Lin, Hanhe


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Personal profile


I received my Ph.D. degree at University of Otago (New Zealand) in 2016. From Oct. 2016 to Aug. 2021, I was a postdoc in multimedia signal processing (MMSP) group, University of Konstanz (Germany). Since Jun. 2022, I am a lecturer in Computing at School of Science and Engineering at University of Dundee (UK). I have been involved in some significant projects, funded by German Research Foundation (DFG). I have published more than 40 peer-reviewed machine learning and computer vision articles, e.g., IEEE TIP, IEEE TCSVT, and Neurocomputing. I serve as a member of technical program committee or a reviewer in a number of conferences/journals, e.g. QoMEX, IEEE TPAMI/TMM/TIP. 


  • DI11004 - Project (Computing) (SEM 1 22/23)
  • DI11007 - Calculus for Science and Engineering (SEM 1 22/23)

  • AC52010 - MSc Project (Data Science and Engineering 22/23)


My research includes but not limit to:

  • Visual quality assessment
  • Motorcycle helmet use detection
  • Visual saliency prediction
  • Crowd scene analysis in video surveillance 

Potential PhD research projects

  • Medical Image Quality Assessment The quality of a medical image, e.g., chest X-ray, plays an essential role in doctors’ clinical decision-making. While image quality assessment (IQA) has been widely studied on natural images, medical IQA is still challenging and less studied. This project aims to conduct a subjective study to build a benchmarking medical IQA database. With the database, a novel objective IQA metric will be developed using computer vision and deep learning techniques.
  • Benchmarking trustworthy image quality assessment Current image quality assessment (IQA) methods, in particular deep learning-based, are not used to their full potential, due to limitations in the underlying databases, and shortcomings in reproducibility and reliability. The overarching goal of the project is to build a large-scale, well-structured benchmark database that could not only benefit the development and evaluation of objective IQA methods but also produce reproducible and reliable results that place researchers' trust in IQA research.
  • Other ML/CV/DL topics

If you are interested in applying for a PhD study, please contact me ( 

I also welcome Chinese PhD applicants via China Scholarship Council (CSC)!

Research interests

  • Image processing
  • Deep learning
  • Machine learning
  • Computer vision

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 11 - Sustainable Cities and Communities

Education/Academic qualification

Doctor of Philosophy, University of Otago

Award Date: 1 Oct 2016

External positions

Research fellow, Robert Gordon University

1 Sept 202130 Jun 2022

Postdoc, University of Konstanz

1 Oct 201631 Aug 2021


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