Fatemeh Aghagoli’s educational background includes a Ph.D. program at the Iran University of Science and Technology, where she is studying in the Faculty of Mathematics and Computer Science. She was accepted into the program without a test as a brilliant talent. Additionally, Fatemeh holds a master’s degree in Mathematical Statistics from Iran University of Science and Technology. Her academic journey began with a bachelor’s degree in Statistics from the University of Qom, Iran.
Research Experience:
Fatemeh Aghagoli is a dedicated researcher with a focus on machine learning, image processing, artificial intelligence, cluster computing, and statistical modeling in medical science. She is currently pursuing a Ph.D. at the Iran University of Science and Technology, Faculty of Mathematics and Computer Science, under the supervision of Professor Rahman Farnoosh. Her academic journey began with a bachelor’s degree in Statistics from the University of Qom, Iran, followed by a master’s degree in Mathematical Statistics from Iran University of Science and Technology. Fatemeh’s research has yielded significant contributions, including the development of improved mixtures of factor analyzers based on dynamic co-clustering for the segmentation of brain MRI images. This work was published in Neurocomputing in 2024. She has also devised a novel approach for automatic tumor detection and localization in mammography images using a mixture of factor analyzers based on co-clustering, which was published in Biomedical Signal Processing and Control in 2024. Furthermore, Fatemeh has presented her research on entropy-based nonparametric methods for mammography image segmentation and the use of the k-mean algorithm and mean entropy in MRI images for brain tumor lesion detection at conferences.
Research Interest: