Ivana Jovanovic Buha, M.Sc. (hons)

Technical University of Munich

Department of Informatics
Boltzmannstr. 3
85748 Garching
Germany

Office: MI 02.05.040
Mail: ivana.jovanovic (at) tum.de
Tel: +49-89-289-18613
Office Hours: by arrangement

 

Background

Research interests

My research focuses on applied and computational mathematics, particularly on uncertainty quantification (UQ), modeling and system identification, inverse problems, and data-driven model learning. The main applications driving my research are from hydrology. More precisely, in my work, I am bridging the gap between theoretical work on High-dimensional Uncertainty Quantification and Bayesian Inversion, applied to relatively simple simulation models, and more complex real-world problems.

  • High-dimensional Forward Uncertainty Quantification and Sensitivity analysis (mainly, analysis of conceptual distribured hydrological models)
  • Sparse Grids Methods
  • Inverse problems - Bayesian Inference
  • Machine Learning

News

Ivana Jovanovic and Severin Reiz scored the 1st and 2nd place in the Best Poster Jury Award at CoSaS meeting in Erlangen, Germany, among 70 posters.…

Open and running student projects

If you are interested in a student project (Bachelor's or Master's Thesis or anything else), please contact me directly. See also the list of Student Projects at our chair.

Do you want to know what other students are working on in our chair? You are warmly encouraged to attend their presentations at the SCCS Colloquium! Come to get ideas, meet your potential supervisor, or to learn from the style of others for your own presentation.

Open student projects

see: https://www.in.tum.de/i05/jobangebote-studentische-projektarbeiten/job-offers-student-projects/uncertainty-quantification/

You can also come to my office and discuss possible topics.

Running student project

Finished Student Projects

2022

  • Markus Englberger: Using the Spatially Adaptive Combination Technique for Efficient Quantification of Uncertainty in Hydrological Models. Bachelor thesis, 2022 more… BibTeX Full text (mediaTUM)

2021

  • Hanna Weigold: Second-Order Optimization Methods for Bayesian Neural Networks. Master thesis, 2021 more… BibTeX
  • Jonas Fill: Development of the Bayesian Recurrent Neural Network Architectures for Hydrological Time Series Forecasting. Bachelor thesis, 2021 more… BibTeX Full text (mediaTUM)
  • Simon Zocholl: Development of Recurrent Neural Network Architectures for Hydrological Time Series Forecasting. Bachelor thesis, 2021 more… BibTeX Full text (mediaTUM)

2020

  • Jonas Treplin: Parallel Evaluation of Adaptive Sparse Grids with Application to Uncertainty Quantification of Hydrology Simulations. Projekt thesis, 2020 more… BibTeX Full text (mediaTUM)
  • Mathieu Putz: Developing a prototype of Bayesian Inference framework to recalibrate the complex hydrological model LARSIM. Studien thesis, 2020 more… BibTeX Full text (mediaTUM)

2019

  • Frank Schraufstetter: Development of a Prototype to Quantify the Uncertainty of the Water Balance Model LARSIM. Bachelor thesis, 2019 more… BibTeX Full text (mediaTUM)
  • Vyshakh Unnikrishnan: Implementation of a deep learning based model for rainfall-runoff modelling. Master thesis, 2019 more… BibTeX

Winter semester 2021/22

  • Einführung in die wissenschaftliche Programmierung (IN8008) [TUMonline] (Moodle)

Summer semester 2021

Winter semester 2020/21

  • Einführung in die wissenschaftliche Programmierung (IN8008) [TUMonline] (Moodle)

Summer semester 2020

Winter semester 2019/20

Summer semester 2018/19

Winter semester 2018/19

Winter semester 2016/17

Publications

Posters

2022

  • Ivana Jovanovic Buha; Michael Obersteiner; Tobias Neckel; Hans-Joachim Bungartz: Efficient Uncertainty Quantification and Global Time-Varying Sensitivity Analysis Using the Spatially Adaptive Combination Technique. SIAM Conference on Uncertainty Quantification (UQ22), SIAM, 2022Atlanta, Georgia more…

2021

  • Ivana Jovanovic Buha; Florian Künzner; Tobias Neckel; Hans-Joachim Bungartz: Efficient Uncertainty Quantification and Global Time-Varying Sensitivity Analysis of Conceptual Hydrological Model. SIAM Conference on Computational Science and Engineering (CSE21), SIAM, 2021Fort Worth, Texas, U.S.A. more…

Other activities

  • Organizational support for "BGCE Student Paper Prize" for the best paper at the SIAM CSE  (2019, 2021)
  • Responsible for Chair's new website (2019- today)