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Biography

Dr. Saber Kazeminasab is a distinguished researcher in computer vision, AI, and robotics, currently serving as a Postdoctoral Research Fellow at Harvard Medical School. With over 10 years of experience, Dr. Kazeminasab has made significant contributions to the development of surgical robots and advanced computer vision algorithms. His expertise extends to precision control systems, instrument-tissue tracking, phase detection, and iOCT registration with augmented reality devices and robotic systems.

Dr. Kazeminasab earned his Ph.D. in Computer Engineering from Texas A&M University. His research interests focus on various fields, including federated learning for ophthalmic imaging, deep learning for glaucoma diagnosis, longitudinal data analysis with irregular time intervals, and genome-wide analysis study (GWAS) for adjusting optic cup to optic disc ratio (CDR). He has authored numerous papers in prestigious journals and conferences, contributing significantly to understanding glaucoma progression patterns and high-risk patient identification.

His technical skills include proficiency in programming languages like Python, C++, and MATLAB, as well as machine learning frameworks such as TensorFlow, Keras, and PyTorch. Dr. Kazeminasab’s work aims to integrate augmented reality with robotic systems, enhancing the precision and effectiveness of surgical procedures.