Assoc. Prof. Gulsen Taskin
Institute of Disaster Management
Istanbul Technical University
Assoc. Prof. Gulsen Taskin
Institute of Disaster Management
Istanbul Technical University
gulsen.taskin@gmail.comgulsen.taskin@itu.edu.tr
I received my bachelor's degree from the School of Geomatic Engineering. Since my passion and ambition has always been to study computer science, I applied to the computational science and engineering (CSE) department at ITU to do my master's degree and PhD. My research areas have been formed based on the experiences I achieved while in the Department of CSE at ITU.
I received my bachelor's degree from the School of Geomatic Engineering. Since my passion and ambition has always been to study computer science, I applied to the computational science and engineering (CSE) department at ITU to do my master's degree and PhD. My research areas have been formed based on the experiences I achieved while in the Department of CSE at ITU.
In my research, I have been acutely interested in machine learning (ML), working on more advanced techniques, and developing alternative ML methods to solve multiple issues encountered in various application domains. The ML topics on which I have mostly worked are methods, explainable AI, classification, multivariate regression, feature selection, feature extraction, manifold learning, model selection, and optimization, including heuristic methods. I have also been dealing with remote sensing image analysis, including earthquake damage assessment from high-resolution satellite images, hyperspectral image classification along with dimensionality reduction, and SAR data analysis for paddy-rice crop monitoring.
In my research, I have been acutely interested in machine learning (ML), working on more advanced techniques, and developing alternative ML methods to solve multiple issues encountered in various application domains. The ML topics on which I have mostly worked are methods, explainable AI, classification, multivariate regression, feature selection, feature extraction, manifold learning, model selection, and optimization, including heuristic methods. I have also been dealing with remote sensing image analysis, including earthquake damage assessment from high-resolution satellite images, hyperspectral image classification along with dimensionality reduction, and SAR data analysis for paddy-rice crop monitoring.
News!
News!
Applications are now open for the TÜBİTAK 1001 project, focusing on developing a novel explainable AI method for remote sensing image analysis using deep learning models.
Apply for Tubitak 1001 Project Scholarship