Research Interests

Computational medicine and data science have the potential to advance biomedical sciences when adapted to accommodate clinical practice. On the one hand, in computational medicine, physiology and patient data-driven mathematical models are built that aim to improve disease diagnosis and personalize treatment. On the other hand, data science can transform clinical data into usable information that can directly improve patient care. Combining these two could transform the healthcare system, providing new platforms to understand, diagnose, prevent, and treat diseases. 

My research interests primarily include developing computational tools to improve disease management and critical care by combining data science and mathematical physiology. These tools can be used to discover new disease markers, link physiology with pathology, and design new treatment strategies. Besides, I am interested in understanding underlying biological processes using novel mathematical tools based on monotone systems and deficiency theory to study the stability of equilibria and periodic behaviors.