George Mohler
CAM Assistant Adjunct Professor
UCLA Department of Mathematics
Email: gmohler at math.ucla.edu
Phone: 310 825 9369
George Mohler
CAM Assistant Adjunct Professor
UCLA Department of Mathematics
Email: gmohler at math.ucla.edu
Phone: 310 825 9369
Teaching
Math 33B: Differential Equations
REU Projects Supervised
Mike Egesdal, Chris Fathauer, Kym Louie, and Jeremy Neuman, Statistical Modeling of Gang Violence in Los Angeles,
Kit Curtius and Bryant Hirai, Statistical inference for anomalous diffusion with trapping in urban environments.
Tony De Cino, Simulation of point processes on networks.
Preprints
G. Mohler, A. Bertozzi, T. Goldstein and S. Osher, Fast TV Regularization for 2D Maximum Penalized Likelihood Estimation, submitted.
G. Mohler, M. Short, P. Brantingham, F. Schoenberg, and G. Tita, Self-exciting point process modeling of crime, submitted.
G. Mohler and M. Short, Geographic profiling from kinetic models of criminal behavior, submitted.
L. Smith, M. Keegan, T. Wittman, G. Mohler, and A Bertozzi, Improving Density Estimation By Incorporating Spatial Information, submitted.
Publications
H. D. Ceniceros, G. H. Fredrickson, and G. O. Mohler, Coupled flow-polymer dynamics via statistical field theory: modeling and computation,
Journal of Computational Physics, 228 (5), 1624, 2009.
E. M. Lennon, G. O. Mohler, H. D. Ceniceros, C. J. Garcia-Cervera, and G. H. Fredrickson, Numerical solutions of the complex Langevin equations in polymer field theory, Multiscale Modeling and Simulation, 6 (4), 1347, 2008.
H. D. Ceniceros and G. O. Mohler, A practical splitting method for stiff SDEs with applications to problems with small noise, Multiscale Modeling and Simulation, 6 (1), 212, 2007.
Education
Ph.D. Mathematics, UCSB, 2008
B.S. Mathematics, Indiana, 2003
Research Interests
pattern forming systems
computational mathematics and statistics
stochastic differential equations
spatial point processes
complex fluids
.
A model for the conditional intensity of earthquakes, with aftershock risk diffusing along a fault line.
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