Ali Hassan
Postdoktor|Postdoc
- Professional title: Postdoc
- Academic title: Doctor of Philosophy (PhD)
- Other title: Computer Engineering
- Area of responsibility: Computer Vision and Artificial Intelligence
- Telephone: +46 (0)10-1428562
- Email: ali.hassan@miun.se
- Visitor address: Holmgatan 10, SE-85170, Sundsvall, Sweden
- Room number: L417
- Location: Sundsvall
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- Employed at the subject:
- Computer Engineering
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- Research centers:
- STC Research Centre
Researcher in Efficient Visual AI
My name is Ali Hassan, and I am from Islamabad, Pakistan. I am a Post-Doctoral Researcher in the Realistic3D lab under the Computer and Electrical Engineering Department.
Background
I have completed a double doctoral degree from Mid Sweden University, Sweden and Tampere University, Finland. I have 6+ years of research experience, with 10 publications.
Area of interest
Machine Learning, Light Field, Digital Image Processing, Computer Vision, Deep Learning,
Publications
Articles in journals
Conference papers
Doctoral theses, comprehensive summaries
Articles in journals
Hassan, A. , Sjöström, M. , Zhang, T. & Egiazarian, K. (2026). REDARTS : Regressive Differentiable Neural Architecture Search for Exploring Optimal Light Field Disparity Estimation Network. IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 10: 1, pp. 531-542.
Hassan, A. , Zhang, T. , Egiazarian, K. & Sjöström, M. (2025). CR-DARTS : Channel Redistribution-based Differentiable Architecture Search. IEEE Access, vol. 13, pp. 201166-201182.
Hassan, A. , Ahmad, W. , Ghafoor, M. , Qureshi, K. , Olsson, R. & Sjöström, M. (2025). Two-Dimensional Hierarchical Rate Control Scheme For Light Field Compression Using MV-HEVC. Journal of Electronic Imaging (JEI), vol. 34: 05
Conference papers
Hassan, A. , Zhang, T. , Egiazarian, K. & Sjöström, M. (2025). EPINET-Lite : Rethinking Mixed Convolutions forEfficient Light Field Disparity Estimation Network. In 2025 IEEE 27th International Workshop on Multimedia Signal Processing (MMSP).. pp. 120--125.
Hassan, A. , Sjöström, M. , Zhang, T. & Egiazarian, K. (2022). Light-Weight EPINET Architecture for Fast Light Field Disparity Estimation. In 2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP) : 26-28 Sept. 2022, Shanghai, China. Shanghai, China : . pp. 1--5.
Doctoral theses
Hassan, A. (2026). Parameter-Efficient Convolutional Neural Networks for Computer Vision Applications. Dis. (Comprehensive summary) Sundsvall : Mid Sweden University, 2026 (Mid Sweden University doctoral thesis : 439)