|Ph.D.,||Rensselaer Polytechnic Institute,||(2017)|
|B.S.,||Florida State University,||(2013)|
National Cancer Institute (NIH)
Mathematical models of physical phenomena contain parameters, the values of which are important for accurately quantifying a modeled system. For biological models, many of the parameters are unknown due to the challenges of directly measuring such parameters, and therefore the parameters need to be estimated indirectly. My research focuses on designing experiments for obtaining the data from which model parameters are indirectly estimated. By optimizing the information content of the experimental data, it is possible to reduce the uncertainty of model parameter values and increase the accuracy of model predictions.