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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 a Lecturer in Computing at School of Science and Engineering, University of Dundee.

As an active researcher in his research domain, Dr Lin served as a member of the technical program committee or a reviewer in numerous prestigious conferences such as QoMEX, ICIP, and ICME. 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. Currently, he is serving as guest editor for the MDPI Journal of Imaging and associate editor for the Frontier in Imaging.


Dr Lin’s research interests are predominantly in computer vision, machine learning, medical image analysis, and crowdsourcing. His current research topics mainly focus on Visual Quality Assessment. Using techniques crowdsourcing, machine learning, deep learning, and eye-tracking, he has established benchmark datasets and designed computational models for predicting the visual quality of images and videos, with respect to technical and perceptual aspects.
Sampled research outputs:

  • 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.
  • 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.
  • 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.
  • Lou, J., Lin, H., Marshall, D., Saupe, D. and Liu, H., 2022. TranSalNet: Towards perceptually relevant visual saliency prediction. Neurocomputing.
  • 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.

Dr Lin keeps looking for talented and motivated PhD students on the projects relevant to visual quality assessment. Interested candidates are welcome to contact via hlin001@dundee.ac.uk.

View full research profile and publications


Dr Lin has extensive experience in developing and delivering teaching across a range of computing-related topics. He is an Associate Fellow of the Higher Education Academy.

He is currently teaching:

  • DI11004 - Project (Computing)
  • DI11007 - Calculus for Science and Engineering
  • DI21008 - Introduction to Programming