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Resume

Bradley M. Bell
Principal Mathematician
Applied Physics Laboratory, University of Washington
1013 Ne. 40th Street, Seattle, WA, 98105-6698
206-543-6855,  bradbell@washington.edu, http://www.seanet.com/~bradbell

Education
 B.A.:   in mathematics and physics from Saint Lawrence University in 1973.
 M.A.:   in mathematics form University of Washington in 1976.
 Ph.D.:  in mathematics from University of Washington in 1984.

Employment
 1973-76:  Teaching Assistant for University of Washington.
 1976-78:  Computer Programmer for Flow Research.
 1978-82:  Computer Programmer for Applied Physics Laboratory.
 1982-84:  Student Fellow of Applied Physics Laboratory.
 1984-  :  Mathematician for Applied Physics Laboratory.
 2002-  :  Part time lecturer for Mathematics Department.

Team Projects
Team member on many projects; e.g., underwater tracking, underwater acoustic simulation, nonlinear random effects parameter estimation, non-parametric population analysis, modeling surface waves, acoustic super resolution, nonlinear pharmacokinetic analysis, creating a matrix based language.

Teaching
Taught linear programming for the Mathematics department of University of Washington. Worked with graduate students on research in Mathematics, Bioengineering, and Oceanography.

Commercial Software
Designed the O-Matrix language and developed its compiler and mathematical algorithms.

Designed and implemented the numerical methods in the SAAM II pharmacokinetic analysis software.

Open Source
Developed, distributed, and supported the COIN-OR C++ algorithmic differentiation package CppAD .

Developed, distributed, and supported other open source packages ; e.g., the documentation tool  omhelp, the Python algorithmic package  pycppad, the constrained Kalman smoother  ckbs, the L1 fitting and regularization tool  l1_regular, a library for by hand conversion from Matlab to C++  mat2cpp, and a program that models surface waves on the ocean  sar_iw.

Research
Preformed research in the following areas: linear and non-linear Kalman filtering and smoothing, algorithmic differentiation, deconvolution and stochastic function estimation, neuron modeling, pharmacokinetic analysis, global positioning, Fourier spectrum estimation, autoregressive modeling, semi-infinite programming, error correcting codes; see list of publications .

Skills Summary
Mathematics: optimization and numerical analysis, Kalman filtering and smoothing, algorithmic differentiation, statistical analysis of scientific data, Fourier spectral analysis, ordinary differential equation modeling and inversion, Monte-Carlo Methods, method of characteristics.

Languages and Systems: Auto(conf|make), Bash, Basic, Bugzilla, C++, C, Doxygen, Fortran, Gdb, Html, Lex, Matlab, Make, Mathematica, Octave, Pascal, Python, R, Sed, Subversion, Unix, Visual-Studio, Windows, Xml, Yacc.
Input File: resume.omh