Shifa Turan is a Professor in the Department of Obstetrics, Gynecology, and Reproductive Sciences at the University of Maryland, School of Medicine. She is the Director of the Fetal Heart Program and leads the department's cardiovascular research by bridging basic and clinical science. Her work in first-trimester cardiac evaluation, cardiovascular assessment, and the application of various imaging modalities in tiny hearts has been widely recognized in the field.

Dr. Turan is also at the forefront of integrating artificial intelligence (AI) into fetal cardiac imaging. She is currently pioneering the development and implementation of AI-driven tools to enhance the accuracy, efficiency, and early detection capabilities of fetal cardiac examinations. This innovative approach aims to standardize image acquisition and interpretation, allowing for earlier and more precise diagnosis of congenital heart disease. By combining her deep clinical insight with cutting-edge technology, she is shaping the future of prenatal cardiac screening and diagnostics.

Her expertise has allowed her to apply these methodologies across all animal models, improving translational research in obstetrics using a reverse approach—bedside to bench. She pioneered a stepwise approach for analyzing normal and diabetic mouse embryonic hearts using a 17.6 Tesla MRI.

Her clinical and basic science research continues to evolve. She is currently an NIH-funded investigator and holds grants focused on the baboon model to evaluate the protective cardiovascular effect of estrogen in baboon hearts. She is also the principal investigator in the project titled “Heightened hypoxia and DNA methylation in heart defects of diabetic embryopathy.”

Dr. Turan is deeply committed to education. She is responsible for teaching ultrasound to medical students, residents, and Maternal-Fetal Medicine Fellows in the department, as well as mentoring Ph.D. and master’s degree students. She has published over 80 original papers, reviews, and book chapters, and her work has been cited more than 3,000 times by fellow researchers.