Jonas Latz, M.Sc.

Name :	Jonas Latz
Address :	M2 - Lehrstuhl für Numerische Mathematik
	Boltzmannstraße 3
	85748 Garching b.M.
Office :	03.10.055
Phone :	+49 89 289 18404
E-mail :	jonas.latztum.de (Send me an encrypted email)

Research

Various topics in Numerical Analysis, Computational Science, Probability Theory and Statistics. Some keywords:

Uncertainty Quantification: Forward propagation and Inverse Problems, Multilevel and Multifidelity methods, Discretisation of Random fields
Computational Bayesian Statistics: Markov Chain Monte Carlo, Sequential Monte Carlo, Ensemble Kalman Filters, Model Selection
Surrogate Models: Reduced Basis Methods, Sparse Grids
Applications: Plasma Physics, Engineering (ERA) and Biology
Further interests: Machine Learning, Measure Theory, Approximation of Probability Distributions, Interpretation and Foundations of Probability and Statistics, High-performance Computing

Jonas Latz, Marvin Eisenberger, Elisabeth Ullmann (2018): Fast Sampling of parameterised Gaussian random fields, submitted. (Abstract, Bibtex, Isaac Newton Institute preprint )
Jonas Latz, Iason Papaioannou, Elisabeth Ullmann (2018): Multilevel Sequential² Monte Carlo for Bayesian Inverse Problems, J. Comp. Phys. (accepted for publication). (Abstract, Bibtex, ArXiv preprint )

(July 1st-6th 2018) 13th International Conference in Monte Carlo & Quasi-Monte Carlo Methods in Scientific Computing (MCQMC 2018) , Garden Grove, CA, USA.
(April 16th-19th 2018) SIAM Conference on Uncertainty Quantification 2018 (UQ18) , Garden Grove, CA, USA.
(March 19th-23rd 2018) GAMM Annual Meeting 2018 , Munich, Germany.
(February 20th 2018) Seminar , Isaac Newton Institute, Cambridge, United Kingdom.
(February 5th-9th 2018) Surrogate models for UQ in complex systems , Isaac Newton Institute, Cambridge, United Kingdom. (Poster)
(November 22nd 2017) Seminar Stochastics, Statistics and Numerical Analysis, Universität Mannheim, Germany. (Slides)
(September 6th-8th 2017) FrontUQ in Engineering, Munich, Germany.
(June 15th-17th 2017) 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017) , Rhodes, Greece.
(March 24th 2017) Group Seminar, Hybrid Materials Interfaces Group, Universität Bremen, Germany.

(September - November 2018) Chair of Scientific Computing and Uncertainty Quantification, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. (with Fabio Nobile)
(February 5th-23rd 2018) Isaac Newton Institute, University of Cambridge, UK.
(November 20th-22nd 2017) Chair of Mathematical Optimization, Universität Mannheim, Germany. (with Claudia Schillings)

(Summer term 2018) Tutorials in Numerical Methods for Uncertainty Quantification,
(Winter term 2017/18) Tutorials in Einführung in die Numerische Lineare Algebra,
(Summer term 2017) Tutorials in Numerical Methods for Uncertainty Quantification and Supervision in Hauptseminar: Uncertainty Quantification with Efficient Monte Carlo Methods,
(Winter term 2016/17) Tutorials in Maß- und Integrationstheorie,
(Term 1/2 2015/16) Undergraduate Supervisor (Mathematics Institute, University of Warwick),
(Summer term 2015) Tutorials in Elemente der Analysis 2 (Fachbereich IV, Universität Trier),
(Winter term 2014/15) Tutorials in Elemente der Analysis 1 and Tutorials in Mikroökonomik (Fachbereich IV, Universität Trier),
(Winter term 2013/14) Tutorials in Mikroökonomik (Fachbereich IV, Universität Trier).

(ongoing) Sabrina Balzer (M.Sc. student, working title: Surrogate construction for a Cahn-Hillard model and Bayesian Inversion; with Christian Kahle and Elisabeth Ullmann)
(ongoing) Fabian Wagner (M.Sc. student, working title: Particle Methods for Deep Learning)
(ongoing) Matthieu Bulte (B.Sc. student, working title: Bayesian Updating of a mathematical pendulum ode with noisy data)
(ongoing) Konstantin Riedl (B.Sc. student, working title: The Multifidelity cross-entropy method; with Elisabeth Ullmann)
(2017) Marvin Eisenberger (M.Sc. student, working title: Efficient parameterised solving of KL Eigenproblems)

(ongoing) Doctoral Studies in Mathematics, Technische Universität München, Germany
(2015-2016) Master of Science in Scientific Computing (with Distinction), University of Warwick, UK
(2014-2016) Master of Science in Applied Mathematics and Economics, Universität Trier, Germany
(2012-2014) Bachelor of Science in Business Mathematics, Universität Trier

Jonas Latz (2016): Bayes Linear Methods for Inverse Problems, Master's Thesis, University of Warwick. (*.pdf | *.bib)

Reading Group Uncertainty Quantification
Project 10.02/BAYES@International Graduate School of Science and Engineering at TUM.
Networks: GitHub\latz-io , orcid.org , researchgate
Lunch menus@Garching: FMI Cafeteria, IPP Canteen , Mensa
Science Communication:
- Uncertaintea Quantification (Youtube) , Science Slam, Hamburg, 2017 (in German)
- Latz, Ullmann: Bayes'sche Inversion am Beispiel des Fadenpendels, in Quartl 84, Garching, 2017 (in German)
- Latz, Ullmann: Wie lernen Computer die Erdbeschleunigung?, in TUM Campus Magazin, 01/2018 (in German)