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, AAMAS, AAAI, 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 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.

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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
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
Online Sparse Representation Clustering for Evolving Data Streams, Chen, J., Yang, S., Fahy, C., Wang, Z., Guo, Y., Chen, Y. Jan 2025, In: IEEE Transactions on Neural Networks and Learning Systems
Underdetermined Blind Signal Separation with Smooth Approximation Function for Insufficiently Sparse Sources, Li, Y., Peng, D., Xiang, Y., Chen, Y., Tao, Q. 1 Apr 2025, In: Circuits, Systems, and Signal Processing
Adaptive Masked Autoencoder Transformer for image classification, Chen, X., Liu, C., Hu, P., Lin, J., Gong, Y., Chen, Y., Peng, D., Geng, X. 1 Oct 2024, In: Applied Soft Computing
Detecting anomalies with granular-ball fuzzy rough sets, Su, X., Yuan, Z., Chen, B., Peng, D., Chen, H., Chen, Y. 1 Sep 2024, In: Information Sciences
DiDA: Disambiguated Domain Alignment for Cross-Domain Retrieval with Partial Labels, Liu, H., Ma, Y., Yan, M., Chen, Y., Peng, D., Wang, X. 24 Mar 2024, Proceedings of the 38th AAAI Conference on Artificial Intelligence, Washington, DC, AAAI Press/International Joint Conferences on Artificial Intelligence
Dual Self-Paced Cross-Modal Hashing, Sun, Y., Dai, J., Ren, Z., Chen, Y., Peng, D., Hu, P. 25 Mar 2024, Proceedings of the 38th AAAI Conference on Artificial Intelligence, Washington, DC, AAAI Press/International Joint Conferences on Artificial Intelligence