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Vishwa S. Parekh, PhD

Academic Title:

Assistant Professor

Primary Appointment:

Diagnostic Radiology and Nuclear Medicine

Additional Title:

Technical Director, University of Maryland Medical Intelligent Imaging (UM2ii) Center

Phone (Primary):

410-706-4256

Education and Training

 

2007 - 2011        B.E.(Hons.), Computer Science

                                Birla Institute of Technology and Science, India

2011 - 2013        M.S.E., Computer Science

                                Johns Hopkins University, USA

2013 - 2018        Ph.D., Computer Science

                                Johns Hopkins University, USA

2018 - 2021        Postdoctoral Fellowship, Computer Science and Radiology

                                Johns Hopkins University, USA

Biosketch

Vishwa Parekh is an Assistant Professor of Diagnostic Radiology at UMB and the Technical Director of the UM2ii Center. Dr. Parekh is a computer scientist with over a decade of experience conducting multidisciplinary research with radiologists and other physicians for Artificial Intelligence in medical imaging. He received his MSE and PhD in computer science at Johns Hopkins, where he most recently served as the co-Director of AI for the Imaging Response Assessment Team. Dr. Parekh’s research focus is on building a bridge between the fields of radiology and engineering, specifically in building imaging techniques that could further the perceivable universe of information available to radiologists for making clinical decisions. He has published over 40 peer-reviewed manuscripts and his work has been recognized with numerous honors, including spotlight presentations at international conferences, including the ISMRM and Medical Imaging with Deep Learning (MIDL), as well as numerous patents encompassing the fields of AI, Radiology, and Oncology. Dr. Parekh's current work involves building an end-to-end collaborative lifelong learning platform for radiological decision support.

Research/Clinical Keywords

Artificial Intelligence, Machine Learning, Deep Learning, Image Processing, Computer Vision, Medical Imaging, Medical Image Analysis