Ph.D. Research
My Ph.D. thesis research focuses on investigating the potential of greedy approximation techniques in datadriven computational frameworks for robust design optimization of complex systems.
In the design of engineering systems, time and monetary expenses are often the primary burden for computational and physical experiments alike. Machine learning techniques can be applied to construct an interpolative surrogate model which serves as an approximation of the original highfidelity model or experiment and can be evaluated for fractions of the cost. However, these techniques often do not scale well for large sets of data  constructing inaccurate models at a high cost. My research looks into applying sequential greedy algorithms to solve the NPhard problems which usually arise when trying to construct approximate solutions to complex problems. By including approximations of various error metrics such as the leaveoneout cross validation error, we are able to construct adaptive surrogate models which offer improved accuracy as well as memory and solution costs that are orders of magnitude lower than classical methods. 
Other Research
I have previously worked on solar sail spacecraft research at the Advanced Space Concepts Laboratory of the University of Strathclyde in the UK. My research focused on developing an optimal control law for changing orbital elements during missions with solar sail propulsion.
While at Strathclyde, I worked closely with Professor Matteo Ceriotti (now at University of Glasgow), Dr Camilla Colombo (now at Politecnico di Milano), and Professor Colin McInnes (now James Watt Chair at University of Glasgow).

Courses
The following is a list of courses I have taken throughout my studies, sorted by topic, in alphabetical order.
Numerical Methods and Machine Learning
Numerical Methods and Machine Learning
 Computational Finance and Risk Management
 Fundamentals of Computational Fluid Dynamics
 Inference Algorithms
 Kernel Methods and Support Vector Machines (audit)
 Numerical Methods for Uncertainty Quantification
 Scientific Computing
 Simulation Design and Optimization
 Topics in Computational Fluid Dynamics
 Calculus I
 Calculus II
 Complex Analysis
 Computer Algorithms and Data Structures
 Digital and Computer Systems
 Economic Analysis and Decision Making
 Linear Algebra
 Mathematical Theory of Finance
 Partial Differential Equations
 Probability and Statistics
 Vector Calculus
 Aircraft Design
 Aircraft Flight
 Aerospace Propulsion
 Advanced Mechanics of Structures
 Control Systems
 Mechanics of Solids and Structures
 Space Systems Design
 Spacecraft Dynamics and Control
 Aerodynamics
 Combustion Processes
 Dynamics
 Electricity and Magnetism
 Gas Dynamics
 Molecules and Materials
 Quantum and Thermal Physics
 Relativity
 Thermodynamics
 Waves and Modern Physics