Ivana Jovanovic Buha, M.Sc. (hons)

Technical University of Munich

TUM School of CIT
Department of Computer Science
Boltzmannstrasse 3
85748 Garching

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



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 distributed hydrologic models)
  • Sparse Grids Methods
  • Inverse problems - Bayesian Inference
  • Machine Learning

Open and running student projects

Runnin student projects

  • Boris Liu: "Accounting for parameter uncertainty and time-varying sensitivity analysis of the HBV-SASK hydrologic model using sequential data assimilation and pseudo-spectral methods". Bachelor's thesis, CIT School - Computer Science Department; Since October 2023Hi Tobi, 

Open student projects

If you are interested in a student project (Bachelor's or Master's Thesis or anything else), it is the best to contact me directly. Here is the list of some projects that I would offer at the moment (the list is not exhaustive):

  1. "UQ and SA of Hydrologic model HBV using pyApprox software tool"

  2. "Calibration under uncertainty of the HBV hydrologic model using a parallel implementation of the Metropolis-Hastings algorithm"

  3. "Running Uncertainty Quantification simulations using the UM-Bridge software tool: application on a hydrologic model"

  4. Mapping sparse grid interpolation to pseudospectral approximation 

  5. Calibration under uncertainty of the simple hydrologic model using different software tools, e.g., DREAM (Dakota), MUQ

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

See also the list of Student Projects at our chair, e.g.,  https://www.in.tum.de/i05/jobangebote-studentische-projektarbeiten/job-offers-student-projects/uncertainty-quantification/

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.


Finished Student Projects


  • Boris Liu: Accounting for states and parameter uncertainty of the HBV-SASK hydrologic model using particle filtering as a sequential data assimilation technique. Bachelorarbeit, 2024 mehr… BibTeX
  • Oleksandr Pokras: Artificial Intelligence for Team Productivity. Bachelorarbeit, 2024 mehr… BibTeX Volltext (mediaTUM)


  • Markus Englberger: Using the Spatially Adaptive Combination Technique for Efficient Quantification of Uncertainty in Hydrological Models. Bachelorarbeit, 2022 mehr… BibTeX Volltext (mediaTUM)


  • Hanna Weigold: Second-Order Optimization Methods for Bayesian Neural Networks. Masterarbeit, 2021 mehr… BibTeX
  • Jonas Fill: Development of the Bayesian Recurrent Neural Network Architectures for Hydrological Time Series Forecasting. Bachelorarbeit, 2021 mehr… BibTeX Volltext (mediaTUM)
  • Simon Zocholl: Development of Recurrent Neural Network Architectures for Hydrological Time Series Forecasting. Bachelorarbeit, 2021 mehr… BibTeX Volltext (mediaTUM)


  • Jonas Treplin: Parallel Evaluation of Adaptive Sparse Grids with Application to Uncertainty Quantification of Hydrology Simulations. Projektarbeit, 2020 mehr… BibTeX Volltext (mediaTUM)
  • Mathieu Putz: Developing a prototype of Bayesian Inference framework to recalibrate the complex hydrological model LARSIM. Studienarbeit, 2020 mehr… BibTeX Volltext (mediaTUM)


  • Frank Schraufstetter: Development of a Prototype to Quantify the Uncertainty of the Water Balance Model LARSIM. Bachelorarbeit, 2019 mehr… BibTeX Volltext (mediaTUM)
  • Vyshakh Unnikrishnan: Implementation of a deep learning based model for rainfall-runoff modelling. Masterarbeit, 2019 mehr… BibTeX


Other Supervised Student Projects

  • Leon Fiedler: "Sensitivity Analysis of a Deep Learning Model for Discharge Prediction in the Regen Catchment". Masterarbeit, Ingenieurfakultät Bau Geo Umwelt; 2020 [BibTeX] [Volltext (mediaTUM)],


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.…


Summer semester 2024

  • Algorithms for Uncertainty Quantification

Winter semester 2023

Summer semester 2022

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




  • Ivana Jovanovic Buha: SCCS Lehrstuhl Treffen. (Vortrag) 2023 mehr…



  • 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 mehr…


  • 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. mehr…

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)