Bishawi Recognized for Contributions to Research, School and Community

The award is presented annually to a fourth year student who has made exceptional contributions to the field of medicine, scientific knowledge, the community and the School of Medicine through outstanding leadership, industriousness, innovation, and vision.
Bishawi completed a Biochemistry Degree in 2008 and a Master’s Degree in Public Health in 2010 at Stony Brook before matriculating into the University’s School of Medicine. He has served as a key research resource for many residents in the School’s Department of Surgery and has assisted numerous medical students in designing their research projects.
“I have been extremely blessed during my time at Stony Brook as an undergraduate student, MPH graduate student and a medical student to be involved in such high quality research under the mentorship of really extraordinary scientists and clinicians,” said Bishawi.
“I cannot think of a better way to prepare for my future career as a surgeon scientist who will actively seek new ways to improve patient care.”
Since 2011, Bishawi has co-authored 17 peer-reviewed publications on topics such as cardiac surgery, colorectal cancer surgery, vascular surgery, plastic surgery, and surgical education. He has also co-authored three book chapters in the cardiac surgical field and 32 abstracts, presenting at 15 meetings since 2009.
“These accomplishments are just the tip of the iceberg,” said Dr. Anthony Girardi ’80, President of the Stony Brook School of Medicine Alumni Association. “Muath is a truly outstanding student who goes above and beyond his studies to pave the way for new breakthroughs and the success of our faculty and students. His ability to address scientific research questions in an integrated manner across scientific disciplines sets him apart from almost any other medical student.”
Bishawi plans to continue research in the field of clinical outcomes in surgery, specifically those of patients with cardiovascular and thoracic disease. His focus on risk stratification and risk prediction will help clinicians choose the right procedure for each patient to improve outcomes on an individual basis.
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