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Dr Yingke Chen

Associate Professor

Department: Computer and Information Sciences

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.

Yingke Chen

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). 

  • Please visit the Pure Research Information Portal for further information
  • 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
  • Evolving filter criteria for randomly initialized network pruning in image classification, Chen, X., Liu, C., Hu, P., Lin, J., Gong, Y., Chen, Y., Peng, D., Geng, X. 14 Aug 2024, In: Neurocomputing
  • Look before you leap: Detecting phishing web pages by exploiting raw URL and HTML characteristics, Opara, C., Chen, Y., Wei, B. 1 Feb 2024, In: Expert Systems with Applications
  • Noisy-Correspondence Learning for Text-to-Image Person Re-identification, Qin, Y., Chen, Y., Peng, D., Peng, X., Zhou, J., Hu, P. 17 Jun 2024, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Piscataway, NJ, US, IEEE
  • Spectral Embedding Fusion for Incomplete Multiview Clustering, Chen, J., Chen, Y., Wang, Z., Zhang, H., Peng, X. 4 Jul 2024, In: IEEE Transactions on Image Processing
  • Online Sparse Representation Clustering for Evolving Data Streams, Chen, J., Yang, S., Fahy, C., Wang, Z., Guo, Y., Chen, Y. 27 Oct 2023, In: IEEE Transactions on Neural Networks and Learning Systems
  • HTMLPhish: Enabling Phishing Web Page Detection by Applying Deep Learning Techniques on HTML Analysis, Opara, C., Wei, B., Chen, Y. Jul 2020, 2020 International Joint Conference on Neural Networks (IJCNN 2020), Piscataway, IEEE

Computing Science PhD July 01 2013


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