Principal Investigator
Daniel P. Howsmon
Interrogating cellular and clinical time course data with mechanistic and data-driven strategies, Daniel is leading a team to elucidate dynamic systems at multiple scales to help patients today and provide pathways for the improved therapies of the future.
Graduate Students
Mahmoud M. Abdullah
Merging cell culture with mechanistic modeling, Mahmoud is elucidating crosstalk mechanisms that contribute to fibrosis mechanisms in the heart.
Maryam Vaez
Employing advanced data science models to clinical hemodynamics and vital signs, Maryam is building advanced alarm systems for postoperative monitoring.
Undergraduate Students
Charlie Everhart
Curating impulsive noise and integrating clinical notes, Charlie is identifying noise characteristics of clinical hemodynamic data.