Dr Hans Ren

Tutor in Computer Science, Computer Science

hanchi.ren@swansea.ac.uk

Admin - 015
Ground Floor
Computational Foundry
Bay Campus

Research Links

About

Dr Hanchi Ren is a Tutor and a member of the Computer Vision and Machine Learning group (http://csvision.swan.ac.uk) in the Department of Computer Science, Swansea University, where he completed both his PhD (2023) and MSc (2016) degrees.

With the successes of deep learning in many computational cognitive tasks, AI has been becoming the core of digital infrastructure. Majority of Dr Hanchi Ren’s work is closely related to applied machine learning to diverse industrial and consumable products. Therefore, his research and teaching interest is mainly focus on the fundamental advancement of theoretical machine learning and its applications in computer vision, big data and privacy preservation.

Areas Of Expertise

Computer Vision
Privacy Preservation
Machine Learning
Deep Learning

Publications

Research Highlights

Ren, H., Hu, F., Myint, S., Hou, K., Zhang, X., Zuo, M., Zhang, C., Zhang, Q., & Li, H. (2021). A Real-Time and Long-Term Face Tracking Method Using Convolutional Neural Network and Optical Flow in IoT-Based Multimedia Communication Systems. Wireless Communications and Mobile Computing, 2021, 1-15.
https://doi.org/10.1155/2021/6711561, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58621
Ren, H., Deng, J., & Xie, X. (2022). GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning. ACM Transactions on Intelligent Systems and Technology, 13(4)
https://doi.org/10.1145/3510032, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59093
Ren, H., Deng, J., Xie, X., Ma, X., & Wang, Y. (2024). FedBoosting: Federated learning with gradient protected boosting for text recognition. Neurocomputing, 569
https://doi.org/10.1016/j.neucom.2023.127126, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65267
Xie, X., Hu, C., Ren, H., & Deng, J. (2024). A survey on vulnerability of federated learning: A learning algorithm perspective. Neurocomputing, 573, 127225
https://doi.org/10.1016/j.neucom.2023.127225, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65451

All Research

Journal Articles

Xie, X., Hu, C., Ren, H., & Deng, J. (2024). A survey on vulnerability of federated learning: A learning algorithm perspective. Neurocomputing, 573, 127225
https://doi.org/10.1016/j.neucom.2023.127225, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65451
Ren, H., Deng, J., Xie, X., Ma, X., & Wang, Y. (2024). FedBoosting: Federated learning with gradient protected boosting for text recognition. Neurocomputing, 569
https://doi.org/10.1016/j.neucom.2023.127126, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65267
Ren, H., Deng, J., & Xie, X. (2022). GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning. ACM Transactions on Intelligent Systems and Technology, 13(4)
https://doi.org/10.1145/3510032, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59093
Ren, H., Hu, F., Myint, S., Hou, K., Zhang, X., Zuo, M., Zhang, C., Zhang, Q., & Li, H. (2021). A Real-Time and Long-Term Face Tracking Method Using Convolutional Neural Network and Optical Flow in IoT-Based Multimedia Communication Systems. Wireless Communications and Mobile Computing, 2021, 1-15.
https://doi.org/10.1155/2021/6711561, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58621