Manuel H. Tiglio
- Associate Research Scientist, CASS
Faculty, Center for Computational Mathematics (CCoM)
Research Scientist, San Diego Supercomputer Center (SDSC)
- Email: firstname.lastname@example.org
- Office: SERF 406 (CASS)
Office: E318 (SDSC)
Dr. Tiglio received his Ph. D. in Physics from the Universidad Nacional de Cordoba (Argentina) in October of 2000. Since then he has had a number of postdoctoral, research, visiting scholar and faculty positions at Penn State, Louisiana State University, Cornell University, the University of Maryland, and Caltech.
Dr. Tiglio’s research interests are in real-time solutions to complex problems, both forward (simulations) and inverse (parameter estimation, model selection, Bayesian inference) ones; uncertainty quantification, high order and spectral methods in complex geometries, heterogeneous computing and, more broadly: gravitational wave physics, computational mathematics, scientific computing and numerical analysis, in particular reduced order modeling, learning, and data mining.
Most recent five publications:
1) "Fast and accurate prediction of numerical relativity waveforms from binary black hole mergers using surrogate models"; Jonathan Blackman, Scott E. Field, Chad R. Galley, Daniel A. Hamburger Bela Szilagyi, Mark A. Scheel, Manuel Tiglio. To appear in Physical Review Letters (2015). eprint: arXiv:1502.07758
2) “Accelerated gravitational-wave parameter estimation with reduced order modeling”; Priscilla Canizares, Scott E. Field, Jonathan Gair, Vivien Raymond, Rory Smith, Manuel Tiglio. Physical Review Letters 114 (2015) 7, 971104
3) “Sparse representations of gravitational waves from precessing compact binaries”; Jonathan Blackman, Bela Szilagyi, Chad R. Galley, Manuel Tiglio. Physical Review Letters 113 (2014) 2, 021101
4) "Fast prediction and evaluation of gravitational waveforms using surrogate models”; Scott E. Field, Chad R. Galley, Jan S. Hesthaven, Jason Kaye, Manuel Tiglio. Physical Review X 4 (2014) 3, 031006
5) “Gravitational wave parameter estimation with compressed likelihood evaluations”; Priscilla Canizares, Scott E. Field, Jonathan Gair, Manuel Tiglio. Physical Review D 87 (2013) 12, 124005