My research focuses on human airways and how they change with various disease conditions. I am interested in airway behavior in children with obstructive sleep apnea (OSA) and premature babies born with tracheomalacia (TM) and congenital abnormalities. My goals are to identify how airway problems affect patients’ symptoms, inform and evaluate surgical and therapeutic interventions, and differentiate the effects of airway abnormalities versus lung disease.
With a background in aerospace engineering, I previously worked for Formula One designing racing cars. This experience led to an understanding of aerodynamics. I have more than eight years of experience applying airflow knowledge to human airways, and I’ve worked at Cincinnati Children’s for more than three years. We have the world's first virtual models of human airways that move realistically base the motion on high-speed magnetic resonance imaging (MRI).
The effects of airway diseases can be hard to measure in patients. It is also hard to know which treatments will be effective. We create virtual models of airways from MRIs. We then use computational fluid dynamics (CFD) to simulate how air flows through the airway. This model shows us where in the airway are regions with high resistance. We can virtually alter the airway to predict how it would change after treatment. We also calculate the effect that treatment would have on airway symptoms. Our goal is to predict the best treatment approach for children with OSA and premature babies with TM.
My group's research led to “Best of Pediatrics” presentations in 2019 and 2020, hosted by the American Thoracic Society. I am a K99 grant recipient from the National Institutes of Health (NIH).
PhD: Imperial College London, London, UK, 2015.
BA, MEng: University of Cambridge, Cambridge, UK, 2008.
Airway disease; computational fluid dynamics (CFD); airflow; respiration; obstructive sleep apnea (OSA); tracheomalacia
Increased Work of Breathing due to Tracheomalacia in Neonates. Annals of the American Thoracic Society. 2020; 17:1247-1256.
1011 Comparison of MRI-based Dynamic 4D Airway Measurements and DISE Results in Pediatric Patients with Persistent OSA. Sleep. 2025; 48:a437-a438.
0452 Quantification of How Hypoglossal Nerve Stimulation Affects Upper Airway Neuromuscular Control Using Computational Airflow Modeling. Sleep. 2025; 48:a197-a198.
Computational Fluid Dynamics Analysis of Tracheal Pressure Difference in Neonates With Tracheoesophageal Fistulas Before and After Surgical Repair. American Journal of Respiratory and Critical Care Medicine. 2025; 211:a5119.
Serial MRI Evaluation of Tracheomalacia Changes in Neonates With Bronchopulmonary Dysplasia. American Journal of Respiratory and Critical Care Medicine. 2025; 211:a1284.
Evaluation of Magnetic Resonance Imaging (MRI) Anatomic Risk Factors to Predict Outcomes in Patients With Esophageal Atresia (EA). American Journal of Respiratory and Critical Care Medicine. 2025; 211:a2299.
Quantifying the Effect of Albuterol on Tracheal and Lung Compliance. American Journal of Respiratory and Critical Care Medicine. 2025; 211:a7086.
Clinical Outcomes Through Two Years for Infants With Bronchopulmonary Dysplasia and Tracheomalacia. Pediatric Pulmonology. 2025; 60:e27383.
The effect of including dynamic imaging derived airway wall motion in CFD simulations of respiratory airflow in patients with OSA. Scientific Reports. 2024; 14:17242.