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Ionut-Gabriel Farcas, M.Sc.

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<pubsccs3 pubid=670479 person="Farcas" type="dt-konferenzbeitrag|dt-zeitschriftenaufsatz|dt-thesis" postfilter="type=dt-konferenzbeitrag ~ contribution-type=Textbeitrag / Aufsatz"/>
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== Talks ==
 
== Talks ==

Latest revision as of 10:33, 10 July 2019

Ionut.Farcas.jpg

Address:

TU München
Institut für Informatik
Boltzmannstr. 3
85748 Garching b. München
Office:
MI 02.05.053
Email:
Farcasimail.png
Phone:
(089) 289 18 634
Fax:
(089) 289 18 607
Office hours:
by arrangement

Contents

[edit] Research Interests

  • multilevel and multifidelity methods for uncertainty quantification
  • Bayesian inverse problems
  • adaptive sparse grid approximations for forward and inverse uncertainty quantification
  • reduced models for uncertainty quantification

[edit] Research Stays

  • 07.05.2019 - 09.05.2019, Leibniz University of Hanover (with Prof. Thomas Wick)
  • 01.03.2019 - 01.04.2019, Massachusetts Institute of Technology (with Prof. Youssef Marzouk)
  • 11.09.2018 - 14.12.2018, Institute for Pure and Applied Mathematics, University of California at Los Angeles
  • 15.03.2018 - 13.07.2018, University of Wisconsin at Madison (with Prof. Benjamin Peherstorfer)

[edit] Honours and awards

  • 2019, Best poster award at SIAM Conference on Computational Science and Engineering 2019, Spokane, Washington, USA
  • 2017, Best poster award at SIAM Conference on Computational Science and Engineering 2017, Atlanta, Georgia, USA
  • 2015 - 2018, DAAD Doctoral Research Grant
  • 2013 - 2015, DAAD Study Scholarship for Graduates

[edit] Travel grants

  • SIAM Student Travel Award for SIAM Conference on Uncertainty Quantification 2018, Garden Grove, California, USA

[edit] Publications

[edit] Talks

[edit] Posters

[edit] Teaching

[edit] Students

Volume 2017

  • D. Schmidhammer: Uncertainty propagation in linear gyrokinetic problems using sparse Leja quadrature [BibTeX].
    Bachelor's thesis, Fakultät für Mathematik, Technische Universität München, July 2017.
  • A. Ziller: Uncertainty Quantification of decoupled multi-component systems [BibTeX].
    Bachelor's thesis, Institut für Informatik, Technische Universität München, January 2017.

Volume 2016

  • J. Sültemeyer: Uncertainty Quantification in Fluid Flows via Polynomial Chaos Methodologies [BibTeX].
    Bachelor's thesis, Institut für Informatik, Technische Universität München, June 2016.