Panteleimon (Pan) Pantelidis is a cardiologist and data scientist driven by a passion for the intersection of clinical practice in arrhythmias and electrophysiology, and artificial intelligence (AI) technology. He earned his medical degree from the Aristotle University of Thessaloniki, Greece, and an MSc in Data Science and Decision Analysis from the University of Stockholm, Sweden. He completed his clinical training at the 3rd Department of Cardiology in Athens, Greece, complemented by a clinical rotation in electrophysiology at Karolinska University Hospital in Stockholm, Sweden. Clinically based in Athens, he is also pursuing his PhD at the National & Kapodistrian University of Athens (NKUA), where his research focuses on analyzing cardiac arrhythmias using Artificial Neural Networks.

Throughout his academic and professional career, Panteleimon has authored more than 40 scientific papers in peer-reviewed journals. He serves as an elected Nucleus Member of the ESC Working Group on e-Cardiology, holding memberships with ESC, EHRA, HRS, and ACC. His research has been recognized with numerous awards for his projects and presentations from EHRA, the Hellenic Society of Cardiology, and the WHBA. Notably, he has been a Young Investigator Award (YIA) finalist at the ESC 2024 congress and is a 2025 Fulbright scholarship awardee.

Combining his clinical background in cardiology with his background in data science, Panteleimon is currently advancing his research at the Cardiovascular Data Science Lab (CarDS Lab) at Yale University. As a Fulbright scholar, his current position at the CarDS Lab centers around pursuing his PhD-level research. He focuses mainly on the design and development of AI-based electrocardiographic models to predict the future onset of arrhythmias, with the ultimate goal of improving proactive clinical alertness and patient care.

In his free time, Pan enjoys traveling, sailing, and playing the guitar.