Dr Yingke Chen

Associate Professor

School: Computer Science

Yingke Chen received his PhD from Aalborg University, Denmark. He did post-doctoral research at Queen’s University Belfast, UK, and Georgia University, USA. His main research interests include artificial intelligence, machine learning, data-driven decision-making, and their applications. His research has led to national and regional research grants and publications in the Journal of AI Research, JAAMAS, TNNLS, TIP, TKDE, AAMAS, AAAI, CVPR, and IJCAI conferences.

Alongside fundamental research, he also designs innovative solutions based on theoretical findings to address practical challenges. He has been the major contributor (PI/Co-I) of over £1.3M Innovate UK-funded projects (including five Knowledge Transfer Partnerships). He works together with business partners from transportation, logistics, autonomous underwater vehicles, education, and e-commerce sectors to exploit data science and AI techniques to understand their current operations and upscale their businesses for the future.

Email Yingke

Research Themes and Scholarly Interests

Yingke Chen‘s research interests include Artificial Intelligence (in particular, machine learning, multiagent systems and their applications) and Formal Methods (in particular, machine learning-based model checking).

Key Publications

Please visit the Pure Research Information Portal for further information
Ambiguity-Tolerant Cross-Modal Hashing with Partial Labels, Su, C., Li, Y., Wang, X., Chen, Y., Zheng, H., Peng, D., Sun, Y. 14 Mar 2026, Proceedings of the AAAI Conference on Artificial Intelligence, Washington DC, US, Association for the Advancement of Artificial Intelligence (AAAI)
External Guidance Incomplete Cross-modal Hashing, Chen, J., Pu, R., Peng, D., Song, X., Chen, Y., Sun, Y. 18 Mar 2026, In: IEEE Transactions on Image Processing
Granular-Ball Subspace-Based Fuzzy Neighborhood Anomaly Detector, Wang, S., Su, X., Peng, D., Peng, X., Chen, H., Chen, Y., Yuan, Z. 4 Mar 2026, In: IEEE Transactions on Fuzzy Systems
Learning Beyond Domains: Misleading Prompts and Pseudo-Label Contrast for Text Domain Generalization, Li, Q., Wang, X., Chen, Y., Yan, M., Peng, D., Peng, X., Wang, X. 17 Mar 2026, Proceedings of the 40th Annual AAAI Conference on Artificial Intelligence, Washington, US, Association for the Advancement of Artificial Intelligence (AAAI)
Neighbor-aware Instance Refining with Noisy Labels for Cross-Modal Retrieval, Liu, Y., Pu, R., Xu, S., Chen, Y., Liu, Q., Sun, Y. 17 Mar 2026, Proceedings of the 40th Annual AAAI Conference on Artificial Intelligence, Washington, US, Association for the Advancement of Artificial Intelligence (AAAI)
Optimal transport filtering for robust cross-modal retrieval with open-set noisy labels, Liu, X., Pu, R., Sun, Y., Chen, Y., Huang, S., Peng, D., Sang, Y., Wang, Z. 3 Mar 2026, In: Pattern Recognition
A Reliable Deep Learning Model for ECG Interpretation: Mitigating Overconfidence and Direct Uncertainty Quantification, Li, X., Zheng, Q., Zhang, S., Fu, S., Chen, Y., Ye, K. 20 May 2025, In: Symmetry
DFNO: Detecting Fuzzy Neighborhood Outliers, Yuan, Z., Hu, P., Chen, H., Chen, Y., Li, Q. 1 Jan 2025, In: IEEE Transactions on Knowledge and Data Engineering
Granular-ball computing guided anomaly detection for hybrid attribute data, Su, X., Wang, X., Peng, D., Chen, H., Chen, Y., Yuan, Z. 1 Jun 2025, In: International Journal of Machine Learning and Cybernetics
Integrating granular computing with density estimation for anomaly detection in high-dimensional heterogeneous data, Chen, B., Yuan, Z., Peng, D., Chen, X., Chen, H., Chen, Y. 1 Feb 2025, In: Information Sciences