Web Stayman, Ph.D., M.S.

Joseph Webster Stayman, Ph.D., M.S.

Headshot of Web Stayman
  • Associate Professor of Biomedical Engineering

Research Interests

Medical Imaging; Device Design and Optimization; Adaptive Imaging; Computational Imaging; Task-Based Acquisition; Reconstruction; Machine Learning; and Estimation Theory ...read more


Dr. Joseph Webster Stayman is an assistant professor of biomedical engineering at the Johns Hopkins University School of Medicine. His research focuses on medical imaging systems including device design and optimization, adaptive imaging, computational imaging, task-based acquisition, reconstruction, machine learning, and estimation theory.

Dr. Stayman received his B.S. from Rensselaer Polytechnic Institute. He earned his M.S. and his Ph.D. from the University of Michigan.

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  • Associate Professor of Biomedical Engineering

Departments / Divisions



  • B.S.; Rensselaer Polytechnic Institute (New York) (1995)
  • M.S.; University of Michigan (Ann Arbor) (Michigan) (1998)
  • Ph.D.; University of Michigan (Ann Arbor) (Michigan) (2003)

Research & Publications


Dr. Stayman’s is the principal investigator for the Advanced Imaging Algorithms and Instrumentation Laboratory. The AIAI Lab is dedicated to high-fidelity modeling and design of medical imaging systems and the application of strong priors and knowledge of the class of objects being imaged to drive customized data acquisitions, data processing, and image formation algorithms that are optimized for specific imaging tasks. The lab’s mission to personalize medical imaging takes many forms including the design of dedicated imaging systems for specific anatomical sites, novel acquisition methods that permit adaptation of the medical imaging equipment to specific sites or diagnostic tasks, and novel image formation methods that accommodate non-standard or low-fidelity data.

Lab Website: Advanced Imaging Algorithms and Instrumentation Laboratory

Patient Ratings & Comments

The Patient Rating score is an average of all responses to physician related questions on the national CG-CAHPS Medical Practice patient experience survey through Press Ganey. Responses are measured on a scale of 1 to 5, with 5 being the best score. Comments are also gathered from our CG-CAHPS Medical Practice Survey through Press Ganey and displayed in their entirety. Patients are de-identified for confidentiality and patient privacy.

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