Hanghang Wang, MD

Description

Hanghang Wang, MD, PhD is a cardiac surgeon and Assistant Professor of Surgery at Johns Hopkins, practicing at Suburban Hospital in Bethesda and The Johns Hopkins Hospital in Baltimore. She practices all aspects of adult cardiac surgery, with particular expertise in mitral valve repair, aortic surgery,  and complex redo operations. She also sees patients for second opinions on treatment options and timing of surgery. Dr. Wang earned a BA in Biology from Grinnell College, an MD from Dartmouth Medical School, and a PhD in Computational Biology and Bioinformatics from Duke University. She completed general surgery residency at Duke University Medical Center and cardiothoracic surgery fellowship at Johns Hopkins, followed by focused experience in complex mitral and aortic operations at high-volume centers including the University of Toronto. Dr. Wang directs the Cardiovascular Precision Medicine Laboratory at Johns Hopkins, which integrates cardiac surgery, computational biology, and bioengineering. Her work focuses on improving diagnosis, surgical decision-making, and recovery for patients with cardiovascular disease. She has contributed to biomarker discovery, standardized metabolomic profiling protocols, and the development of clinical registries and tissue biorepositories for aortic disease. She has presented at many national and international meetings and published in leading journals including JAMA Cardiology and Circulation. In addition to her clinical and research work, Dr. Wang is actively involved in surgical education and mentorship at Johns Hopkins and serves in national professional roles through the Society of Thoracic Surgeons. Current research interests include:  Biomarker Discovery: Identifying novel biomarkers for the rapid diagnosis of acute Type A aortic dissection Predictive Recovery Modeling: Combining imaging, medical records, and operative data to anticipate complications and guide personalized recovery  AI in Surgery: Developing AI-assisted personalized surgical planning for mitral valve repair and AI-assisted video analysis