Seeing Cancer’s Spread Through a Computational Window
Computational model allows researchers to simulate cellular-scale interactions across unprecedented distances in the human vasculature
Personal, Environmental & Population Health
Duke engineers are deeply engaged in improving the health of humans and our environment — from understanding and ameliorating disease at the molecular and genetic level, to developing technologies to improve global health, to exploring the interconnections between human health and environmental quality. A hallmark of our approach is extensive collaborations with leading physicians and scientists at Duke’s School of Medicine and Nicholas School of the Environment.
Major Centers and Initiatives
Engineer-Clinician Team Development
Improving Individual Health
Groups
- Bioelectric Engineering
- Biomaterials—Duke BME and Duke MEMS
- Biomedical Imaging
- Biophotonics
- Computational Modeling of Biological Systems
- Genetic Engineering
- Neural Engineering
- Synthetic Biology
Centers
- Center for Advanced Genomic Technologies (CAGT)
- Center for Biomolecular and Tissue Engineering (CBTE)
- Fitzpatrick Institute for Photonics (FIP)
- Impact of Genomic Variation on Function Characterization Center (IGVF)
- Kaganov Research Initiative in Pulmonary Medicine & Engineering with Duke’s School of Medicine
- Marcus Center for Cellular Cures with Duke’s School of Medicine
Improving Population Health
- Center for Global Women’s Health Technologies (Duke GWHT)
- Center for Water, Sanitation, Hygiene & Infectious Disease (WaSH-AID)
- Data Analytics for Population-Scale Screening, Diagnostics and Prognostics
- Duke Global Health Institute—university-wide
- Mapping Epigenetic Memory of Exposure to Observe (MEMENTO)
- NiCHES Children’s Environmental Health Research Center—with Duke’s School of Medicine
Environmental & Health Systems Research
Groups
Centers
Related News
Measuring Long-Term Heart Stress Dynamics With Smartwatch Data
A new “digital twins” computational framework captures personalized arterial forces over 700,000 heartbeats to better predict risks of heart disease and heart attack
Using AI to Create More Precise and Personalized Drug Delivery Solutions
With two NIH Awards totaling $2.8 million, Daniel Reker of Duke BME will design machine learning models to improve the development of more effective drug delivery tools.