Artificial Intelligence and Emerging Technologies in Medicine

The Artificial Intelligence & Emerging Technologies in Medicine (AIET) concentration of the PhD Program in Biomedical Sciences at ISMMS offers students with solid quantitative and technical backgrounds educational and research opportunities in AI/machine learning, next generation medical technologies (medical devices, sensors, robotics, etc.), and virtual/augmented reality simulation technologies for clinical applications or drug discovery.

AIET further leverages existing relationships with several well-regarded higher education institutions (State University of New York at Stony Brook, Rensselaer Polytechnic Institute (RPI), the Grove School of Engineering at the City College of New York, the Cooper Union - Albert Nerken School of Engineering, and the Hasso Plattner Institute of the University of Potsdam, in Germany) to offer complementary technical expertise to expand collaborative research and enrichment opportunities for trainees and faculty.

Artificial Intelligence and a variety of other powerful technologies (e.g., imaging, biotechnology, nanotechnology, information technology, cognitive science, and robotics) are paving the way for a new era of biomedical research, offering unparalleled opportunities to improve human health. In addition to receiving foundational education in the use of information systems, students enrolled in the AIET training area will learn how to develop and interpret predictive diagnostic and therapeutic models using a variety of machine learning tools based on statistics and probability theory, drawing upon quantitative fields such as computer science, mathematics, theoretical physics, theoretical/computational chemistry, and digital engineering.

Our curriculum offers a multifaceted training experience in various aspects of biomedical sciences, leveraged by AI/machine learning, computer systems, medical imaging, and a variety of next-generation medical technologies.

Meet Our Co-Directors

Hayit Greenspan, PhD is a Professor in the Department of Diagnostic, Molecular, and Interventional Radiology and Director of the BMEII AI Core. Prof. Greenspan has been conducting research in image processing and computer vision for the past 20 years, with a special focus on deep learning, image modeling and analysis, resolution augmentation, and content-based image retrieval. 

Alan Seifert, PhD, is an Assistant Professor in the Department of Diagnostic, Molecular and Interventional Radiology. The central theme of his research is to identify physiologically relevant MRI signals that are challenging to detect, and develop imaging methods that can quantify these signals, thus providing new and clinically valuable imaging biomarkers.

Meet Our Faculty

Faculty in AIET offer educational and research opportunities in AI/machine learning, next generation medical technologies (medical devices, sensors, robotics, etc.), and virtual/augmented reality simulation technologies for clinical applications or drug discovery.