Research
Interests
♠ Uncertainty Quantification :
Bayesian inverse problems, Polynomial Chaos, uncertainty propagation
♠ Statistics : Bayesian
statistics, design of experiments, Monte Carlo methods
♠ Nonlinear dynamics : Soliton
propagation, Bose-Einstein condensates, numerical simulations
Education
♠ Ph.D. in Applied Mathematics, USC -
08/2016
Thesis : Design, Adaptation and Variational Methods in
Uncertainty Quantification
♠ M.A. in Applied Mathematics, USC -
08/2014
♠ M.Sc. in Applied Mathematics, NTU Athens, Greece - 06/2011
Thesis : Nonlocal Soliton Dynamics (pdf in English... ...and in Greek)
♠ Erasmus visiting student KTH Stockholm, Sweden - 08/2008-06/2009
♠ Diploma in Applied Mathematical and Physical Sciences, NTU Athens, Greece - 09/2009
Thesis : Stability of Solitons to the Nonlinear Schrödinger equation
Research work - Publications
♠ Journals
·
Compressive sensing adaptation for polynomial chaos expansions
P. Tsilifis, X. Huan, C.Safta,
K. Sargsyan, G. Lacaze, J. Oefelein, H. Najm and R.G. Ghanem
Journal of Computational Physics (submitted) (2018)
·
The stochastic quasi-chemical model for bacterial growth: Variational Bayesian parameter update
P. Tsilifis, W.J. Browning, T.E. Wood,
P.K. Newton and R.G. Ghanem
Journal of Nonlinear Science (2017)
·
Homogeneous Chaos basis adaptation for design optimization under uncertainty: Application to the oil well placement problem
C. Thimmisetty, P. Tsilifis and R.G. Ghanem
Artificial Intelligence for Engineering Design, Analysis and Manufacturing 31 (3) 265-276 (2017)
·
Reduced Wiener Chaos representation of random fields via basis
adaptation and projection
P. Tsilifis and R.G. Ghanem
Journal of Computational Physics 341 102-120 (2017)
·
Efficient Bayesian experimentation using an expected
information gain lower bound
P. Tsilifis, R.G. Ghanem and
P. Hajali
SIAM/ASA Journal on Uncertainty Quantification 5(1) 30-62 (2017)
·
Computationally efficient variational approximations for
Bayesian inverse problems
P. Tsilifis, I. Bilionis, I. Katsounaros and N. Zabaras
ASME Journal of Verification, Validation and
Uncertainty Quantification, 1(3) 031004
(2016)
·
Markov Chain Monte Carlo inference of parametric dictionaries
for sparse Bayesian approximations
T. Chaspari, A. Tsiartas, P. Tsilifis and
S. Narayanan
IEEE Transactions on Signal Processing, 64(12) 3077 - 3092
(2016)
·
Cubic-quintic long-range interactions with doule-well
potentials
P.A. Tsilifis, P.G. Kevrekidis and
V.M. Rothos
Journal of Physics A, 47(3) 035201
(2014)
♠ Conferences - Presentations
Proceedings :
· Variational reformulation of Bayesian
inverse problems
P. Tsilifis, I. Bilionis, I. Katsounaros and N. Zabaras
ECCOMAS 1st International Conference on
Uncertainty Quantification in Computational Sciences and
Engineering (UNCECOMP2015), Crete island, Greece, 25-27 May 2015
Invited Talks :
·
Efficient methods for Bayesian experimental design and inference and dimensionality reduction for Polynomial Chaos expansions
Combustion Research Facility, Sandia National Labs,
Livermore, CA, USA, September 27, 2017
·
Gaussian Process regression for Sovereign Ratings forecasting
MIGA Department, World Bank Group,
Washington, D.C., USA, November 15, 2016
Talks/Abstracts :
·
Variance reduction methods for efficient Bayesian experimental
design
P. Tsilifis, R. Ghanem
SIAM Conference on Uncertainty Quantification (UQ16), EPFL
Campus, Lausanne, Switzerland, 5-8 April 2016
·
Variational Bayesian inference using basis adaptation in Homogeneous
Chaos surrogates
P. Tsilifis, R. Ghanem
SIAM Conference on Uncertainty Quantification (UQ16), EPFL
Campus, Lausanne, Switzerland, 5-8 April 2016
Posters :
·
Optimal Bayesian experimental design for subsurface characterization
of contaminated areas
P. Tsilifis, R. Ghanem, P. Hajali
CNLS Conference on Data Analysis (CoDA2016), Santa Fe, NM, USA, 2-4 March 2016
·
Markov Chain Monte Carlo inference of parametric dictionaries for sparse Bayesian approximations
T. Chaspari, A. Tsiartas, P. Tsilifis, S.S. Narayanan
2015 MBMC Workshop: Communications, Inference and Computing in Molecular and Biological Systems, USC, Los Angeles, CA, USA, 3 & 4 December 2015
·
Optimal Bayesian experimental design for contaminant transport under
uncertainty
P. Tsilifis, R. Ghanem
USACM 13th US National Congress on Computational Mechanics
(USNCCM13), San Diego, CA, USA, 26-30 July 2015
·
Optimal Bayesian experimental design for permeability identification
in the presence of contaminants
P. Tsilifis, R. Ghanem
SIAM
Conference on Mathematical and Computational Issues in the
Geosciences (GS15), Stanford University, Stanford, CA, USA, 29 June-2 July 2015
·
Variational reformulation of Bayesian inverse problems
P. Tsilifis, I. Bilionis and N. Zabaras
SIAM
Conference in Computational Sciences and Engineering (CSE15), Salt Lake
City, UT, USA, 13-18 March 2015
Graduate Coursework
♠ USC :
Real Analysis, Numerical Analysis, Introduction to
Mathematical Statistics I and II, Probability Theory I and II,
Econometric Methods, Economic and Financial Time Series,
Analysis of Variance and Design, Stochastic Differential
Equations, Stochastic Simulation, Filtering Theory,
Uncertainty Quantification, Computational Reservoir Modeling, Combinatorial
Analysis, Applied Matrix Analysis, Chaos Expansions and
Malliavin Calculus.
♠ NTUA :
Functional Analysis, Numerical Analysis and Finite Elements, Dynamical Systems and Chaos theory, Time-frequency Analysis and Wavelets, Nonlinear Functional Analysis, Harmonic Analysis, Partial Differential Equations, Nonlinear PDEs and Variational Methods.
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