I am currently a postdoctoral researcher at the Delft University of Technology, working with the team of AidroLab at the Faculty of Civil Engineering and Geosciences. 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. I also joined LIACS, Leiden University as a Ph.D candidate in 2019 fall, and was supervised by Prof. Marcello Bonsangue.

My research vision is to develop AI-based solutions to address real-world challenges across diverse domains, including social computing, urban computing, and environmental science.

(1) AI + Social Computing, with a specific focus on understanding the diffusion of online information (information diffusion prediction) and assessing its credibility (rumor/fake news detection). Recently, I have also been interested in the predictability of economic behavior that influences human life (stock prediction).
(2) AI + Urban Computing, which focuses on deploying AI in city development. I have focused on transportation management, including traffic (vehicle and metro) flow prediction, as well as analyzing human mobility behavior through data from user online check-ins. Additionally, I have worked on extracting meaningful information based on the interactions (e.g., nearby and located in) of urban entities (e.g., shopping centers, restaurants, and roads) within geographical areas (urban region modeling and prediction).
(3) AI + Environmental Science, an interdisciplinary research field that integrates AI, environmental science, and physics, is critically important for addressing diverse challenges in Earth’s environment. My primary focus within this area is solving problems related to water management.

In a nutshell, I’m interested in extracting meaningful features from multi-modal data, including text, images, dynamic networks, videos, and time-series data, for various real-world downstream tasks. In addition, in the era of large language models (LLMs), I’m also particularly intrigued by the potential of leveraging LLMs and the training strategies behind them, such as retrieval augmented generation (RAG), in-context learning, and mixture-of-experts (MoE), to enhance existing applications.

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 Dependency Dynamics in Traffic Flow Forecasting via Graph Risk Bootstrap Qiang Gao, Zizheng Wang, Li Huang, Goce Trajcevski, Kunpeng Zhang and Xueqin Chen SIGSPATISL, 2024 (Full, CCF C) Accepted   • Codes

pdf	Contrastive Learning with Edge-wise Augmentation for Rumor Detection Nan Liu, Fengli Zhang, Qiang Gao and Xueqin Chen* International Journal of Intelligent Systems, 2024 (JCR 1)

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)   • Codes

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 ICLR' 25 | KDD' 23/24 | IJCAI' 24 | DSAI’ 23 | SDM’ 24 Journal Reviewer for Expert Systems With Applications | Transactions on Knowledge and Data Engineering | Information Sciences | International Journal of Intelligent Systems | Journal of Circuits, Systems, and Computers | Information Processing and Management | IEEE Transactions on Circuits and Systems for Video Technology | Scientific Reports | Knowledge-Based Systems Conference External 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: November, 2024.