Assistant Years Experience

Ryan Compton - Resume

UCLA Mathematics Department O ce: MS 3965

Box 951555 ********@****.****.***

Information

Los Angeles,CA 90095 310-***-****

www.math.ucla.edu/ rcompton/

webpage:

Numerical linear algebra, image processing, complex networks, parallel computing.

Specializations

Finishing PhD Student in Mathematics at UCLA

Education

Fall 2006-present

Thesis title: A Sparse Spectral Method for Hamiltonian Eigensystems.

Advisor: Chris Anderson

MS, Mathematics, April 2008, UCLA.

BA, Mathematics/Physics, May 2006, New College of Florida, Sarasota, FL

Thesis title: Optimizing Cover Times with Constraints.

Advisor: Patrick McDonald

Research sta, HRL Laboratories, Summer 2011. Worked in the information and systems science

Professional

lab with the goal of forecasting large sudden changes in social networks.

Ryan Compton, Stanley Osher and Louis Bouchard, Hybrid regularization for MRI reconstruction

Research

with static eld inhomogeneity correction, IEEE International Symposium on Biomedical Imaging, May 2012

Ryan Compton, Hankyu Moon and Tsai-Ching Lu, Catastrophe prediction via estimated network

autocorrelation, WIN Workshop on Information in Networks, September 2011

Ryan Compton, A sparse spectral method for Hamiltonian eigensystems, UCLA technical report,

January 2011

NSF VIGRE Fellowship, Fall 2006-2010. Grant from the NSF provides partial funding for graduate

Awards

education/research through 2010.

UCLA Teaching Assistantship, Fall 2006-present. Awarded by UCLA, provides partial funding for

graduate education/research.

Computer Skills Five years experience developing numerical methods in C/C++, Python, and MATLAB.

Classes taken Real Analysis (3 quarters), Applied Di erential Equations (3 quarters), Numeri-

Coursework

cal PDE (2 quarters), Complex Analysis, Probability (2 quarters), Numerical Linear Algebra (2

quarters), Programming for Statistics (2 quarters).

Qualifying exams Applied Di erential Equations, Numerical Analysis.

Teaching Assistant, Math 170B (Probability) Laws of large numbers and Markov chains.

Teaching

Teaching Assistant, Math 164 (Optimization) Simplex methods and polytopes.

Teaching Assistant, Math 1142 (Mathematical Modeling) Fall 2008. Conservation laws

in the context of tra c ow.

Teaching Assistant, Math 136 (Partial Di erential Equations) Spring 2008. Heat equa-

tion, wave equation, Poisson equation.

Teaching Assistant, PIC 10b (Intermediate C++) Winter 2008. Dynamic memory allo-

cation and data structures.

Teaching Assistant, PIC 10a (Introductory C++) Spring-Fall 2007. Fall-Winter 2010.

Fall 2011. Basic syntax and programming in C++.

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