Usman Mahmood

Dr. Usman Mahmood serves as Assistant Professor at Weill Cornell Graduate School of Medical Sciences and assistant attending physicist at Memorial Sloan Kettering Cancer Center (MSKCC). He directs the X-ray methods and computed tomography physics course within Weill Cornell Medical College's biomedical imaging graduate program, bridging medical physics, artificial intelligence, and oncological imaging to enhance diagnostic accuracy while prioritizing patient safety and equity.

His educational background includes:

• B.S. in Physics from Stony Brook University (cum laude)
• M.S. in Medical Physics from Columbia University
• Ph.D. from Rochester Institute of Technology (completed while working at MSKCC)

Dr. Mahmood's research focuses on developing quantitative imaging and AI methodologies for precise tumor characterization in radiological imaging. His lab leverages invisible quantitative features from medical images to enhance cancer diagnosis and treatment, with emphasis on data quality and reliability. Current projects include AI-driven tumor characterization, 3D printing for imaging validation, ethical radiological AI tools in oncology, and quality assurance methodologies. His work addresses AI's potential biases while advancing diagnostic accuracy through rigorous validation frameworks.

His publication portfolio demonstrates consistent innovation at the medical physics-AI intersection, with recent work emphasizing practical validation frameworks using 3D-printed phantoms that replicate tumor micro-textures. A recurring theme is establishing tangible benchmarks for AI tools in clinical settings, ensuring algorithmic predictions maintain clinical relevance while mitigating risks associated with radiological AI deployment.

Notable distinctions include:

• 2020 MSK Physics Clinical Service Award for work in CT
• 2018 President of Radiological and Medical Physics Association of NY
• 2014 Diplomate, American Board of Radiology - Diagnostic Imaging Physics

As a board-certified diagnostic medical physicist, Dr. Mahmood mentors students in developing 3D-printed phantoms that replicate complex anatomical shapes of tumors. His leadership extends to directing educational programs and professional associations. His research utilizes institutional resources at MSKCC to develop large-scale datasets for training AI systems in cancer classification on CT scans, with emphasis on clinical translation and ethical implementation.

Dr. Mahmood leads a research group focused on bridging physical and digital realms in medical imaging. His lab develops 3D-printed phantoms providing real-world benchmarks for validating quantitative imaging features, enhancing AI diagnostic reliability through physical counterparts to digital images. This approach ensures technically advanced solutions maintain clinical significance and patient safety as primary considerations.