Prateek Prasanna

Prateek Prassana     

Assistant Professor

Department of Biomedical Informatics

Stony Brook, NY 11794


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Dr. Prateek Prasanna received his Ph.D. in Biomedical Engineering from Case Western Reserve University, M.S. in Electrical and Computer Engineering from Rutgers University, and B.Tech. in Electrical and Electronics Engineering from National Institute of Technology, Calicut, India. Prior to joining Stony Brook University, he was a Research Associate at CWRU and Case School of Medicine, Cleveland. Dr Prasanna’s research has involved developing companion diagnostic tools for thoracic-, neuro-, and breast-imaging applications. The overarching goal of his research is to bridge the gap between human and machine interpretation of biomedical imaging data via techniques such as radiomics, pathomics, deep learning, and multi-modal data fusion. Current research directions include developing quantitative tools to predict lesion growth, discovering imaging markers of disease progression, and identifying prognostic signatures of response to therapy.



  • Building clinically translatable medical image analytics and machine learning tools for enabling better treatment decisions and evaluating response to different therapies.
  • Application areas: (a) Decision support for early detection and diagnosis of oncologic and non-oncologic diseases via machine learning approaches, (b) Targeting therapeutic procedures and monitoring response (e.g. guiding immunotherapy in lung cancer), and (c) Characterizing pathologic processes using multiscale data integration (e.g. radiology, pathology, genomics).


Seeking talented and motivated candidates for MS/PhD/PostDoc interested in computational imaging. No prior experience in medicine is required. Interests in image analysis/machine learning, clinical applications, and collaborating with medical professionals are essential. 

Preferred technical skills for MS/PhD positions: Proficiency in Python and/or Matlab, prior experience in image analysis and machine learning is preferred.

Applicants for post-doctoral positions must have a PhD degree in Biomedical Engineering, Computer Science, Electrical Engineering or a related field, and a demonstrable record of accomplishment in image analysis, computer vision, and machine learning.