Selin Aslan
Assistant Professor, Department of Mathematics, Koç University
Tuesday, August 5, 2025, 3:00-4:00 PM ET (1:00-2:00 PM MT)
Abstract: Computational imaging is fundamentally reshaping how we capture and understand visual information, transcending the inherent limitations of conventional optics. By integrating advanced numerical techniques with machine learning, this dynamic field has driven significant advancements across diverse domains, including microscopy, and medical imaging. Particularly, recent strides in large-scale 3D imaging have dramatically enhanced both resolution and robustness in complex real-world environments. In this talk, I will go over pivotal aspects of computational imaging, highlighting my contributions to tomography, phase retrieval, and image segmentation. I will demonstrate how these techniques address core challenges in reconstruction and analysis, thereby unlocking new applications and fostering interdisciplinary collaborations. The discussion will also illuminate current challenges and new opportunities, aiming to spark conversations on the future trajectory of imaging science.
Bio: Selin Aslan joined Koç University in Fall 2023 as an Assistant Professor in the Department of Mathematics. Prior to this, she was a postdoctoral appointee at Argonne National Laboratory, USA, where she collaborated with an interdisciplinary team of applied mathematicians, computer scientists, and physicists to develop new algorithmic and computational capabilities for next-generation microscopy instruments. Her primary research interest lies in developing algorithmic and computational solutions for large-scale imaging problems, with a special emphasis on inverse problems and optimization. Her work spans areas such as phase retrieval, tomography, large-scale data, and deep learning.
Host: Gunay Dogan
Note: Per the speaker's request, this talk was not recorded.
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