Joo Heung Yoon

Joo Heung Yoon, MD is an Assistant Professor of Medicine in the Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine at the University of Pittsburgh School of Medicine. His research develops machine learning models for predicting hemodynamic instability in critical care settings, with applications extending to space medicine environments.

His educational background includes:

• MD from Catholic University of Korea, Seoul, South Korea (2002)
• Internal Medicine Internship at Maimonides Medical Center - SUNY Downstate (2007)
• Internal Medicine Residency at New York Medical College (2009)
• Research Fellowship at Massachusetts General Hospital / Harvard Medical School (2011)
• Research Fellowship at Beth Israel Deaconess Medical Center / Harvard Medical School (2014)
• Fellowship in Pulmonary and Critical Care Medicine at University of Pittsburgh School of Medicine (2017)

Dr. Yoon specializes in identifying hidden pathologic patterns through machine learning, developing prediction models for shock, hemorrhage, and tachycardia using large-scale clinical data. His work bridges critical care medicine with AI, focusing on real-world ICU implementation through alert systems and user interfaces. He actively explores microgravity applications, aiming to create feasible prediction algorithms for resource-constrained space missions where timely high-stake decisions are critical.

His publication trend (2018-2020) reveals consistent advancement in hemodynamic prediction models, transitioning from theoretical frameworks to practical implementation strategies. These works integrate supervised ML and deep neural networks to address circulatory shock, hemorrhage identification, and instability surrogates, demonstrating strong interdisciplinary collaboration between clinical medicine and engineering.

Notable awards include:

• SCCM Gold Snapshot Award (2019)
• ATS Abstract Award (2018)
• Excellence in Clinical Service Award (2010)
• Partners in Excellence Award (2009)
• Richard D. Levere Teaching Award (2008)

As Principal Investigator for NIH K23 grant GM138984 (2020-2025), Dr. Yoon leads research on machine learning-driven shock prediction models. He mentors medical students and house staff daily in the ICU, specializing in cardiopulmonary physiology teaching. His grant portfolio focuses on therapeutic strategies for circulatory shock in critically-ill patients, with strong industry-academic partnerships.

Based at UPMC Montefiore, Dr. Yoon collaborates with Carnegie Mellon University's Machine Learning School and Pitt Engineering to develop clinical decision support systems. His team is designing graphic user interfaces for spaceflight applications where resource limitations demand highly efficient predictive analytics for hemodynamic crises.