University of California San Francisco'dan Assistant Professor Reza Abbasi-Asl 11 Ekim 2024 Cuma günü misafirimiz olacak.
"Spatio-temporal Modeling in Neuroscience through Interpretable Machine Learning" başlıklı sunumunu 11 Ekim 2024 Cuma günü saat 10.00'da fakültemizde yüz yüze gerçekleştirecektir.
Sunumun düzenleneceği odaya karar vermek için katılımcı sayısını kestirmek istiyoruz. Katılmak isteyenlerden aşağıdaki katılım formunu 8 Ekim Salı akşamına kadar doldurmalarını rica ediyoruz:
Konuşma özeti ve konuşmacıya ait kısa özgeçmişi aşağıda bulabilirsiniz:
Title: Spatio-temporal Modeling in Neuroscience through Interpretable Machine Learning
Abstract: In this talk, I will outline our research lab’s quest to investigate the role of advanced machine learning tools in understanding brain functions and related disorders. More specifically, I will present solutions based on interpretable machine learning to (1) integrate multi-modal spatio-temporal data collected from the brain (and body) in both microscopic and macroscopic resolutions, (2) predict functions of biological systems in different resolutions, and (3) determine the functional differences across neurological disorders.
Bio: Reza is an Assistant Professor in the Department of Neurology and the Department of Bioengineering and Therapeutic Sciences at UCSF. He is a core faculty member at the UCSF Neuroscape Center, a Weill Neurohub Investigator, and the Director of Data Analytics at the UCSF Weill Institute for Neuroscience. Before joining UCSF, Reza was a scientist at the Allen Institute for Brain Science in Seattle. He completed his PhD and MSc in Electrical Engineering and Computer Sciences at UC Berkeley in 2018, where he developed interpretable machine learning tools with applications in computational neuroscience. Reza is the recipient of the 2023 Kunal Patel Catalyst Award, New Frontiers Research Award from the Sandler Program for Breakthrough Biomedical Research (PBBR) in 2021, and 2022, and the Eli Jury Award from UC Berkeley, Department of Electrical Engineering and Computer Sciences in 2018.