Profile

FIB-Lab, the Department of Electronic Engineering, Tsinghua University

Email: chgao96[at]gmail[dot]com

Chen Gao is now a PostDoc Researcher at FIB-Lab in the Department of E.E., Tsinghua University. He obtained his Ph.D. Degree (advised by Prof. Yong Li and Prof. Depeng Jin) and Bachelor Degree from the same department in 2021 and 2016, respectively. His research mainly focuses on data mining and information retrieval, with over 40 papers in top-tier venues including SIGIR, WWW, KDD, ICDE, ICLR, NeurIPS, MM, UbiComp, CSCW, TKDE, etc. His work on GNN-based bundle recommendation received the Best Short Paper Honorable Mention Award in SIGIR 2020. He serves as the PC member for conferences including WWW, KDD, WSDM, NeurIPS, ICLR, ICML, CIKM, AAAI, IJCAI, ECML-PKDD, etc., and the regular reviewer for journals including IEEE TKDE, ACM TOIS, etc. He was a visiting research scholar (advised by Prof. Tat-Seng Chua) at NExT Center of National University of Singapore in 2018. He was selected as one of Top 100 Chinese Rising Stars in Artificial Intelligence (Data Mining Area) by Baidu Scholar in 2021. He was also at the finalist of 2021 China Computer Federation (CCF) Outstanding Doctoral Dissertation Award.

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Survey

Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions. [arXiv]

Tutorial

WSDM 2022, Graph Neural Networks for Recommender System [Website][Slides]

IJCAI 2021, Towards Automated Recommender System [Website][Slides]

KDD 2020, Advances in Recommender System [Website][Slides]

Publications [Google Scholar]

(*corresponding author)

In the year of 2022:

  • Spatiotemporal-aware Session-based Recommendation with Graph Neural Networks. Y. Li, Chen Gao*, X. Du, H. Wei, H. Luo, D. Jin, and Y. Li. (CIKM'22)

  • 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 MM'22, oral)

  • Automatically Discovering User Consumption Intents in Meituan. Y. Li, Chen Gao*, X. Du, H. Wei, H. Luo, D. Jin, and Y. Li. (KDD'22)

  • Modeling the Effect of Persuasion Factor on User Decision for Recommendation. C. Liu, Chen Gao*, Y. Yuan, C. Bai, L. Luo, X. Du, H. Luo, D. Jin, and Y. Li. (KDD'22)

  • Disentangled Modeling of Social Homophily and Influence for Social Recommendation. N. Li, Chen Gao*, D. Jin and Q. Liao. (TKDE'22)

  • Dual Contrastive Network for Sequential Recommendation. G. Lin, Chen Gao*, Y. Li, Y. Zheng, Z. Li, D. Jin and Y. Li. (SIGIR'22, short)

  • Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation. Y. Li, Chen Gao*, H. Luo, D. Jin and Y. Li (SIGIR'22, short)

  • DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction. Y. Li, Chen Gao*, Q. Yao, T. Li, D. Jin and Y. Li. (ICDE'22)

  • Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks. Z. Zhu, Chen Gao, X. Chen, N. Li, D. Jin and Y. Li. (ICDE'22)

  • Disentangling Long and Short-Term Interests for Recommendation. Y. Zheng, Chen Gao*, J. Chang, Y. Niu, Y. Song, D. Jin and Y. Li. (TheWebConf/WWW'22)

  • 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. (CSCW'22)

In the year of 2021:

  • Progressive Feature Interaction Search for Deep Sparse Network. Chen Gao, Y. Li, Q. Yao, D. Jin and Y. Li. (NeurIPS'21)

  • Bundle Recommendation and Generation with Graph Neural Networks . J. Chang, Chen Gao*, X. He, D. Jin and Y. Li. (TKDE'21)

  • Cross-platform Item Recommendation for Online Social E-Commerce. Chen Gao, TH. Lin, N. Li, D. Jin and Y. Li. (TKDE'21)

  • Incorporating Price into Recommendation with Graph Convolutional Networks. Y. Zheng, Chen Gao, X. He, D. Jin and Y. Li. (TKDE'21)

  • 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. (CSCW'21)

  • Efficient Data-specific Model Search for Collaborative Filtering. Chen Gao, Q. Yao, D. Jin and Y. Li. (KDD'21)

  • User Consumption Intention Prediction in Meituan. Y. Ping, Chen Gao, T. Liu, X. Du, H. Luo, D. Jin and Y. Li. (KDD'21)

  • Sequential Recommendation with Graph Neural Networks. J. Chang, Chen Gao, Y. Zheng, Y. Hui, Y. Niu, Y. Song, D. Jin and Y. Li. (SIGIR'21)

  • Cross-domain Recommendation with Bridge-Item Embeddings. Chen Gao, Y. Li, F. Feng, X. Chen, K. Zhao, X. He and D. Jin. (TKDD'21)

  • Learnable Embedding Sizes for Recommender Systems. S. Liu, Chen Gao*, Y. Chen, D. Jin and Y. Li. (ICLR'21)

  • Group-Buying Recommendation for Social E-Commerce. J. Zhang, Chen Gao*, D. Jin and Y. Li. (ICDE'21)

  • Disentangling User Interest and Conformity for Recommendation with Causal Embedding. Y. Zheng, Chen Gao, X. Li, X. He, D. Jin and Y. Li. (TheWebConf/WWW'21)

  • DGCN: Diversified Recommendation with Graph Convolutional Networks. Y. Zheng, Chen Gao, L. Chen, D. Jin and Y. Li. (TheWebConf/WWW'21)

In the year of 2020:

  • Differentially Private Local Collaborative Filtering. Chen Gao, C. Huang, D. Lin, D. Jin and Y. Li. (SIGIR'20)

  • Multi-behavior Recommendation with Graph Convolutional Networks. B. Jin, Chen Gao, X. He, D. Jin and Y. Li. (SIGIR'20)

  • 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. (TKDE'20)

  • Social Recommendation with Characteristic Regularization. Chen Gao, N. Li, TH. Lin, D. Lin, J. Zhang, Y. Li and D. Jin. (TKDE'20)

  • Bundle Recommendation with Graph Convolutional Networks. J. Chang, Chen Gao, X. He, D. Jin and Y. Li.(SIGIR'20, Best Short Paper Honorable Mention Award)

  • Price-aware Recommendation with Graph Convolutional Networks. Y. Zheng, Chen Gao, X. He, Y. Li and D. Jin. (ICDE'20)

  • Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs . H. Wang, Chen Gao, Y. Li, ZL. Zhang and D. Jin. (TNSM'20)

In 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. (TKDE'19)

  • Cross-domain Recommendation without Sharing User-relevant Data. Chen Gao, X. Chen, F. Feng, K. Zhao, X. He, Y. Li and D. Jin. (TheWebConf/WWW'19)

  • Privacy-preserving Cross-domain Location Recommendation. Chen Gao, C. Huang, Y. Yu, H. Wang, Y. Li and D. Jin. (IMWUT/UbiComp'19)

  • 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. (ICDE'19, short)

  • CROSS: Cross-platform Recommendation for Online Shopping in Social Media. TH. Lin, Chen Gao and Y. Li. (SIGIR'19)

  • λOpt: Learn to Regularize Recommender Models in Finer Levels. Y. Chen, B. Chen, X. He, Chen Gao, Y. Li, JG. Lou and Y. Wang. (KDD'19)

  • DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation. H. Yan, X.. Chen, Chen Gao, Y. Li and D. Jin. (IJCAI'19)

  • Anonymization and De-anonymization of Mobility Trajectories: Dissecting the Gaps between Theory and Practice. H. Wang, Y. Li, Chen Gao, G. Wang, X. Tao and D. Jin. (TMC'19)

Before 2019:

  • Recommender Systems with Characteristic Social Regularization. TH. Lin, Chen Gao and Y. Li. (CIKM'18, short)

  • 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. (NDSS'18)

  • From Fingerprint to Footprint: Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs. H. Wang, Chen Gao, Y. Li, ZL. Zhang and D. Jin. (CIKM'17)

Professional Services

Program Committee Member (Reviewr): WSDM 2022-2023, ICLR 2022-2023, KDD 2022, ICML 2022, WWW 2021-2022, AAAI 2021-2023, IJCAI 2021-2022, NeurIPS 2021-2022, ECML-PKDD 2020-2022, CIKM 2019

Invited Journal Reviewer: IEEE TKDE, ACM TOIS

News

Aug. 2, 2022

One full research paper and one short research paper are accepted by CIKM 2022.

Jun. 30, 2022

One paper on short-video recommendation is accepted by ACM Multimedia 2022.

May. 19, 2022

Two papers on user intention discovery and user decision-factor are accepted by KDD 2022.

May. 17, 2022

One paper on disentangling social conformity and social influence for recommendation is accepted by IEEE TKDE.

Apr. 1, 2022

Two short papers on sequential recommendation and session-based recommendation are accepted by SIGIR 2022.

Feb. 25, 2022

We hosted the tutorial on "Graph Neural Networks for Recommender System" (Website | Slides) in WSDM 2022.

Dec. 30, 2021

I am invited to be a Program Committee (PC) Member of KDD 2022 and 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 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, ICLR 2022, WSDM 2022, AAAI 2022, and IJCAI 2022.

Apr. 17, 2021

I am invited to be a Program Committee (PC) Member of NeurIPS 2021.

Mar. 17, 2021

I am invited to be a Program Committee (PC) Member of ECML-PKDD 2021.


Awards

  • 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

  • Best Short Paper Honorable Mention Award, SIGIR 2020