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Biography
Dr Hanhe Lin obtained his PhD degree from University of Otago (New Zealand) in 2016. From 2016 to 2021, he was a postdoctoral researcher at University of Konstanz (Germany), funded by the German Research Foundation (DFG). After being a research fellow at National Subsea Centre (Robert Gordon University) for a short period, he is currently DIICSU Programme Lead and Lecturer in Computing at the Faculty of Science, Engineering and Business, University of Dundee.
Dr Lin is an IEEE Senior member and an EPSRC Peer Review College member. As an active researcher in the field of artificial intelligence, he has published more than 60 papers in AI-related venues. He served as a member of the technical program committee or a reviewer in numerous prestigious conferences such as ICME, ICIP, ICASSP, and QoMEX. Since 2016, he has been serving regularly as a reviewer for journals such as IEEE Trans. Pattern Analysis and Machine Intelligence, IEEE Trans. Image Processing, and IEEE Trans. Multimedia. He has been serving as a Guest Editor for the MDPI Journal of Imaging and as an Associate Editor for Frontiers in Imaging. He is the Publication Chair of International Conference on Pattern Recognition (Virtual) 2027.
Research
Dr Lin’s research interests are predominantly in computer vision, deep learning, medical image analysis, and crowdsourcing. His current research topics mainly focus on Visual Quality Assessment and Medical Image Analysis.
Dr Lin keeps looking for talented and motivated PhD students on the projects relevant to visual computing such as computer vision, deep learning, medical image analysis, etc. Interested candidates are welcome to contact via [email protected].
Sampled research outputs:
Mao, J., Liu, J., Tian, X., Pan, Y., Trucco, E. and Lin, H.*, 2024. Towards Integrating Federated Learning with Split Learning via Spatio-temporal Graph Framework for Brain Disease Prediction. IEEE Transactions on Medical Imaging. *Corresponding author. (IF:8.9, JCR Q1)
Su, S., Lin, H.*, Hosu, V., Wiedemann, O., Sun, J., Zhu, Y., Liu, H., Zhang, Y. and Saupe, D., 2023. Going the extra mile in face image quality assessment: A novel database and model. IEEE Transactions on Multimedia. *Corresponding author. (IF:8.4, JCR Q1)
Lou, J., Lin, H., Young, P., White, R., Yang, Z., Shelmerdine, S., Marshall, D., Spezi, E., Palombo, M. and Liu, H., 2023. Predicting radiologists' gaze with computational saliency models in mammogram reading. IEEE Transactions on Multimedia. (IF:8.4, JCR Q1)
Lin, H., Chen, G., Jenadeleh, M., Hosu, V., Reips, U.D., Hamzaoui, R. and Saupe, D., 2022. Large-scale crowdsourced subjective assessment of picturewise just noticeable difference. IEEE Transactions on Circuits and Systems for Video Technology. (IF:8.3, JCR Q1)
Hosu, V., Lin, H.*, Sziranyi, T. and Saupe, D., 2020. KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment. IEEE Transactions on Image Processing. *Contribute equally. (IF:10.8, JCR Q1 1000+ citations)
Teaching
Dr Lin has extensive experience in developing and delivering teaching across a range of computing-related topics. He is a Fellow of the Higher Education Academy.
He is currently teaching:
- DI11004 - Project (Computing)
- DI21008 - Introduction to Programming
- DI40001 - Honours Project
PhD Projects
Principal supervisor
- Type
- PhD opportunity
Lightweight AI Model for Medical Image Analysis
- Type
- PhD opportunity