Gozde Unal

Gozde Unal received her PhD in Electrical and Computer Engineering, with a PhD minor in Mathematics, from North Carolina State University, Raleigh, NC, USA, in 2002. Following a postdoctoral fellowship at Georgia Institute of Technology, USA, she worked as a research scientist at Siemens Corporate Research, Princeton, NJ, USA, between 2003-2007. She was also a visiting researcher at HPLabs, Palo Alto, CA, and Xerox Labs, Webster, NY. She held positions of assistant professor and associate professor at Sabancı University, Faculty of Engineering and Natural Sciences between 2007-2015. In Fall 2015, Dr. Unal joined Istanbul Technical University (ITU), Faculty of Computer and Informatics Engineering, where she is currently a full professor. She is one of the founding professors of the new AI & Data Engineering Department at ITU and served as the founding director of the ITU-AI: the Artificial Intelligence and Data Science Research Center. She currently serves as the Department Head of the AI & Data Engineering Department within the Faculty of Computer and Informatics Engineering.

Dr. Unal was on sabbatical leave between 2023 and 2025. She has been an affiliated faculty member at the Center for Machine Learning, University of Southern Denmark, since 2023. From 2024 to 2025, she was a Senior Research Scientist at NYU Langone Health, NY, USA. During her sabbatical, her work focused on representation learning in discrete latent spaces, self-supervised learning—particularly for MRI-based foundation models—and uncertainty modeling and quantification.

Dr. Unal was the recipient of L’Oréal Turkey’s Female Scientist Award in 2010 in Life Sciences and the Distinguished Young Scientist Award from TUBA (GEBIP). She was awarded the Marie Curie Alumni Association (MCAA) Career Award of the European Commission in 2017. She served as a technical program co-chair for MICCAI 2016, Athens, Greece, and MIDL 2019, London, UK. She is currently a member of ITU-AI and the director of the ITU Vision Lab/Multimedia Lab. Her research interests are in AI, computer vision, deep learning, and machine learning.