Research in stochastic optimal control and games. Worked on a new machine learning methodology for solving stochastic differential games with delay. This has been applied to solve financial models from areas such as systemic risk to competition between portfolio managers. The full research for this topic is shown here: https://arxiv.org/pdf/2307.06450.pdfAlso, I worked on applying stochastic control and game theory to the Covid-19 pandemic using machine learning techniques to solve for Nash equilibrium policy decisions. For more info, see: https://msml21.github.io/papers/id42.pdf and https://www.ams.org/journals/notices/202211/rnoti-p1878.pdf.

Developed quantitative models in VBA for portfolio optimization and analysis under realistic market features such as fat tails.

- Research in approximation methodologies applied to analysis of a class of stochastic PDEs.- Tutoring Colorado School of Mines students in courses Calculus I-III, Differential Equations.- Teaching assistant in Applied Mathematics and Statistics courses.

- Research Experience for Undergraduates (REU) in mathematics-- a paid undergraduate research position studying nonlinear PDEs. - Mathematical analysis for nonlinear PDE coupled with numerical analysis.- Developed code in C++ for numerical solutions to free boundary problems.