Human Digital Twin Lab
Overview
The Human Digital Twin Lab is dedicated to developing the next-generation, patient-centered computational models that represent the human body across multiple biological and behavioral scales. Our work integrates artificial intelligence, bioinformatics, and high-performance computing to construct dynamic digital representations of individuals, enabling personalized, predictive, and preventive health care.
At the core of our approach is a multi-scale, multi-layer digital twin framework that captures processes from cellular and molecular activity to organ systems, whole-body physiology, and mental and behavioral states. This unified representation evolves continuously through real-time data integration and advanced modeling.
Vision
To transform healthcare from reactive treatment to proactive, personalized care through continuously evolving human digital twins.
Mission
To design scalable, explainable, and clinically actionable digital twin systems that improve communication, decision-making, and health outcomes across diverse populations.
Director and Founder
Somayeh Bakhtiari Ramezani, Ph.D.
Assistant Professor of Computer Science and Data Science
Students
Brian Strong, MSDS ’25
Data Science Ph.D. student
Contact and Collaboration
We welcome collaborations across academia, health care systems, and industry partners interested in advancing personalized and intelligent health care systems.