معرفی
Mohsen Saffari is an Assistant Professor of Computer Engineering at Purdue University Northwest (PNW), joining the Electrical and Computer Engineering department in Fall 2024. His research and teaching focus on machine learning, deep neural networks, and their applications in spatiotemporal data analysis, particularly in power systems and computer vision. He holds a Ph.D. and is actively involved in advancing interdisciplinary approaches to energy systems and intelligent technologies.
His research emphasizes the theoretical and practical aspects of machine learning and deep learning models applied to spatiotemporal data. His work spans power systems optimization, including fault detection in power distribution networks and probabilistic optimal power flow analysis. In computer vision, he explores domain adaptation techniques for traffic scene understanding and masked face recognition. He also develops innovative methods like physics-informed graph neural networks and generative adversarial networks for solving complex engineering and healthcare challenges.
Recent trends in his publications highlight advancements in graph neural networks for power systems, spatiotemporal data applications, and domain adaptation in computer vision. His contributions include energy disaggregation techniques, photovoltaic forecasting, and medical imaging through interdisciplinary approaches combining deep learning with physics-based models.
Dr. Saffari’s teaching focuses on machine learning fundamentals, artificial neural networks, and software engineering. He advocates for engineers’ role in shaping societal advancements through critical thinking and innovation.
