu, Han Lei, Yihao Wang, Wangchunshu Zhou and Jun Wang.

Training-free Periodic Interest Augmentation in Incremental Recommendation.

SIGIR 2025. (CCF A)  

• Pengyang Zhou, Chaochao Chen*, Weiming Liu, Wenkai Shen, Xinting Liao, Huarong Deng, Zhihui Fu, Jun Wang, Wu Wen and Xiaolin Zheng. 

Joint Item Embedding Dual-view Exploration and Adaptive Local-Global Fusion for Federated Recommendation.

SIGIR 2025. (CCF A) 

• Boxin Zhao, Lingxiao Wang, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Chaochao Chen, Mladen Kolar.

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback.

JMLR 2025. (CCF A) 

• Xiaohua Feng, Yuyuan Li, Chaochao Chen*, Li Zhang, Longfei Li, JUN ZHOU, Xiaolin Zheng. 

Controllable Unlearning for Image-to-Image Generative Models via ε-Constrained Optimization. 

ICLR 2025. (CCF A) 

• Weiming Liu, Chaochao Chen*, Jiahe Xu, Xinting Liao, Fan Wang, Xiaolin Zheng, Zhihui Fu, Ruiguang Pei, Jun Wang.

Joint Similarity Item Exploration and Overlapped User Guidance for Multi-Modal Cross-Domain Recommendation.

TheWebConf 2025. (CCF A) 

• Xiaohua Feng, Yuyuan Li, Fengyuan Yu, Li Zhang, Chaochao Chen, Xiaolin Zheng.

Plug and Play: Enabling Pluggable Attribute Unlearning in Recommender Systems.

TheWebConf 2025. (CCF A)

• Fan Wang, Chaochao Chen, Weiming Liu, Minye Lei, Jintao Chen, Yuwen Liu, Xiaolin Zheng, Jianwei Yin. 

DR-VAE: Debiased and Representation-enhanced Variational Autoencoder for Collaborative Recommendation. 

AAAI 2025. (CCF A)

• Li Zhang, Chaochao Chen*, Zhongxuan Han, Qiyong Zhong, Xiaolin Zheng. 

LoGoFair: Post-Processing for Local and Global Fairness in Federated Learning. 

AAAI 2025. (CCF A)

• Pengyang Zhou, Chaochao Chen, Weiming Liu, Xinting Liao, Wenkai Shen, Jiahe Xu, Zhihui Fu, Jun Wang, Wen Wu David, Xiaolin Zheng*. 

FedGOG: Federated Graph Out-of-Distribution Generalization with Diffusion Data Exploration and Latent Embedding Decorrelation.

AAAI 2025. (CCF A)

• Yihao Wang, Jiajie Su, Chaochao Chen, Meng Han, Chi Zhang, Jun Wang*. 

Sim4Rec: Data-Free Model Extraction Attack on Sequential Recommendation. 

AAAI 2025. (CCF A)

• Pengyang Zhou, Chaochao Chen, Weiming Liu, Xinting Liao, Fengyuan Yu, Zhihui Fu, Xingyu Lou, Wu Wen, Xiaolin Zheng∗, Jun Wang∗.

FedGF: Enhancing Structural Knowledge via Graph Factorization for Federated Graph Learning.

WSDM 2025. (CAAI A, CCF B)

2024

• Chaochao Chen, Xiaohua Feng, Yuyuan Li, Lingjuan Lyu, Jun Zhou, Xiaolin Zheng*, Jianwei Yin*.

Integration of Large Language Models and Federated Learning.

Cell Patterns. 

• Chaochao Chen, Yizhao Zhang, Yuyuan Li*, Jun Wang, Lianyong Qi, Xiaolong Xu, Xiaolin Zheng, Jianwei Yin.

Post-Training Attribute Unlearning in Recommender Systems.

ACM TOIS. (CCF A)

• Chaochao Chen, Jiaming Zhang, Yizhao Zhang, Li Zhang, Lingjuan Lyu, Yuyuan Li, Biao Gong, Chenggang Yan.

CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence.

NeurIPS 2024 (DB Track). (CCF A)

• Biao Gong, Shuai Tan, Yutong Feng, Xiaoying Xie, Yuyuan Li, Chaochao Chen, Kecheng Zheng, Yujun Shen, Deli Zhao

UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training.

NeurIPS 2024 (DB Track). (CCF A)

• Xinting Liao, Weiming Liu, Pengyang Zhou, Fengyuan Yu, Jiahe Xu, Jun Wang, Wenjie Wang, Chaochao Chen, Xiaolin Zheng

FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection.

NeurIPS 2024. (CCF A)

• Ziqi Yang, Zhaopeng Peng, Zihui Wang, Jianzhong Qi, Chaochao Chen, Weike Pan, Chenglu Wen, Cheng Wang, Xiaoliang Fan.

Federated Graph Learning for Cross-Domain Recommendation.

NeurIPS 2024. (CCF A)

• XiaoHua Feng, Chaochao Chen*, Yuyuan Li, Zibin Lin. 

Fine-grained Pluggable Gradient Ascent for Knowledge Unlearning in Language Models. 

EMNLP 2024. (CCF A)

• Xiaolin Zheng, Weiming Liu, Chaochao Chen*, Jiajie Su, Xinting Liao, Mengling Hu, Yanchao Tan. 

Mining User Consistent and Robust Preference for Unified Cross Domain Recommendation. 

TKDE 2024. (CCF A)

• Heyuan Huang, Xingyu Lou, Chaochao Chen, Pengxiang Cheng, Yue Xin, Chengwei He, Xiang Liu and Jun Wang.

DIIT: A Domain-Invariant Information Transfer Method for Industrial Cross-Domain Recommendation. 

CIKM 2024. (CCF B)

• Fan Wang, Chaochao Chen*, Weiming Liu, Tianhao Fan, Xinting Liao, Yanchao Tan, Lianyong Qi, Xiaolin Zheng. 

CE-RCFR: Robust Counterfactual Regression for Consensus-Enabled Treatment Effect Estimation. 

KDD 2024. (CCF A)

• Xinping Zhao, Chaochao Chen*, Jiajie Su, Yizhao Zhang and Baotian Hu. 

Enhancing Attributed Graph Networks with Alignment and Uniformity Constraints for Session-based Recommendation. 

ICWS 2024. (CCF B)

• Weiming Liu, Xiaolin Zheng, Chaochao Chen, Jiahe Xu, Xinting Liao, Fan Wang, Yanchao Tan, Yew-Soon Ong. 

Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation. 

ICML 2024. (CCF A)

• Chaochao Chen, Jiaming Zhang, Yuyuan Li, Zhongxuan Han. 

One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment.

ICML 2024. (CCF A)

• Fei Zheng, Chaochao Chen, Lingjuan Lyu, Xinyi Fu, Xing Fu, Weiqiang Wang, Xiaolin Zheng, Jianwei Yin. 

Protecting Split Learning by Potential Energy Loss. 

IJCAI 2024. (CCF A)

• Zhongxuan Han, Chaochao Chen, Xiaolin Zheng, Li Zhang and Yuyuan Li. 

Hypergraph Convolutional Network for User-Oriented Fairness in Recommender Systems. 

SIGIR 2024. (CCF A)

• Jiajie Su, Chaochao Chen*, Weiming Liu, Zibin Lin, Shuheng Shen, Weiqiang Wang and Xiaolin Zheng. 

Revisit Targeted Model Poisoning on Federated Recommendation: Optimize via Multi-objective Transport. 

SIGIR 2024. (CCF A)

• Xinting Liao, Weiming Liu, Chaochao Chen*, Pengyang Zhou, Fengyuan Yu, Huabin Zhu, Binhui Yao, Tao Wang, Xiaolin Zheng, Yanchao Tan.

Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data.

CVPR 2024. (CCF A)

• Weiming Liu, Chaochao Chen*, Xinting Liao, Mengling Hu, Jiajie Su, Yanchao Tan, Fan Wang.

User Distribution Mapping Modelling with Collaborative Filtering for Cross Domain Recommendation.

TheWebConf 2024. (CCF A)

• Weiming Liu, Chaochao Chen*, Xinting Liao, Mengling Hu, Yanchao Tan, Fan Wang, Xiaolin Zheng, Yew Soon Ong.

Learning Accurate and Bidirectional Transformation via Dynamic Embedding Transportation for Cross-Domain Recommendation. 

AAAI 2024. (CCF A)

• Zhongxuan Han, Chaochao Chen, Xiaolin Zheng, Meng Li, Weiming Liu, Binhui Yao, Yuyuan Li, Jianwei Yin.

Intra- and Inter-Group Optimal Transport for User-Oriented Fairness in Recommender Systems. 

AAAI 2024. (CCF A)

• Yanchao Tan, Hang Lv, Zihao Zhou, Wenzhong Guo, Bo Xiong, Weiming Liu, Chaochao Chen, Shiping Wang, Carl Yang.

Logical Relation Modeling and Mining in Hyperbolic Space for Recommendation. 

ICDE 2024. (CCF A)

• Yuyuan Li, Chaochao Chen, Xiaolin Zheng, Junlin Liu, Jun Wang.

Making recommender systems forget: Learning and unlearning for erasable recommendation.

KBS 2024.  (SCI, IF=8.8)

2023

• Yuyuan Li, Chaochao Chen∗, Yizhao Zhang, Weiming Liu, Lingjuan Lyu, Xiaolin Zheng, Dan Meng, Jun Wang.

UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition.

NeurIPS 2023. [code]  (CCF A)

• Yanchao Tan, Zihao Zhou, Leisheng Yu, Weiming Liu, Chaochao Chen, Guofang Ma, Xiao Hu, Vicki Hertzberg, and Carl Yang.

Enhancing Personalized Healthcare via Capturing Disease Severity, Interaction, and Progression. 

ICDM 2023.  (CCF B)

• Yuyuan Li, Chaochao Chen, Xiaolin Zheng, Yizhao Zhang, Biao Gong, Jun Wang.

Selective and Collaborative Influence Function for Efficient Recommendation Unlearning.

ESWA 2023.  (SCI, IF=8.5)

• Longfei Zheng, Yingting Liu, Xiaolong Xu, Chaochao Chen*, Yuzhou Tang, Lei Wang, Xiaolong Hu.

FedPSE: Personalized Sparsification with Element-wise Aggregation for Federated Learning.

CIKM 2023.  (CCF B)

• Xiaolin Zheng, Zhongyu Wang, Chaochao Chen*, Jiashu Qian, Yao Yang.

Decentralized Graph Neural Network for Privacy-Preserving Recommendation.

CIKM 2023.  (CCF B)

• Personalized Behavior-Aware Transformer for Multi-Behavior Sequential Recommendation.

Jiajie Su, Chaochao Chen, Zibin Lin, Xi Li, Weiming Liu, Xiaolin Zheng. 

ACM MM 2023.  (CCF A)

• Weiming Liu, Xiaolin Zheng, Chaochao Chen, Mengling Hu, Xinting Liao, Fan Wang, Yanchao Tan, Dan Meng, Jun Wang.

Differentially Private Sparse Mapping for Privacy-Preserving Cross Domain Recommendation.

ACM MM 2023.  (CCF A)

• Xinting Liao, Chaochao Chen*, Weiming Liu, Pengyang Zhou, Huabin Zhu, Shuheng Shen, Weiqiang Wang, Mengling Hu, Yanchao Tan, Xiaolin Zheng.

Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data.

ACM MM 2023.  (CCF A)

• Zhongxuan Han, Chaochao Chen*, Xiaolin Zheng, Weiming Liu, Jun Wang, Wenjie Cheng, Yuyuan Li.

In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems.

ACM MM 2023.  (CCF A)

• Zhenghong Lin, Yanchao Tan, YunFei Zhan, Weiming Liu, Fan Wang, Chaochao Chen, Shiping Wang, Carl Yang.

Contrastive Intra- and Inter-Modality Generation for Enhancing Incomplete Multimedia Recommendation.

ACM MM 2023.  (CCF A)

• Yuyuan Li, Chaochao Chen*, Xiaolin Zheng, Yizhao Zhang, Zhongxuan Han, Dan Meng, Jun Wang.

Making Users Indistinguishable: Attribute-wise Unlearning in Recommender Systems.

ACM MM 2023.  (CCF A)

• Xiaolin Zheng, Senci Ying, Fei Zheng, Jianwei Yin, Longfei Zheng, Chaochao Chen* and Fengqin Dong.

Federated Learning on Non-iid Data via Local and Global Distillation.

ICWS 2023.  (CCF B)

• Xiaolin Zheng, Zhongyu Wang, Chaochao Chen*, Feng Zhu and Jiashu Qian.

Freshness or Accuracy, Why Not Both? Addressing Delayed Feedback via Dynamic Graph Neural Networks.

ICWS 2023.  (CCF B)

• Xiaolin Zheng, Mengling Hu, Weiming Liu, Chaochao Chen*, Xinting Liao

Robust Representation Learning with Reliable Pseudo-labels Generation via Self-Adaptive Optimal Transport for Short Text Clustering.

ACL 2023. [code] (CCF A)

• Fei Zheng, Chaochao Chen*, Lingjuan Lyu, Binhui Yao.

Reducing Communication for Split Learning by Randomized Top-k Sparsification.

IJCAI 2023.  (CCF A)

• Xinting Liao, Weiming Liu, Chaochao Chen*, Pengyang Zhou, Huabin Zhu, Yanchao Tan, Jun Wang, Yue Qi.

HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning.

IJCAI 2023. [code] (CCF A)

• Weiming Liu, Chaochao Chen*, Xinting Liao, Mengling Hu, Jianwei Yin, Yanchao Tan, Longfei Zheng.

Federated Probabilistic Preference Distribution Modelling with Compactness Co-Clustering for Privacy-Preserving Multi-Domain Recommendation.

IJCAI 2023.  (CCF A)

• Tao Lu, Chengkun Wei, Ruijing Yu, Chaochao Chen, Wenjing Fang, Lei Wang, Zeke Wang, Wenzhi Chen.

cuZK: Accelerating Zero-Knowledge Proof with A Faster Parallel.

CHES 2023 [pdf]. (CCF B)

• Zhongxuan Han, Xiaolin Zheng, Chaochao Chen*, Wenjie Cheng and Yang Yao.

Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation.

TheWebConf 2023. (CCF A)

• Weiming Liu, Xiaolin Zheng, Chaochao Chen*, Jiajie Su, Xinting Liao, Mengling Hu and Yanchao Tan.

Joint Internal Multi-Interest Exploration and External Domain Alignment for Cross Domain Sequential Recommendation.

TheWebConf 2023: 383-394. (CCF A)

• Jiajie Su, Chaochao Chen, Weiming Liu, Fei Wu, Xiaolin Zheng and Haoming Lyu.

Enhancing Hierarchy-Aware Graph Networks with Deep Dual Clustering for Session-based Recommendation.

TheWebConf 2023: 165-176. (CCF A)

• Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, Jianzhong Qi, Chaochao Chen and Longbiao Chen.

INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging.

TheWebConf 2023 [pdf]. (CCF A)

• Bowen Liu, Wanchun Dou, Xiaokang Zhou, Xuyun Zhang, Lianyong Qi, Fei Dai, Chaochao Chen

An Intelligent Resource Scheduling Method With Edge Channel Deployment for BPM.

IEEE UIC 2023. (CCF C, Outstanding Paper Award)

• Feng Zhu, Mingjie Zhong, Xinxing Yang, Longfei Li, Lu Yu, Tiehua Zhang, Jun Zhou, Chaochao Chen, Fei Wu, Guanfeng Liu, Yan Wang.

DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation. 

ICDE 2023 [pdf]. (CCF A)

• Weiming Liu,Xiaolin Zheng, Jiajie Su, Longfei Zheng, Chaochao Chen*, Mengling Hu.

Contrastive Proxy Kernel Stein Path Alignment for Cross-Domain Cold-Start Recommendation.

TKDE 2023, 35(2): 1171-1184. (CCF A)

• Xinting Liao, Weiming Liu, Xiaolin Zheng, Binhui Yao, Chaochao Chen*.

PPGenCDR: A Stable and Robust Framework for Privacy-Preserving Cross-domain Recommendation.

AAAI 2023 [pdf]. (CCF A)

2022

• Heterogeneous Information Crossing on Graphs for Session-based Recommender Systems.

Xiaolin Zheng, Rui Wu, Zhongxuan Han, Chaochao Chen*, Linxun Chen, Bing Han.

ACM Transactions on the Web (TWEB) [pdf]. (CCF B)

• Finding High-quality Item Attributes for Recommendation.

Xiaolin Zheng, Yanchao Tan, Yan Wang, Xiangyu Wei, Shengjia Zhang, Chaochao Chen, Longfei Li, Carl Yang.

TKDE 2022 [pdf]. (CCF A)

• Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection.

Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang.

KDD 2022: 4838-4839 [pdf]. (CCF A)

• VFGNN: A Mixed Framework for Vertically Federated Graph Neural Network.

Chaochao Chen, Fei Zheng, Jun Zhou, Lingjuan Lyu, Jianwei Yin, Longfei Zheng, Li Wang, Xiaolin Zheng.

CIKM FedGraph 2022. (Best Paper Award)

• Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees.

Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Chaochao Chen, Zhiwei Liu, Jia Wu, Xu Bai, Philip S. Yu.

CIKM 2022:1685-1695 [pdf]. (CCF B, Best Paper Runner Up Award)

• DDGHM: Dual Dynamic Graph with Hybrid Metric Training for Cross-Domain Sequential Recommendation.

Xiaolin Zheng, Jiajie Su, Weiming Liu, Chaochao Chen*.

ACM MM 2022: 471-481 [pdf]. (CCF A)

• 4SDrug: Symptom-based Set-to-set Small and Safe Drug Recommendation.

Yanchao Tan, Chengjun Kong, Leisheng Yu, Pan Li, Chaochao Chen, Xiaolin Zheng, Vicki Hertzberg, Carl Yang.

KDD 2022: 3970-3980 [pdf]. (CCF A)

• Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification.

Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng.

IJCAI 2022: 1959-1965 [pdf]. (CCF A)

• HCFRec: Hash Collaborative Filtering via Normalized Flow with Structural Consensus for Efficient Recommendation.

Fan Wang, Weiming Liu, Chaochao Chen, Mengying Zhu, Xiaolin Zheng.

IJCAI 2022: 2270-2276 [pdf].  (CCF A)

• MERIT: Learning Multi-level Representations on Temporal Graphs.

Binbin Hu, Zhengwei Wu, Ziqi Liu, Jun Zhou, Zhigang Huangfu, Zhiqiang Zhang, Chaochao Chen*.

IJCAI 2022: 2073-2079 [pdf].  (CCF A)

• Decision Boundary-aware Data Augmentation for Adversarial Training.

Chen Chen, Jingfeng Zhang, Xilie Xu, Lingjuan Lyu, Chaochao Chen, Tianlei Hu, Gang Chen.

TDSC 2022 [pdf]. (CCF A)

• Exploiting Variational Domain-Invariant User Embedding for Partially Overlapped Cross Domain Recommendation.

Weiming Liu, Xiaolin Zheng, Jiajie Su, Mengling Hu, Yanchao Tan and Chaochao Chen*.

SIGIR 2022: 312-321 [pdf].  (CCF A)

• MetaCare++: Meta-Learning with Hierarchical Subtyping for Cold-Start Diagnosis Prediction in Healthcare Data.

Yanchao Tan, Carl Yang, Xiangyu Wei, Chaochao Chen, Weiming Liu, Longfei Li, Jun Zhou and Xiaolin Zheng

SIGIR 2022: 449-459 [pdf].  (CCF A)

• Towards Secure and Practical Machine Learning via Secret Sharing and Random Permutation.

Fei Zheng, Chaochao Chen, Xiaolin Zheng, Mingjie Zhu.

Knowledge-Based Systems [pdf]. 2022.

• Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation.

Chaochao Chen, Huiwen Wu, Jiajie Su, Lingjuan Lyu, Xiaolin Zheng and Li Wang.

TheWebConf 2022: 1455-1465 [pdf] [code].  (CCF A)

• Collaborative Filtering with Attribution Alignment for Review-based Non-overlapped Cross Domain Recommendation.

Weiming Liu, Xiaolin Zheng, Mengling Hu and Chaochao Chen*.

TheWebConf 2022: 1181-1190 [pdf].  (CCF A)

• Enhancing Recommendation with Automated Tag Taxonomy Construction in Hyperbolic Space. 

Yanchao Tan, Carl Yang, Xiangyu Wei, Chaochao Chen, Longfei Li, Xiaolin Zheng.

ICDE 2022: 1180-1192 [pdf]. (CCF A)

• Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. 

Jun Zhou, Longfei Zheng, Chaochao Chen*, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin.

ACM TIST 2022, 13(4): 53:1-53:21 [pdf]. 

2021

• Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation. 

Jamie Cui, Chaochao Chen*, Lingjuan Lyu, Carl Yang, Wang Li.

NeurIPS 2021: 10524-10534 [pdf].  (CCF A)

• Leveraging Distribution Alignment via Stein Path for Cross-Domain Cold-Start Recommendation.

Weiming Liu, Jiajie Su, Chaochao Chen, Xiaolin Zheng.

NeurIPS 2021: 19223-19234 [pdf].  (CCF A)

• Large-scale Secure XGB for Vertical Federated Learning. 

Wenjing Fang, Derun Zhao, Jin Tan, Chaochao Chen*, Chaofan Yu, Li Wang, Lei Wang, Jun Zhou, Benyu Zhang.

CIKM 2021: 443-452 [pdf]. (CCF B)

• A Unified Framework for Cross-Domain and Cross-System Recommendations. 

Feng Zhu, Yan Wang, Jun Zhou, Chaochao Chen*, Longfei Li, Guanfeng Liu.

IEEE TKDE 2021 [pdf].  (CCF A)

• When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control. 

Chaochao Chen, Jun Zhou, Li Wang, Xibin Wu, Wenjing Fang, Jin Tan, Lei Wang, Xiaoxi Ji, Alex X. Liu, Hao Wang, Cheng Hong.

KDD 2021: 2652-2662 [pdf] (CCF A)

• Cross-Domain Recommendation: Challenges, Progress, and Prospects. 

Feng Zhu, Yan Wang, Chaochao Chen*, Jun Zhou, Longfei Li, Guanfeng Liu.

IJCAI 2021:4721-4728 [pdf] (CCF A)

• ASFGNN: Automated Separated-Federated Graph Neural Network.

Longfei Zheng, Jun Zhou, Chaochao Chen*, Bingzhe Wu, Li Wang, Benyu Zhang.

PPNA 14(3): 1692-1704 2021 [pdf] (CCF C)

2020

• Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications.

Chaochao Chen, Jamie Cui, Guanfeng Liu, Jia Wu, Li Wang.

Preprint 2020 [pdf]

• Secure Graph Database Search with Oblivious Filter.

Jamie Cui, Chaochao Chen*, Alex X. Liu, Li Wang.

Cryptology ePrint Archive, Report 2020/1415 [pdf]

• Faster Secure Multiparty Computation of Adaptive Gradient Descent

Wen-jie Lu, Yixuan Fang, Zhicong Huang, Cheng Hong, Chaochao Chen, Hunter Qu, Yajin Zhou, Kui Ren.

PPMLP 2020: 47–49 [pdf]

• Nebula: A Scalable Privacy-Preserving Machine Learning System in Ant Financial.

Cen Chen, Bingzhe Wu, Li Wang, Chaochao Chen, Jin Tan, Lei Wang, Jun Zhou, Benyu Zhang.

CIKM 2020: 3369-3372 [pdf] (CCF B)

• Secure Social Recommendation based on Secret Sharing.

Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou. 

ECAI 2020: 506-512 [pdf] (CCF B)

• Practical Privacy Preserving POI Recommendation.

Chaochao Chen, Jun Zhou, Bingzhe Wu, Wenjin Fang, Li Wang, Yuan Qi, Xiaolin Zheng.

ACM TIST 11(5): 52:1-52:20, 2020 [pdf]

• A Graphical and Attentional Framework for Dual-Target Cross-Domain Recommendation.

Feng Zhu, Yan Wang, Chaochao Chen, Guanfeng Liu, Xiaolin Zheng.

IJCAI 2020: 3001-3008 [pdf] [code] [data] (CCF A)

• Industrial Scale Privacy Preserving Deep Neural Networks.

Longfei Zheng, Chaochao Chen*, Yingting Liu, Bingzhe Wu, Xibin Wu, Li Wang, Lei Wang and Jun Zhou. 

AAAI'2020 Workshop on Privacy-Preserving Artificial Intelligence [pdf]

• Privacy Preserving PCA for Multiparty Modeling.

Yingting Liu, Chaochao Chen, Longfei Zheng, Li Wang, Jun Zhou, Guiquan Liu. 

AAAI'2020 Workshop on Privacy-Preserving Artificial Intelligence [pdf]

• Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics.

Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou. 

AAAI 2020: 6372-6379 [pdf] (CCF A)

2019

• Adapted Tree Boosting for Transfer Learning.

Wenjing Fang, Chaochao Chen, Bowen Song, Li Wang, Jun Zhou, Kenny Zhu.

IEEE BigData 2019: 741-750 [pdf] 

• DTCDR: A Framework for Dual-Target Cross-Domain Recommendation.

Feng Zhu, Chaochao Chen, Yan Wang, Guanfeng Liu, Xiaolin Zheng.

CIKM 2019: 1533-1542 [pdf] [data] (CCF B)

• Quantification of the Leakage in Federated Learning.

Zhaorui Li, Zhicong Huang, Chaochao Chen, Cheng Hong.

NeurIPS Workshop on Federated Learning for Data Privacy and Confidentiality 2019 [pdf]

• Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection.

Bingzhe Wu, Shiwan Zhao, ChaoChao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou.

NeurIPS 2019 [pdf] (CCF A)

• How Much Can A Retailer Sell? Sales Forecasting on Tmall.

Chaochao Chen#, ZiqiLiu#, Jun Zhou, Xiaolong Li, Yuan Qi, Yujing Jiao, Xingyu Zhong.

PAKDD 2019: 204-216 [pdf] 

• FinBrain: when finance meets AI 2.0.

Xiaolin Zheng, Mengying Zhu, Qibing Li, Chaochao Chen, Yanchao Tan.

Frontiers of Information Technology & Electronic Engineering, 2019, 20(7): 914-924 [pdf]

• EXPLORE: Explainable Item-Tag Co-recommendation.

Xiaolin Zheng, Menghan Wang, Chaochao Chen, Yan Wang, Zhehao Cheng.

Information Sciences, 474: 170-186 (2019). (CCF B)

• GeniePath: Graph Neural Networks with Adaptive Receptive Paths. 

Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi. 

AAAI 2019 [pdf] (CCF A)

• Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud.

Ya-Lin Zhang, Jun Zhou, Wenhao Zheng, Ji Feng, Longfei Li, Ziqi Liu, Ming Li, Zhiqiang Zhang, Chaochao Chen, Xiaolong Li, Zhi-Hua Zhou.

ACM TIST 10.5 (2019): 1-19 [pdf]

2018

• Heterogeneous Graph Neural Networks for Malicious Account Detection.

Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, Le Song.

CIKM 2018: 2077-2085 [pdf] (CCF B)

• Semi-supervised Learning Meets Factorization: Learning to Recommend with Chain Graph Model.

Chaochao Chen, Kevin C. Chang, Qibing Li, Xiaolin Zheng.

TKDD 12 (6): 73:1-73:24 (2018) [pdf] (CCF B)

• A Deep Framework for Cross-Domain and Cross-System Recommendations.

Feng Zhu, Yan Wang, Chaochao Chen, Mehmet Orgun, Jia Wu, Guanfeng Liu.

IJCAI 2018: 3711-3717 [pdf] (CCF A)

• Distributed Collaborative Hashing and Its Applications in Ant Financial.

Chaochao Chen, Ziqi Liu, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li.

SIGKDD 2018: 100-109  [pdf] (CCF A)

• An Industrial-scale System for Heterogeneous Information Card Ranking in Alipay. 

Zhiqiang Zhang, Chaochao Chen, Jun Zhou, Xiaolong Li. 

DASFFA 2018: 713-724 [pdf] (CCF B)

• A Local Online Learning Approach for Non-linear Data.

Xinxing Yang, Jun Zhou, Peilin Zhao, Cen Chen, Chaochao Chen, Xiaolong Li. 

PAKDD 2018: 431-443 (CCF C)

• Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization. 

Chaochao Chen, Ziqi Liu, Peilin Zhao, Jun Zhou, Xiaolong Li. 

AAAI 2018: 257-264 [pdf] (CCF A)

2017

• Towards Context-Aware Social Recommendation via Individual Trust. 

Jun Li, Chaochao Chen*, Huiling Chen, Changfei Tong. 

Knowledge-Based System 127: 58-66 (2017) [pdf] 

• Large scale app recommendation in Ant Financial.

Chaochao Chen, Xinxing Yang, Li Wang, Jun Zhou, Xiaolong Li.  

BigData 2017: 4733-4735.

• KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial. 

Jun Zhou, Xiaolong Li, Peilin Zhao, Chaochao Chen, Longfei Li, Xinxing Yang, Qing Cui, Jin Yu, Xu Chen, Yi Ding, Yuan Alan Qi. 

SIGKDD 2017: 1693-1702 [pdf] (CCF A)

• POSTER: Neural Network-based Graph Embedding for Malicious Accounts Detection. 

Ziqi Liu#, Chaochao Chen#, Jun Zhou, Xiaolong Li, Feng Xu, Tao Chen, Le Song. 

ACM Conference on Computer and Communications Security (CCS) 2017: 2543-2545  (CCF A)

2016

• Social recommendation via multi-view user preference learning. 

Hanqing Lu, Chaochao Chen, Ming Kong, Hanyi Zhang, Zhou Zhao. 

Neurocomputing 216: 61-71 (2016) [pdf] 

• Recommender System with Composite Social Trust Networks. 

Chaochao Chen, Xiaolin Zheng, Mengying Zhu, Litao Xiao. 

International Journal Web Service Research 13(2): 56-73 (2016) [pdf]

• A hybrid approach for movie recommendation via tags and ratings. Electronic Commerce Research and Applications. 

Shouxian Wei, Xiaolin Zheng, Deren Chen, Chaochao Chen. 

Electronic Commerce Research and Applications. 18: 83-94 (2016)

• Topic tensor factorization for recommender system.

Xiaolin Zheng, Weifeng Ding, Zhen Lin, Chaochao Chen. 

Information Sciences 372: 276-293 (2016) (CCF B)

• Capturing Semantic Correlation for Item Recommendation in Tagging Systems. 

Chaochao Chen, Xiaolin Zheng, Yan Wang, Fuxing Hong, Deren Chen. 

AAAI 2016: 108-114 [pdf] (CCF A)

2015 and Before

• A Hybrid Trust-Based Recommender System for Online Communities of Practice. 

Xiaolin Zheng, Chaochao Chen, Jui-Long Hung, Wu He, Fuxing Hong, Zhen Lin. 

IEEE Transactions on Learning Technologies 8(4): 345-356 (2015) [pdf]

• Efficient learning ensemble SuperParent-one-dependence estimator by maximizing conditional log likelihood.

Xiaolin Zheng, Zhen Lin, Huan Xu, Chaochao Chen, Ting Ye. 

Expert Systems With Applications 42(21): 7732-7745 (2015) (CCF C)

• Context-Aware Collaborative Topic Regression with Social Matrix Factorization for Recommender Systems. 

Chaochao Chen, Xiaolin Zheng, Yan Wang, Fuxing Hong, Zhen Lin. 

AAAI 2014: 9-15 [pdf] (CCF A)

Professional Services

• Journal Reviewer or Review Editor: IEEE TKDE, Frontiers in Big Data, Machine Learning Journal, Computer Standards & Interfaces, Neurocomputing, IEEE Intelligent Systems, IEEE TSP, ACM TIST, Security and Communication Networks,  IEEE TNNLS, IEEE TDSC, IEEE TPAMI, IEEE TC, ACM TOIS, Knowledge-Based Systems, Information Sciences, IEEE TSC

• Conference Area Chair: NeurIPS'24

• Conference PC Member:

2025: IJCAI, WSDM, WWW, ICLR, ACL

2024: WSDM, WWW, ICLR, ICWS, ACL, SIGIR, SDM, ICML, CVPR

2023: WSDM, AAAI, WWW, ICASSP, IJCAI, KDD, ICML, SIGIR, ACL, ICWS, ECML-PKDD, NeurIPS, ACM MM

2022: IJCAI, AAAI, WSDM, WWW, KDD, ICML, ICWS, ACM MM, ECML-PKDD, NeurIPS

2021: WWW, AAAI, CIKM, ACM MM, ICWS, ACM MM ASIA

2020: AAAI, WWW, IJCAI, CCS-PPMLP

2019: AAAI, IJCAI, ACML

2018: IJCAI, ACML

• Conference Senior PC Member: IJCAI'21

• Others: Session Chair for IJCAI'18