I am a computer scientist specializing in artificial intelligence and deep learning, with a focus on applications in electron microscopy. I currently lead the Deep Learning for Electron Microscopy group at Forschungszentrum Jülich’s Institute for Materials Data Science and Informatics (IAS-9).

I earned my Ph.D. in Geodesy and Geoinformatics from Leibniz University Hannover in 2021, where I worked on self-supervised learning for archaeological object detection in LiDAR data. I have a master’s degree in Artificial Intelligence from the Polytechnic University of Catalonia and a bachelor’s degree in Computer Engineering from Middle East Technical University.

My research interests include self-supervised learning, deep active learning, and computer vision techniques applied to electron microscopy data analysis. My goal is to advance material characterization and understanding through AI methods.

Recently, I was selected for the prestigious Young Excellent Scientist Program (YESP) at Forschungszentrum Jülich, recognizing my potential as an early career researcher. I am also coordinating the SOL-AI project, funded by the Helmholtz Foundation Model Initiative, which focuses on developing foundation models for solar energy materials development.