The Computational Electrocardiology Group
Directed by Professor Rob MacLeod and Assistant Professor Karli Gillette
Our research seeks to apply mathematical and computational tools to understand physiological and pathophysiological processes in the field of cardiology. The CEG focused on research domains such as electrocardiographic imaging, cardiac digital twinning, body surface mapping, myocardial ischemia, ventricular arrhythmias, and other cardiac pathologies using tools such as simulation, uncertainty quantification, large animal experimental models, machine learning, and shape analysis. For specific information about our ongoing research efforts, please visit our research page!
We are an interdisciplinary lab that is joint between the College of Engineering and the School of Medicine. We are affiliated with the Department of Biomedical Engineering, the Nora Eccles Harrison Cardiovascular Research and Training Institute, and the Scientific Computing and Imaging Institute. We have students from a variety of different research interests and backgrounds. For example, we’ve worked with students focused on computational, medical, and experimental tracks, just to name a few. Our diversity breeds innovation, and to this end, we value and respect individuals from diverse backgrounds. We are an inclusive and supportive research group that is committed to promoting diversity and equality in STEM.
If you are a student interested in joining our group, please visit our prospective students page for undergraduate research opportunities. Prospective students at the University of Utah are encouraged to take Dr. MacLeod’s Fundamentals of Biomedical Engineering II (BME 2100) course, available every Fall semester. Taking the course is not a prerequisite to work in the lab, but it does provide an excellent opportunity to gain relevant background to our research.
Recent News
CEG members publish new research in Heart Rhythm O2, highlighting machine learning classification tasks for effective ECG diagnosis.
Self-Supervised Contrastive Learning Enables Robust ECG-Based Cardiac Classification
January, 2026
Two CEG members (Jake Bergquist, Eric Paccione) have been accepted to present their research at the 2026 Heart Rhythm Society Conference in Chicago
January, 2026
CEG Ph.D. student Anna Busatto successfully defends her dissertation.
January 20th, 2026
Contact Info:
Rob S. MacLeod, Ph.D. ()
Office: Warnock Engineering Building (WEB) 4602
Karli Gillette, Ph.D. ()
Office: Warnock Engineering Building (WEB) 4640