Dr. Frieboes pursues an improved understanding of disease progression and treatment response by applying principles and techniques from engineering and the physical sciences. This interdisciplinary work integrates mathematical modeling, computational simulations, machine learning, and experiments along with pre-clinical and clinical data. The focus of this research is to predict, and in parallel validate, treatment response across spatio-temporal scales spanning from the omic to the organ, with the ultimate goal to personalize treatment to individual patient conditions. This work includes delivery of therapeutics and fabrication/characterization of delivery vehicles targeting the cancer microenvironment as well as infectious diseases. Projects in Dr. Frieboes’ laboratory have focused on evaluating nanotherapy and immunotherapy in cancer, analyzing metabolomic data for disease diagnosis and prognosis, and tackling infections in the genitourinary system via probiotic and antibiotic administration. In previous experience as an engineer in industry, Dr. Frieboes acquired knowledge and practice in system design and product development, theory and algorithms, software, and project/personnel management.