About Me
I am an Associate Professor of Computational Science and Engineering at the Informatics Institute, specializing in multidimensional problems and computational science. I completed my PhD at the same institute and worked as a postdoctoral researcher at the Hyperspectral Imaging Centre, Glasgow, UK. My work combines tensor decomposition techniques with machine learning to address real engineering challenges.
Research Interests
- Tensor Decomposition
- Scientific Computing
- Hyperspectral Imaging
- Gene Network Analysis
- Machine Learning
Selected Publications
[1] Tuna, S. (2026). Efficient Spatial-Spectral Feature Extraction in Hyperspectral Images via Holistic Multivariance Decomposition arXiv Preprint, DOI: 10.48550/arXiv.2607.22272[2] Tuna, S. (2026). Holistic Multivariance Decomposition: Adapting Mode Interrelations in Low-Rank Tensor Approximations arXiv Preprint , DOI: 10.48550/arXiv.2606.26965
[3] Şen, M. E., Tuna, S. (2025). A new feature extraction scheme based on support optimization in Enhanced Multivariance Products Representation for Hyperspectral Imagery Journal of the Franklin Institute , DOI: 10.1016/j.jfranklin.2024.107464
[4] Tuna, S., Gulec, C., Yucesan, E., Cirakoglu, A., Tarkan Arguden, Y. (2023). Gene Teams are on the Field: Evaluation of Variants in Gene-Networks Using High Dimensional Modelling IEEE/ACM Transactions on Computational Biology and Bioinformatics , DOI:10.1109/TCBB.2023.3292245
[5] Tuna, S., Korkmaz Özay, E., Tunga, B., Gürvit, E., Tunga, M. A. (2022). An Efficient Feature Extraction Approach for Hyperspectral Images Using Wavelet High Dimensional Model Representation International Journal of Remote Sensing , 43(19-24), DOI:10.1080/01431161.2022.2147036
[6] Tuna, S., Töreyin, B. U., Demiralp, M., Ren, J., Zhao, H., & Marshall, S. (2020). Iterative enhanced multivariance products representation for effective compression of hyperspectral images IEEE Transactions on Geoscience and Remote Sensing, 59(11), DOI:10.1109/TGRS.2020.3031016
Ongoing Projects
- A Grid-Based Representation and Generative Artificial Intelligence Framework for the Mechanical Design of Shell Structures (TÜBİTAK 1001)
- Development of an Electronic Nose System for the Detection of Residual Anesthetic Gases in Post-Anesthesia Care Units (TÜBİTAK 1002)
- Development of an Image Processing–Based Automated Monitoring and Decision Support Platform for Blueberry Cultivation (TÜBİTAK 1707)
- Research and Development of Next-Generation Solid-State Detectors within the Framework of the CERN DRD3 Collaboration (TENMAK)
Teaching
- HBM511 Scientific Computing I
- HBM512 Scientific Computing II
- HBM538E Mathematical Methods in Data Analysis and Machine Learning
- HBM698E Computational Methods for Tensor Decomposition and Low-Rank Approximation
Contact
Email: suhatuna@itu.edu.tr
Office: Informatics Institute, Room: 206, Istanbul Technical University Ayazağa Campus