Dr. Gloria Hyunjung Kwak is a tenure-track Assistant Professor at Emory University’s School of Nursing and a member of the Centre for Data Science. Her research focuses on developing equitable AI in healthcare, with a particular emphasis on fairness in AI-driven clinical decision-making. She aims to bridge the gap between advanced AI techniques and real-world healthcare applications, fostering more just and inclusive healthcare solutions.

Practice-Pattern Variation in Neurocritical Care Blood Pressure Control Reveals Opportunities for Improved Long-term Hypertension Control
Megan Kennelly, Andrew J. Webb, Sophie E. Ack, Gloria Hyunjung Kwak, Jonathan Rosand, Eric Scott Rosenthal
Neurology Clinical Practice, 2025

Septic Shock Requiring Three Vasopressors: Patient Demographics and Outcomes
Gloria Hyunjung Kwak, RWMA Madushani, Lasith Adhikari, April Yujie Yan, Eric S. Rosenthal, Kahina Sebbane, Zahia Yanes, David Restrepo, Adrian Wong, Leo Anthony Celi, and Emmett Kistler
Critical Care Explorations, 2024

Social Determinants of Health and Limitation of Life-Sustaining Therapy in Neurocritical Care: A CHoRUS Pilot Project
Gloria Hyunjung Kwak, Hera A. Kamdar, Molly J. Douglas, Hui Hu, Sophie E. Ack, India A. Lissak, Andrew E. Williams, Nirupama Yechoor, and Eric S. Rosenthal
Neurocritical Care, 2024

EchoNotes Structured Database Derived from MIMIC-III (ECHO-NOTE2NUM)
Gloria Hyunjung Kwak, Dana Moukheiber, Mira Moukheiber, Lama Moukheiber, Sulaiman Moukheiber, Neel Butala, and Leo Anthony Celi
PhysioNet, 2024

Health Beyond Clinical Data: How Social Determinants of Health Impact Health Predictions
Ming Yang, Gloria Hyunjung Kwak, Tom Pollard, Leo Anthony Celi, and Marzyeh Ghassemi
AAAI/ACM Conference on AI, Ethics, and Society, 2023

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Dr. Kwak’s teaching philosophy centers on integrating practical, real-world applications of AI in healthcare, drawing from her academic background and industry experience. She strives to cultivate a collaborative learning environment where students actively engage with real-world cases, seamlessly connecting theoretical concepts with practical implementation. While emphasizing the importance of fairness and ethical considerations in AI, her primary focus is on equipping students with the skills to effectively apply AI solutions in healthcare settings. She encourages teamwork, cross-disciplinary collaboration, and critical thinking, preparing students to tackle complex challenges and drive innovation in the evolving landscape of healthcare. Dr. Kwak has taught AI-track PhD courses in the nursing school, including NRSG 752: Foundations of Computation for Nursing Research II. She has also been invited to give lectures and talks at various institutions. Her research and teaching experience provide a strong foundation for mentoring students across disciplines and academic settings.

Her research is dedicated to advancing fairness in AI applications within healthcare, with a focus on precision medicine in critical care, disability patient groups, and socially vulnerable populations. By analyzing treatment pattern variations across hospitals, she aims to identify and address disparities in care delivery. Leveraging cross-modal machine learning techniques, her work seeks to develop AI models that are both accurate and equitable, ensuring that these technologies benefit diverse patient populations rather than reinforce existing biases.

More information about her work and teaching approach can be found on her website: http://eq-ai-health.org/.