Reuben (Ruby) Shamir
About Reuben (Ruby) Shamir
Reuben (Ruby) Shamir is the Algorithm Team Manager at Novocure in Haifa, Israel, specializing in Deep Brain Stimulation and Tumor Treating Fields modeling.
Company
Reuben (Ruby) Shamir is currently employed at Novocure as the Algorithm Team Manager in Haifa, Israel. Novocure is a global oncology company working to extend survival in some of the most aggressive forms of cancer. He previously held the position of Senior Algorithms Engineer at the same company from 2018 to 2020.
Title
Reuben (Ruby) Shamir holds the title of Algorithm Team Manager at Novocure. His role focuses on developing and managing algorithmic solutions aimed at improving medical treatments and patient outcomes.
Education and Expertise
Reuben (Ruby) Shamir's educational background is firmly rooted in computer science and engineering. He earned a Bachelor of Science (BSc) in Computer Engineering, a Master of Science (MSc) in Computer Science, and a Doctor of Philosophy (PhD) in Computer Science from The Hebrew University of Jerusalem. His expertise includes Deep Brain Stimulation (DBS) modeling, Tumor Treating Fields modeling, machine learning for medical applications, high field (7T) MRI processing, tissue segmentation, image-to-patient registration, medical robotics, and Medical Augmented Reality (AR).
Professional Background
Reuben (Ruby) Shamir has an extensive professional background spanning various roles and institutions. He served as a Senior Technical Officer at Surgical Information Sciences in Minneapolis, MN, from 2015 to 2018. Prior to that, he was a Postdoctoral fellow at Case Western Reserve University in the Neuromodulation center, Dept. of Biomedical Engineering, School of Medicine from 2013 to 2015. He also worked as a Postdoctoral fellow at Edmond and Lily Safra Center - ELSC from 2010 to 2013 and as a Guest Researcher at Technische Universität München in 2010.
Research and Projects
Reuben (Ruby) Shamir has conducted various research projects focusing on medical innovations. He has worked on developing advanced planning methods for improving patient outcomes, specializing in Deep Brain Stimulation (DBS) and Tumor Treating Fields modeling. His research also includes utilizing machine learning techniques in medical applications, processing high field (7T) MRI to enhance clinical benefits, segmenting normal and abnormal tissues, and performing image-to-patient registration and error evaluation. Additionally, he explores the use of medical robotics and navigation systems, and investigates the application of Medical Augmented Reality (AR) in treatments.