Biography

Chen Gao is now a Faculty Member (Research-track AP) of BNRist, Tsinghua University. He obtained his Ph.D. Degree (advised by Prof. Yong Li and Prof. Depeng Jin) and Bachelor’s Degree from the Department of Electronic Engineering, Tsinghua University in 2021 and 2016, respectively. His research primarily focuses on data mining (recommender system and spatio-temporal data mining), large language model, embodied agent, etc., with over 60 papers in top-tier venues (50+ CCF-A), including SIGIR, WWW, KDD, etc., attracting over 3,000 citations.

Advertisements (long-term effective): I am seeking self-motivated interns (undergraduate or graduate) and collaborators to conduct research on data mining (recommendation and spatio-temporal data mining), large language models, embodied agent, etc. with us remotely or at Tsinghua. Our interns have good record of publishing first-author papers in CCF-A conferences/journals. Our team is also actively hiring Postdocs/PhD/Master students. Feel free to contact me via email if you are interested.

News

[New!]We released EmbodiedCity platform. For more details, please refer to the paper link.
[New!]Our EconAgent paper received ACL 2024 Outstanding Paper Award. For more details, please refer to the arXiv link.
[New!]Our survey paper on agent-based modeling and simulation with LLM agents is accepted by Humanities and Social Sciences Communications. For more details, please refer to the arXiv link.
[New!]We release a preprint paper about large language model for depression detection. For more details, please refer to the arXiv paper.
[New!]We release a preprint paper about large language model for complex network. For more details, please refer to the arXiv paper.
We release a preprint paper about large language model for session-based recommendation (LLM4SBR). For more details, please refer to the arXiv paper.
We release a preprint paper about large language model agent-based automated machine learning (AutoML). For more details, please refer to the arXiv paper.
Our tutorial proposal about agent-based modeling and simulation with large language model-empowered agents is accepted by WWW 2024. For more details, please refer to our website.
We release a preprint paper about urban generative intelligence (UGI) on the simulation environment and large language model agents in city. For more details, please refer to the arXiv paper.
We release a preprint paper of social simulation with large language model-empowered agents. For more details, please refer to the arXiv paper.
[June. 2, 2024] I am invited to give a talk about LLM-based simulation in the 2nd China Multi-agent System Conference 2024.
[May. 22, 2024] I am selected as a Distinguished Reviewer of ACM TORS.
[May. 16, 2024] One paper about economic simulation with large language agents is accepted by ACL 2024 main conference.
[Apr. 14, 2024] I am invited to give a talk about LLM-based combinational optimization in the 3rd forum on intelligent decision-making, Institute of Automation, CAS.
[Mar. 26, 2024] Our paper about user fatigue in recommender system is accepted by SIGIR 2024.
[Mar. 16, 2024] Our paper about stance detection with large language model agent is accepted by ICWSM 2024.
[Mar. 7, 2024] I am invited to give a talk about filter bubble in recommender system in Data Science Seminar of the School of EECS, The University of Queensland.
[Feb. 2, 2024] Three papers are accepted by ACM Web Conference 2024 (WWW 2024).
Show more

[Nov. 25, 2023] I am invited to give a talk about LLM-based social simulation and economic simulation in CCF RLChina 2023.

[Nov. 9, 2023] Our survey about causal inference-based recommender system is accepted by ACM Transactions on Information Systems (ACM TOIS). We have also released the 2nd Version on arXiv.

[Nov. 1, 2023] I am invited to give a talk about AutoML-based recommender system in CCF Student Pilot Program.

[Oct. 21, 2023] I am invited to give a talk about causal inference-based recommender system in DataFun Summit.

[Oct. 20, 2023] Two papers about recommendation are accepted by ACM International Conference on Web Search and Data Mining as oral paper (WSDM 2024).

[Sep. 8, 2023] One paper about urban knowledge graph is accepted by ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2023).

[Sep. 3, 2023] I will serve as Social Media Co-chair of SIGIR 2024.

[Aug. 5, 2023] One paper about short-video recommendation is accepted by ACM International Conference on Information and Knowledge Management (CIKM 2023).

[Jul. 26, 2023] One paper about recommendation robustness is accepted by ACM International Conference on Multimedia (ACMMM 2023).

[Jun. 21, 2023] One paper about short-video recommendation is accepted by ACM Conference on Recommender Systems (RecSys 2023).

[May. 30, 2023] I am invited to be a Program Committee (PC) Member of ACM International Conference on Information and Knowledge Management (CIKM 2023).

[May. 17, 2023] Three papers on recommendation, urban vulnerability, and living demands prediction are accepted by ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023).

[Apr. 25, 2023] I am invited to be a Program Committee (PC) Member of ACM Multimedia Conference (ACMMM 2023).

[Apr. 14, 2023] One paper on knowledge graph-based recommendation is accepted by ACM Transactions on Information Systems (ACM TOIS).

[Apr. 5, 2023] One full paper and one short paper on micro-video recommendation and cold-start recommendation are accepted by ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023).

[Mar. 3, 2023] I am invited to be a Program Committee (PC) Member of ACM Conference on Recommender Systems (RecSys 2023).

[Jan. 25, 2023] Three papers on controllable recommender system, sequential recommendation, and social recommendation are accepted by TheWebConf (TheWebConf/WWW 2023).

[Dec. 23, 2022] I am invited to be a Program Committee (PC) Member of ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023).

[Oct. 30, 2022] One paper on disentangling geographical effect for point-of-interest recommendation is accepted by IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE).

[Sep. 19, 2022] I am invited to be a Program Committee (PC) Member of International Conference on Artificial Intelligence and Statistics (AISTATS 2023).

[Aug. 29, 2022] We have released a survey on causal inference for recommender systems.

[Aug. 25, 2022] Our survey paper about graph neural network-based recommender systems is accepted by ACM Transactions on Recommender Systems.

[Aug. 2, 2022] One full research paper and one short research paper are accepted by ACM Conference on Information and Knowledge Management (CIKM 2022).

[Jun. 30, 2022] One paper on short-video recommendation is accepted by ACM Multimedia Conference (ACM MM 2022).

[May. 19, 2022] Two papers on user intention discovery and user decision-factor are accepted by ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022).

[May. 17, 2022] One paper on disentangling social conformity and social influence for recommendation is accepted by IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE).

[Apr. 1, 2022] Two short papers on sequential recommendation and session-based recommendation are accepted by ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022).

[Feb. 25, 2022] We hosted the tutorial on "Graph Neural Networks for Recommender System" in ACM International Conference on Web Search and Data Mining (WSDM 2022).

[Dec. 30, 2021] I am invited to be a Program Committee (PC) Member of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) and International Conference on Machine Learning (ICML 2022).

[Nov. 8, 2021] I am invited to give a talk about the GNN-RecSys survey in the Departmental Seminars (COMP 6911 & COMP 6912) Fall 2021 of the Dept. of ECE, HKUST.

[Oct. 28, 2021] Our tutorial proposal of "Graph Neural Networks for Recommender System" is accepted by ACM International Conference on Web Search and Data Mining (WSDM 2022).

[Sep. 27, 2021] We have released a survey entitled "Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions" at arXiv.

[Aug. 1, 2021] I am invited to be a Program Committee (PC) Member of TheWebConf 2022, International Conference on Learning Representations (ICLR 2022), ACM International Conference on Web Search and Data Mining (WSDM 2022), AAAI Conference on Artificial Intelligence (AAAI 2022), and International Joint Conference on Artificial Intelligence (IJCAI 2022).

[Apr. 17, 2021] I am invited to be a Program Committee (PC) Member of Conference on Neural Information Processing Systems (NeurIPS 2021).

[Mar. 17, 2021] I am invited to be a Program Committee (PC) Member of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2021).

Survey

Tutorial

Publications [Google Scholar]

Preprint

EmbodiedCity: A Benchmark Platform for Embodied Agent in Real-world City Environment
Chen Gao, Baining Zhao, Weichen Zhang, Jinzhu Mao, Jun Zhang, Zhiheng Zheng, Fanhang Man, Jianjie Fang, Zile Zhou, Jinqiang Cui, Xinlei Chen, Yong Li
arXiv.

Depression Detection on Social Media with Large Language Models
X. Lan, Y. Cheng, L. Sheng, Chen Gao, Y. Li
arXiv:2403.10750, 2024.

Identify Critical Nodes in Complex Network with Large Language Models
J. Mao, D. Zou, L. Sheng, S. Liu, Chen Gao, Y. Wang, Y. Li
arXiv:2403.03962, 2024.

Large Language Model Agent for Hyper-Parameter Optimization
S. Liu, Chen Gao, Y. Li
arXiv:2402.01881, 2024.

LLM4SBR: A Lightweight and Effective Framework for Integrating Large Language Models in Session-based Recommendation
S. Qiao, Chen Gao, J. Wen, W. Zhou, Q. Luo, P. Chen, Y. Li
arXiv:2402.13840, 2024.

Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment
F. Xu. J. Zhang, Chen Gao (co-first author), J. Feng, Y. Li
arXiv:2312.11813, 2023.

S3: Social-network Simulation System with Large Language Model-Empowered Agents
Chen Gao, X. Lan, Z. Lu, J. Mao, J. Piao, H. Wang, D. Jin, Y. Li
arXiv:2307.14984, 2023.

A Probabilistic Fluctuation based Membership Inference Attack for Diffusion Models
W. Fu, H. Wang, Chen Gao, G. Liu, Y. Li, T. Jiang
arXiv:2308.12143, 2023.

Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration
W. Fu, H. Wang, Chen Gao, G. Liu, Y. Li, T. Jiang
arXiv:2311.06062, 2023.

The Year of 2024:

EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities
N. Li, Chen Gao, M Li, Y. Li, Q. Liao
The 62nd Annual Meeting of the Association for Computational Linguistics (ACL), Main Conference, 2024. (Oral, Outstanding Paper Award, CCF-A)

Modeling User Fatigue for Sequential Recommendation
N. Li, X. Bai, C. Ling, Chen Gao, L. Hu, P. Jiang, K. Gai, Y. Li, Q. Liao
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2024. (CCF-A)

Stance Detection with Collaborative Role-Infused LLM-Based Agents
X. Lan, Chen Gao, D. Jin, Y. Li
The International AAAI Conference on Web and Social Media (ICWSM), 2024. (Spotlight, CCF-B)

Uncovering the Deep Filter Bubble: Narrow Exposure in Short-Video Recommendation
N. Sukiennik, Chen Gao and N. Li
ACM The Web Conference (TheWebConf/WWW), 2024. (CCF-A)

Full-stage Diversified Recommendation: Large-scale Online Experiments in Short-video Platform
N. Li, Y. Pan, Chen Gao, D. Jin and Q. Liao
ACM The Web Conference (TheWebConf/WWW), 2024. (CCF-A)

Improving Item-side Fairness of Multimodal Recommendation via Modality Debiasing
Y. Shang, Chen Gao, J. Chen, D. Jin and Y. Li
ACM The Web Conference (TheWebConf/WWW), 2024. (CCF-A)

Inverse Learning with Extremely Sparse Feedback for Recommendation
G. Lin, Chen Gao, Y. Zheng, Y. Li, J. Chang, Y. Niu, Y. Song, K. Gai, Z. Li, D. Jin, Y. Li
ACM International Conference on Web Search and Data Mining (WSDM), oral, 2024. (CCF-B)

Mixed Attention Network for Cross-domain Sequential Recommendation
G. Lin, Chen Gao, Y. Zheng, Y. Li, J. Chang, Y. Niu, Y. Song, K. Gai, Z. Li, D. Jin, Y. Li, M. Wang
ACM International Conference on Web Search and Data Mining (WSDM), oral, 2024. (CCF-B)

The Year of 2023:

Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System
Y. Pan, N. Li, Chen Gao, J. Chang, Y. Niu, Y. Song, D. Jin, Y. Li.
ACM International Conference on Information and Knowledge Management (CIKM), 2023. (CCF-B)

Modeling Multi-Grained User Preference in Location Visitation
Y. Qin, Chen Gao, T. Zhen, H. Wu, S. Wei, Y. Wang, L. Zhang, Y. Li.
ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL, full, acceptance rate=15.7%), 2023. (CCF-C)

Enhancing Adversarial Robustness of Multi-modal Recommendation via Modality Balancing
Y. Shang, Chen Gao, J. Chen, D. Jin, H. Ma, Y. Li.
ACM International Conference on Multimedia (ACM MM), 2023. (CCF-A)

Understanding and Modeling Passive-Negative Feedback for Sequential Short-video Recommendation
Y. Pan, Chen Gao, Y. Song, K. Gai, Depeng Jin, Y. Li.
ACM Conference on Recommender Systems (RecSys), 2023. (CCF-B)

Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering
Y. Wen, Chen Gao, L. Yi, L. Qiu, Y. Wang, and Y. Li.
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2023. (CCF-A)

NEON: Living Needs Prediction System in Meituan
X. Lan, Chen Gao, W. Shi, X. Chen, Y. Che, H. Zhang, H. Wei, H. Luo, and Y. Li.
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2023. (CCF-A)

Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network
J. Mao, L. Cao, Chen Gao, H. Wang, H. Fan, D. Jin, and Y. Li.
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2023. (CCF-A)

Learning Fine-grained User Interests for Micro-video Recommendation
Y. Shang, Chen Gao, J. Chen, D. Jin, Y. Li, and M. Wang.
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023. (CCF-A)

Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation
T. Liu, Chen Gao, Z. Wang, D. Li, J. Hao, D. Jin, and Y. Li.
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR, short), 2023. (CCF-A)

Alleviating Video-Length Efect for Micro-video Recommendation
Y. Quan, J. Ding, Chen Gao, N. Li, L. Yi, D. Jin, and Y. Li.
ACM Transactions on Information Systems (TOIS), 2023. (CCF-A)

Learning from Hierarchical Structure of Knowledge Graph for Recommendation
Y. Qin, Chen Gao, S. Wei, Y. Wang, D. Jin, J. Yuan, L. Zhang, D. Li, J. Hao, and Y. Li.
ACM Transactions on Information Systems (TOIS), 2023. (CCF-A)

Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning
W. Fu, H. Wang, Chen Gao, G. Liu, Y. Li, T. Jiang.
ACM Transactions on Information Systems (TOIS), 2023. (CCF-A)

Cascading Residual Graph Convolutional Network for Multi-Behavior Recommendation
M. Yan, Z. Cheng, Chen Gao, J. Sun, F. Liu, F. Sun, H. Li.
ACM Transactions on Information Systems (TOIS), 2023. (CCF-A)

Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation
C Meng, Z. Zhao, W. Guo, Y. Zhang, H. Wu, Chen Gao, D. Li, X. Li, R. Tang.
ACM Transactions on Information Systems (TOIS), 2023. (CCF-A)

Dual-interest Factorization-heads Attention for Sequential Recommendation
G. Lin, Chen Gao, Y. Zheng, J. Chang, Y. Niu, Y. Song, Z. Li, D. Jin, and Y. Li.
ACM The Web Conference (TheWebConf/WWW), 2023. (CCF-A)

Breaking Filter Bubble: A Reinforcement Learning Framework of Controllable Recommender System
Y. Dong, Z. Li, Chen Gao, Y. Zhao, D. Li, J. Hao, Z. Wang, K. Zhang, and Y. Li.
ACM The Web Conference (TheWebConf/WWW), 2023. (CCF-A)

Robust Preference-Guided Denoising for Graph-based Social Recommendation
Y. Quan, J. Ding, Chen Gao, L. Yi, D. Jin, and Y. Li.
ACM The Web Conference (TheWebConf/WWW), 2023. (CCF-A)

The Year of 2022:

Disentangling Geographical Effect for Point-of-Interest Recommendation
Y. Qin, Chen Gao, Y. Wang, S. Wei, D. Jin, J. Yuan, and L. Zhang
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022. (CCF-A)

Spatiotemporal-aware Session-based Recommendation with Graph Neural Networks
Y. Li, Chen Gao, X. Du, H. Wei, H. Luo, D. Jin, and Y. Li
ACM International Conference on Information and Knowledge Management (CIKM), 2022. (CCF-B)

An Exploratory Study of Information Cocoon on Short-form Video Platform
N. Li, Chen Gao, J. Piao, X. Huang, A. Yue, L. Zhou, Q. Liao, and Y. Li
ACM International Conference on Information and Knowledge Management (CIKM), short, 2022. (CCF-B)

DVR:Micro-Video Recommendation Optimizing Watch-Time-Gain under Duration Bias
Y. Zheng, Chen Gao, J. Ding, L. Yi, D. Jin, Y. Li, and M. Wang
ACM International Conference on Multimedia (ACM MM), oral, 2022. (CCF-A)

Automatically Discovering User Consumption Intents in Meituan
Y. Li, Chen Gao, X. Du, H. Wei, H. Luo, D. Jin, and Y. Li
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2022. (CCF-A)

Modeling Persuasion Factor of User Decision for Recommendation
C. Liu, Chen Gao, Y. Yuan, C. Bai, L. Luo, X. Du, H. Luo, D. Jin, and Y. Li
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2022. (CCF-A)

Disentangled Modeling of Social Homophily and Influence for Social Recommendation
N. Li, Chen Gao, D. Jin, and Q. Liao
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022. (CCF-A)

Dual Contrastive Network for Sequential Recommendation
G. Lin, Chen Gao, Y. Li, Y. Zheng, Z. Li, D. Jin, and Y. Li
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), short 2022. (CCF-A)

Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation
Y. Li, Chen Gao, H. Luo, D. Jin, and Y. Li
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), short 2022. (CCF-A)

DisenHCN:Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction
Y. Li, Chen Gao, Q. Yao, T. Li, D. Jin, and Y. Li
IEEE International Conference on Data Engineering (ICDE), 2022. (CCF-A)

Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks
Z. Zhu, Chen Gao, X. Chen, N. Li, D. Jin, and Y. Li
IEEE International Conference on Data Engineering (ICDE), 2022. (CCF-A)

Disentangling Long and Short-Term Interests for Recommendation
Y. Zheng, Chen Gao, J. Chang, Y. Niu, Y. Song, D. Jin, and Y. Li
The Web Conference (TheWebConf/WWW), 2022. (CCF-A)

Practitioners Versus Users: A Value-Sensitive Evaluation of Current Industrial Recommender System Design
Z. Chen, J. Piao, X. Lan, H. Cao, Chen Gao, Z. Lu, and Y. Li
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2022 (CCF-A)

The Year of 2021:

Progressive Feature Interaction Search for Deep Sparse Network
Chen Gao, Y. Li, Q. Yao, D. Jin, and Y. Li
Conference on Neural Information Processing Systems (NeurIPS), 2021 (CCF-A)

Bundle Recommendation and Generation with Graph Neural Networks
J. Chang, Chen Gao, X. He, D. Jin, and Y. Li
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021. (CCF-A)

Cross-platform Item Recommendation for Online Social E-Commerce
Chen Gao, TH. Lin, N. Li, D. Jin, and Y. Li
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021. (CCF-A)

Incorporating Price into Recommendation with Graph Convolutional Networks
Y. Zheng, Chen Gao, X. He, D. Jin, and Y. Li
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021. (CCF-A)

Bringing Friends into the Loop of Recommender Systems: An Exploratory Study
J. Piao, G. Zhang, F. Xu, Z. Chen, Y. Zheng, Chen Gao, and Y. Li
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2021 (CCF-A)

Efficient Data-specific Model Search for Collaborative Filtering
Chen Gao, Q. Yao, D. Jin, and Y. Li
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2021. (CCF-A)

User Consumption Intention Prediction in Meituan
Y. Ping, Chen Gao, T. Liu, X. Du, H. Luo, D. Jin, and Y. Li
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2021. (CCF-A)

Sequential Recommendation with Graph Neural Networks
J. Chang, Chen Gao, Y. Zheng, Y. Hui, Y. Niu, Y. Song, D. Jin, and Y. Li
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021. (CCF-A)

Cross-domain Recommendation with Bridge-Item Embeddings
Chen Gao, Y. Li, F. Feng, X. Chen, K. Zhao, X. He, and D. Jin
ACM Transactions on Knowledge Discovery from Data (TKDD), 2021 (CCF-B)

Learnable Embedding Sizes for Recommender Systems
S. Liu, Chen Gao, Y. Chen, D. Jin, and Y. Li
International Conference on Learning Representations (ICLR), 2021

Group-Buying Recommendation for Social E-Commerce
J. Zhang, Chen Gao, D. Jin, and Y. Li
IEEE International Conference on Data Engineering (ICDE), 2021. (CCF-A)

Disentangling User Interest and Conformity for Recommendation with Causal Embedding
Y. Zheng, Chen Gao, X. Li, X. He, D. Jin, and Y. Li
The Web Conference (TheWebConf/WWW), 2021. (CCF-A)

DGCN:Diversified Recommendation with Graph Convolutional Networks
Y. Zheng, Chen Gao, L. Chen, D. Jin, and Y. Li
The Web Conference (TheWebConf/WWW), 2021. (CCF-A)

The Year of 2020:

DPLCF:Differentially Private Local Collaborative Filtering
Chen Gao, C. Huang, D. Lin, D. Jin, and Y. Li
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020. (CCF-A)

Multi-behavior Recommendation with Graph Convolutional Networks
B. Jin, Chen Gao, X. He, D. Jin, and Y. Li
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020. (CCF-A)

Item Recommendation for Word-of-Mouth Scenario in Social E-Commerce
Chen Gao, C. Huang, D. Yu, TH. Lin, H. Fu, D. Jin, and Y. Li
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020. (CCF-A)

Social Recommendation with Characteristic Regularization
Chen Gao, N. Li, TH. Lin, D. Lin, J. Zhang, Y. Li, and D. Jin
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020. (CCF-A)

Bundle Recommendation with Graph Convolutional Networks
J. Chang, Chen Gao, X. He, D. Jin, and Y. Li
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020. (Best Short Paper Honorable Mention Award, CCF-A)

Price-aware Recommendation with Graph Convolutional Networks
Y. Zheng, Chen Gao, X. He, Y. Li, and D. Jin
IEEE International Conference on Data Engineering (ICDE), 2020. (CCF-A)

Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs
H. Wang, Chen Gao, Y. Li, ZL. Zhang, and D. Jin
IEEE Transactions on Network and Service Management (TNSM), 2020.

The Year of 2019:

Learning to Recommend with Multiple Cascading Behaviors
Chen Gao, X. He, D. Gan, X. Chen, F. Feng, Y. Li, TS. Chua, and D. Jin
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019. (CCF-A)

Cross-domain Recommendation without Sharing User-relevant Data
Chen Gao, X. Chen, F. Feng, K. Zhao, X. He, Y. Li, and D. Jin
The Web Conference (TheWebConf/WWW), 2019. (CCF-A)

Privacy-preserving Cross-domain Location Recommendation
Chen Gao, C. Huang, Y. Yu, H. Wang, Y. Li, and D. Jin
ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp/IMWUT), 2019. (CCF-A)

Neural Multi-Task Recommendation from Multi-Behavior Data
Chen Gao, X. He, D. Gan, X. Chen, F. Feng, Y. Li, TS. Chua, and D. Jin
IEEE International Conference on Data Engineering (ICDE), short, 2019. (CCF-A)

CROSS:Cross-platform Recommendation for Social E-Commerce
TH. Lin, Chen Gao, and Y. Li
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2019. (CCF-A)

λOpt:Learn to Regularize Recommender Models in Finer Levels
Y. Chen, B. Chen, X. He, Chen Gao, Y. Li, JG. Lou, and Y. Wang
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2019. (CCF-A)

DeepAPF:Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation
H. Yan, X. Chen, Chen Gao, Y. Li, and D. Jin
International Joint Conference on Artificial Intelligence (IJCAI), 2019. (CCF-A)

Anonymization and De-anonymization of Mobility Trajectories:Dissecting the Gaps between Theory and Practice
H. Wang, Chen Gao, Y. Li, G. Wang, X. Tao, and D. Jin
IEEE Transactions on Mobile Computing (TMC), 2019. (CCF-A)

The Year of 2018 and Before:

Recommender Systems with Characteristic Social Regularization
TH. Lin, Chen Gao, and Y. Li
ACM Conference on Information and Knowledge Management (CIKM), short, 2019.(CCF-B)

De-anonymization of Mobility Trajectories:Dissecting the Gaps between Theory and Practice
H. Wang, Chen Gao, Y. Li, G. Wang, D. Jin, and J. Sun
Network and Distributed System Security Symposium (NDSS), 2018. (CCF-A)

From Fingerprint to Footprint: Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs
H. Wang, Chen Gao, Y. Li, ZL. Zhang, and D. Jin
ACM International Conference on Information and Knowledge Management (CIKM), 2017. (CCF-B)

Academic Services

Conference Organizer

Social Media Chair, SIGIR 2024

Conference Program Committee Member

Invited Journal Reviewer

Awards

ACL Outstanding Paper Award, 2024
Finalist of China Computer Federation (CCF) Outstanding Doctoral Dissertation Award, 2021
Tsinghua University Outstanding Doctoral Dissertation Award, 2021
Top 100 Chinese Rising Stars in Artificial Intelligence, selected by Baidu Scholar, 2021
SIGIR 2020 Best Short Paper Honorable Mention Award, 2020