Roles
Associate Professor
-
Biography
Siamak Yousefi, PhD, is an Associate Professor at the Bascom Palmer Eye Institute, University of Miami, with joint appointments in the Departments of Ophthalmology and Electrical and Computer Engineering. He directs the Data Mining and Machine Learning (DM2L) Laboratory, where his group develops state-of-the-art artificial intelligence (AI) and large language model (LLM)–based approaches to advance ocular imaging analysis, electronic health record mining, and clinical decision support.
Dr. Yousefi received his PhD in Electrical Engineering from the University of Texas at Dallas in 2012, focusing on biomedical pattern recognition and image analysis. He pursued postdoctoral training in neural signal processing and vision research at UCLA (2012–2013), followed by a fellowship at UC San Diego’s Shiley Eye Institute (2013–2014), where he later served as Research Scientist (2014–2016). He was also Adjunct Professor at San Diego State University (2014–2017) and a Visiting Assistant Professor at the University of Tokyo (2017).
He has authored more than 100 peer-reviewed publications in leading journals such as Ophthalmology, JAMA Ophthalmology, American Journal of Ophthalmology, The Ocular Surface, Investigative Ophthalmology & Visual Science (IOVS), and IEEE Transactions. His recent work has advanced the application of deep learning and ChatGPT-like models for glaucoma detection, neuro-ophthalmology, and corneal disease diagnosis. Dr. Yousefi serves on the editorial board of Translational Vision Science & Technology (TVST), is a Senior Member of the IEEE, and is an active member of ARVO. His research has been supported by NIH/NEI and private foundations, totaling over $4 million in competitive funding. -
Publications
Disclaimer: The information presented in this section has been consolidated using AI and machine learning technologies. While every effort has been made to ensure accuracy, errors may occur. If you identify any inaccuracies, please use this link to inform our data team. Your feedback is greatly appreciated and helps us improve the quality of our content.