I am currently a postdoctoral researcher at the Delft University of Technology, working with the team of AidroLab at the Department of Civil Engineering and Geosciences and Electrical Engineering, Mathematics and Computer Science, hosted by Dr. Riccardo Taormina. Before that, I was a Ph.D. candidate at the School of Information and Software Engineering, University of Electronic Science and Technology of China (since 2017 fall), under the supervision of Prof. Fengli Zhang and Prof. Fan Zhou, and also joined LIACS, Leiden University as a Ph.D candidate in 2019 fall, and supervised by Prof. Marcello Bonsangue. My research interests lie primarily in the application of graph representation learning. Recently, I focused on deploying GNN in the water network. If you are interested in modeling information cascades by using deep learning technicals, highly recommended: Awesome-DL-Information-Cascades-Modleing.

Publications

In the Year of 2024:

pdf	Enhancing Fine-Grained Urban Flow Inference via Incremental Neural Operator Qiang Gao, Xiaolong Song, Li Huang, Goce Trajcevski, Fan Zhou and Xueqin Chen IJCAI 2024 (CCF A)

pdf	Information Diffusion Prediction via Cascade-Retrieved In-context Learning Ting Zhong, Jienan Zhang, Zhangtao Cheng, Fan Zhou and Xueqin Chen SIGIR 2024 (Short, CCF A)

In the Year of 2022:

pdf	Multi-view Learning with Distinguishable Feature Fusion for Rumor Detection Xueqin Chen, Fan Zhou, Goce Trajcevski and Marcello Bonsangue Knowledge-Based Systems (JCR-1)

pdf	Multi-Scale Graph Capsule with Influence Attention for Information Cascade Prediction Xueqin Chen, Fengli Zhang, Fan Zhou and Marcello Bonsangue International Journal of Intelligent Systems (JCR-1)   • Codes

In the Year of 2021:

pdf	Catch Me If You Can: A Participant-Level Rumor Detection Framework via Fine-grained User Representation Learning Xueqin Chen, Fan Zhou, Fengli Zhang and Marcello Bonsangue Information Processing and Management (JCR-1)

pdf	Modeling Microscopic and Macroscopic Information Diffusion for Rumor Detection Xueqin Chen, Fan Zhou, Fengli Zhang and Marcello Bonsangue International Journal of Intelligent Systems (JCR-1)

In the Year of 2019:

pdf	Information Cascades Modeling via Deep Multi-Task Learning Xueqin Chen, Kunpeng Zhang, Fan Zhou, Goce Trajcevski, Ting Zhong and Fengli Zhang SIGIR 2019 (Short, CCF A)

pdf	Information Diffusion Prediction via Recurrent Cascades Convolution Xueqin Chen, Fan Zhou, Kunpeng Zhang, Goce Trajcevski, Ting Zhong and Fengli Zhang ICDE 2019 (Full, CCFA)   • Codes

Looking for the full publication list? Please visit Google Scholar.

Honors

ICDE Student Travel Award,    2019    - IEEE 35th International Conference on Data Engineering

Outstanding graduated of general higher education institutions in Liaoning Province,   June 2015    - Dalian Neusoft University of Information, China

Professional Services

Conference PC member for KDD' 23/24 | IJCAI' 24 | DSAI’ 23 | SDM’ 24 Journal Reviewer for IJIS | JCSC | IP&M | TCSVT | TKDE | ESWA | IS Conference Reviewer for KDD (19, 20) | ACL, SIGIR, BigData (20),

Teaching Assistants

CEGM1000: MUDE - Modelling, Uncertainty, Data for Engineers 2022, 2023

CEGM2003: DSAIE - Data Science and Artificial Intelligence for Engineers 2023

Last update: March, 2024.