Senior Lecturer
- About
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- Email Address
- jari.korhonen@abdn.ac.uk
- Office Address
- School/Department
- School of Natural and Computing Sciences
Biography
I am an experienced researcher in computer science, specialised in multimedia technologies and Quality of Experience (QoE) in particular. I received my MSc degree in information engineering at University of Oulu, Finland, in 2001, and PhD in telecommunications and signal processing at Tampere University of Technology, Finland, in 2006. In my early career, I worked as a Research Engineer at Nokia Research Center, Tampere, Finland, from 2001 to 2006, before moving to academia. Before joining the University of Aberdeen, I was working at Shenzhen University, China, from 2017 to 2022.
My past research experience covers both telecommunications and signal processing aspects of multimedia communications. My current research focus primarily on visual quality assessment, and I have contributed to several models for predicting perceived image and video quality directly from the signal. As a part of this work, I have been principal investigator (PI) for a project funded by National Natural Science Foundation of China (NSFC) from 2018 to 2021. Most recently, I have studied deep learning techniques applied to visual quality assessment, as well as other related computer vision problems.
In addition to my research work, I have experience of teaching several courses in the fields of visual communications, signal processing, and telecommunications. I have also supervised and co-supervised several student projects at BSc, MSc and PhD levels.
Qualifications
- PhD Telecommunications and Signal Processing2006 - Tampere University of Technology, Finland
- MSc Information Engineering2001 - University of Oulu, Finland
External Memberships
- IEEE Member
Latest Publications
Gated Transformer Representing Region Importance for Image Quality Assessment
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1109/IJCNN60899.2024.10650165
- [ONLINE] View publication in Scopus
3DTA: No-Reference 3D Point Cloud Quality Assessment with Twin Attention
IEEE Transactions on MultimediaContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TMM.2024.3407698
- [ONLINE] View publication in Scopus
FishIR: Identifying Pufferfish Individual based on Deep Learning and Face Recognition
IEEE Access, vol. 12, pp. 59807 - 59817Contributions to Journals: ArticlesOn the Explainable Detection of Stress Levels Using Heart Rate Variability Based Deep Neural Networks
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1109/Healthcom56612.2023.10472396
- [ONLINE] View publication in Scopus
High Resolution Image Quality Database
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1109/ICASSP48485.2024.10446520
- [OPEN ACCESS] http://aura.abdn.ac.uk/bitstream/2164/23724/1/2401.16087v1.pdf
- [ONLINE] View publication in Scopus
- Research
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Research Areas
Accepting PhDs
I am currently accepting PhDs in Computing Science.
Please get in touch if you would like to discuss your research ideas further.
Computing Science
Accepting PhDsResearch Specialisms
- Artificial Intelligence
- Computer Vision
- Multimedia Computing Science
Our research specialisms are based on the Higher Education Classification of Subjects (HECoS) which is HESA open data, published under the Creative Commons Attribution 4.0 International licence.
Blind Image and Video Quality Assessment
Jari Korhonen has several years of experience of working on automated prediction of image and video quality, with focus on blind models for user generated photos and videos. Several models based on his work, such as Two-Level Video Quality Model (TLVQM), are publicly available.
Funding and Grants
- National Natural Science Foundation of China (NSFC) Grant 61772348: "Quality assessment for consumer video applications," 2018-21 (Shenzhen University).
- Teaching
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Teaching Responsibilities
- JC2002 Java Programming (SCNU Joint Institute, 2022, 2023)
- JC4004 Computational Intelligence (SCNU Joint Institute, 2024)
- JC2503 Web Application Development (SCNU Joint Institute 2023, 2024)