Faculty Mentors

Dr. Jillian Cannons

Dr. Jillian Cannons is an Associate Professor in the Mathematics and Statistic Department at CPP.  Her research focuses on real-world optimization problems such as robot path planning, source seeking, and truck and drone delivery scheduling.  She and her students investigate, develop, and implement solutions using both linear programming and metaheuristic techniques.  Prior to joining CPP, Dr. Cannons spent 6 years in industry working as a software engineer at a robotics company, drawing on her educational background in Electrical and Computer Engineering.  She has over 25 years of experience with multiple programming languages including Pascal, C/C++, Java, Python, and MATLAB.

Dr. Briana Foster-Greenwood

Dr. Foster-Greenwood is an Associate Professor in the Mathematics and Statistic Department at CPP with research interests in algebra, graph theory, and combinatorics.  Her past project topics include Cayley graphs, metric dimension of graphs, and graph assembly, and the majority involved some coding to generate examples and make conjectures.  She frequently uses computer algebra software in support of her research, including GAP (Groups, Algorithms, and Programming), Macaulay2, and SageMath, and has over 10 years of experience with Mathematica.

Dr. Jimmy Risk

Dr. Risk is an Associate Professor in the Mathematics and Statistics Department at CPP, where he specializes in Gaussian process regression and data science.  His research interests span a broad spectrum, including machine learning, actuarial science, and finance, reflecting a commitment to interdisciplinary exploration.  Dr. Risk's extensive experience in programming with R and Python has not only enriched his classes but also empowered his graduate students.  These computational skills have been pivotal in the development of innovative algorithms and the execution of simulations across various research projects.

Dr. Ryan Szypowski

Dr. Szypowski is a Professor in the Mathematics and Statistics Department at CPP.  His background is, broadly speaking, in the field of numerical analysis, and more specifically focuses on provably convergent adaptive finite element methods, fast solvers, preconditioners, and parallel computing.  Dr. Szypowski has  undergraduate and master's degrees in computer science and has significantly contributed to large projects in areas such as computational graph theory, numerical relativity, and parallel implementations of methods for solving large linear systems.  He has software development experience from summer internships both in industry and at Lawrence Livermore National Laboratory, and he has programmed in many languages including C/C++, Java, Python, and MATLAB.