Ivana Jovanovic, M.Sc. (hons): Difference between revisions
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== Background == | |||
* Doctoral candidate, [http://www.gs.tum.de/en/tum-graduate-school/ TUM Graduate School] - [https://www.cedosia.gs.tum.de/ CeDoSIA] | |||
* Scientific employee at TUM SCCS since June 2018 | |||
* M.Sc. with Honours in [http://www.cse.tum.de/ Computational Science and Engineering], Technical University of Munich, 2018 | |||
* Diploma in Electrical Engineering, [https://www.etf.bg.ac.rs/en University of Belgrade], 2014 | |||
== Research Interests == | == Research Interests == | ||
My research focus is on applied and computational mathematics, in particular on modelling and system identification, uncertainty quantification, inverse problems and and data-driven model learning. The main applications driving my research are from hydrology. | |||
== Student Projects == | == Student Projects == | ||
If you are interested in a student project (Bachelor's or Master's Thesis or anything else), please contact me directly. | |||
=== Running student projects === | |||
* '''Vyshakh Unnikrishnan''' is doing his Master's Thesis for M.Sc. CSE. A preliminary title of his thesis is "Implementation of a deep learning based model for rainfall-runoff modelling". | |||
* '''Frank Schraufstetter''' is working on his Bachelor's Thesis with a preliminary title: "Quantify the uncertainty of the water balance model LARSIM using chaospy". | |||
== Teaching == | == Teaching == | ||
=== Summer semester 2020 === | |||
* [https://www.moodle.tum.de/course/view.php?id=53108 Seminar Data Mining (IN0014, IN4927)] | |||
* [https://www.moodle.tum.de/course/view.php?id=53243 Seminar High Dimensional Methods in Scientific Computing (IN2107, IN0014, IN218306)] | |||
=== Winter semester 2019/20 === | |||
* [https://campus.tum.de/tumonline/wbLv.wbShowLVDetail?pStpSpNr=950371836 Scientific Computing 1 (IN2005)] tutorial ([https://www.moodle.tum.de/course/view.php?id=49339 Moodle]) | |||
* [https://www.moodle.tum.de/course/view.php?id=49367 Seminar Computational Aspects of Machine Learning (IN2107,IN0014, IN2183)] | |||
=== Summer semester 2018/19 === | === Summer semester 2018/19 === | ||
* Seminar Data Mining | * [https://www.moodle.tum.de/course/view.php?id=45858 Seminar Data Mining] | ||
=== Winter semester 2018/19 === | === Winter semester 2018/19 === | ||
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* [https://campus.tum.de/tumonline/wbLv.wbShowLVDetail?pStpSpNr=950371836 Scientific Computing 1] tutorial ([https://www.moodle.tum.de/course/view.php?id=41997 Moodle]) | * [https://campus.tum.de/tumonline/wbLv.wbShowLVDetail?pStpSpNr=950371836 Scientific Computing 1] tutorial ([https://www.moodle.tum.de/course/view.php?id=41997 Moodle]) | ||
* Assisting in the seminar [https://campus.tum.de/tumonline/wbLv.wbShowLVDetail?pStpSpNr=950373512&pSpracheNr=2 Next Generation High-Performance Computing]. | * Assisting in the seminar [https://campus.tum.de/tumonline/wbLv.wbShowLVDetail?pStpSpNr=950373512&pSpracheNr=2 Next Generation High-Performance Computing]. | ||
=== Winter semester 2016/17 === | === Winter semester 2016/17 === | ||
Latest revision as of 21:27, 29 September 2020
Address:
- TU München
- Institut für Informatik
- Boltzmannstr. 3
- 85748 Garching b. München
- Office:
- MI 02.05.040
- Email:
- Phone:
- (089) 289 18 613
- Fax:
- (089) 289 18 607
- Office Hours:
- by arrangement
Background
- Doctoral candidate, TUM Graduate School - CeDoSIA
- Scientific employee at TUM SCCS since June 2018
- M.Sc. with Honours in Computational Science and Engineering, Technical University of Munich, 2018
- Diploma in Electrical Engineering, University of Belgrade, 2014
Research Interests
My research focus is on applied and computational mathematics, in particular on modelling and system identification, uncertainty quantification, inverse problems and and data-driven model learning. The main applications driving my research are from hydrology.
Student Projects
If you are interested in a student project (Bachelor's or Master's Thesis or anything else), please contact me directly.
Running student projects
- Vyshakh Unnikrishnan is doing his Master's Thesis for M.Sc. CSE. A preliminary title of his thesis is "Implementation of a deep learning based model for rainfall-runoff modelling".
- Frank Schraufstetter is working on his Bachelor's Thesis with a preliminary title: "Quantify the uncertainty of the water balance model LARSIM using chaospy".
Teaching
Summer semester 2020
- Seminar Data Mining (IN0014, IN4927)
- Seminar High Dimensional Methods in Scientific Computing (IN2107, IN0014, IN218306)
Winter semester 2019/20
- Scientific Computing 1 (IN2005) tutorial (Moodle)
- Seminar Computational Aspects of Machine Learning (IN2107,IN0014, IN2183)
Summer semester 2018/19
Winter semester 2018/19
- Scientific Computing 1 tutorial (Moodle)
- Assisting in the seminar Next Generation High-Performance Computing.
Winter semester 2016/17
- Assisting in the Scientific Computing 1 tutorial.