I. - Basic information

I.1 - Surname

Kossaczká

I.2 - Name

Tatiana

I.3 - Degrees

Dr.rer.nat., M.Sc., Bc.

I.4 - Year of birth

1993

I.5 - Name of the workplace

Comenius University in Bratislava, Faculty of Mathematics, Physics and Informatics, Department of Applied Mathematics and Statistics

I.6 - Address of the workplace

Mlynská dolina F1 842 48 Bratislava

I.7 - Position

university lecturer / research assistent

I.8 - E-mail address

tatiana.kossaczka@fmph.uniba.sk

I.9 - Hyperlink to the entry of a person in the Register of university staff

https://www.portalvs.sk/regzam/detail/69910?do=filterForm-submit&surname=kossaczk%C3%A1&employment_state=yes&filter=Vyh%C4%BEada%C5%A5

I.10 - Name of the study field in which a person works at the university

Mathematics

I.11 - ORCID iD

0000-0001-9910-1087

II. - Higher education and further qualification growth

II.1 - First degree of higher education

II.a - Name of the university or institution

Comenius University in Bratislava, Faculty of Mathematics, Physics and Informatics

II.b - Year

2016

II.c - Study field and programme

Mathematics of ecnonomy and finance

II.2 - Second degree of higher education

II.a - Name of the university or institution

University of Wuppertal, School of Mathematics and Natural Science

II.b - Year

2019

II.c - Study field and programme

Mathematics

II.3 - Third degree of higher education

II.a - Name of the university or institution

University of Wuppertal, School of Mathematics and Natural Science

II.b - Year

2024

II.c - Study field and programme

Mathematics

II.4 - Associate professor

II.5 - Professor

II.6 - Doctor of Science (DrSc.)

III. - Current and previous employment

III.a - Occupation-position	III.b - Institution	III.c - Duration
special assistent	University of Wuppertal, School of Mathematics and Natural Science	2017-2018
research assistent	University of Wuppertal, School of Mathematics and Natural Science	2020-2024

IV. - Development of pedagogical, professional, language, digital and other skills

IV.a - Activity description, course name, other	IV.b - Name of the institution	IV.c - Year
Introduction to numerical mathematics	University of Wuppertal, School of Mathematics and Natural Science	2018
Numerical methods for solving ordinary differential equations	University of Wuppertal, School of Mathematics and Natural Science	2020
Advanced mathematics	University of Wuppertal, School of Mathematics and Natural Science	2023
Programming seminar: Introduction to numerical mathematics	University of Wuppertal, School of Mathematics and Natural Science	2024

V. - Overview of activities within the teaching career at the university

V.1 - Overview of the profile courses taught in the current academic year according to study programmes

V.1.a - Name of the profile course	V.1.b - Study programme	V.1.c - Degree	V.1.d - Field of study
Probability and Statistics for Informaticians	Applied informatics	I.	Inofrmatics
Numerical Modelling	Mathematics of economy, finance and modeling	II.	Mathematics

V.2 - Overview of the responsibility for the delivery, development and quality assurance of the study programme or its part at the university in the current academic year

V.3 - Overview of the responsibility for the development and quality of the field of habilitation procedure and inaugural procedure in the current academic year

V.4 - Overview of supervised final theses

V.4.1 - Number of currently supervised theses

V.4.a - Bachelor's (first degree)

V.4.2 - Number of defended theses

V.5 - Overview of other courses taught in the current academic year according to study programmes

V.5.a - Name of the course	V.5.b - Study programme	V.5.c - Degree	V.5.d - Field of study
Financial Derivatives	Mathematics of economy, finance and modeling	II.	Mathematics

VI. - Overview of the research/artistic/other outputs

VI.1 - Overview of the research/artistic/other outputs and the corresponding citations

VI.1.1 - Number of the research/artistic/other outputs

VI.1.a - Overall

VI.1.b - Over the last six years

VI.1.2 - Number of the research/artistic/other outputs registered in the Web of Science or Scopus databases

VI.1.a - Overall

VI.1.b - Over the last six years

VI.1.3 - Number of citations corresponding to the research/artistic/other outputs

VI.1.a - Overall

VI.1.b - Over the last six years

VI.1.4 - Number of citations registered in the Web of Science or Scopus databases

VI.1.a - Overall

VI.1.b - Over the last six years

VI.1.5 - Number of invited lectures at the international, national level

VI.2 - The most significant research/artistic/other outputs

Kossaczká, T., Ehrhardt, M., & Günther, M.: Enhanced fifth order WENO shock-capturing schemes with deep learning. Results in Applied Mathematics, 12, 100201. 2021.

Kossaczká, T., Ehrhardt, M., & Günther, M.: A neural network enhanced weighted essentially non-oscillatory method for nonlinear degenerate parabolic equations. Physics of Fluids, 34(2), 026604. 2022.

Kossaczká, T., Ehrhardt, M., & Günther, M.: A deep smoothness WENO method with applications in option pricing. European Consortium for Mathematics in Industry. Springer International Publishing, 417-423. 2022.

Kossaczká, T., Ehrhardt, M., & Günther, M.: Deep FDM: Enhanced finite difference methods by deep learning. Franklin Open, 4, 100039. 2023.

Kossaczká, T., Jagtap, A.D. & Ehrhardt, M.: Deep smoothness weighted essentially non-oscillatory method for two-dimensional hyperbolic conservation laws: A deep learning approach for learning smoothness indicators. Physics of Fluids, 36(3), 036603. 2024.

VI.3 - The most significant research/artistic/other outputs over the last six years

Kossaczká, T., Ehrhardt, M., & Günther, M.: Enhanced fifth order WENO shock-capturing schemes with deep learning. Results in Applied Mathematics, 12, 100201. 2021.

Kossaczká, T., Ehrhardt, M., & Günther, M.: Deep FDM: Enhanced finite difference methods by deep learning. Franklin Open, 4, 100039. 2023.

VI.4 - The most significant citations corresponding to the research/artistic/other outputs

Zeifang, J. and Beck, A., 2021. A data-driven high order sub-cell artificial viscosity for the discontinuous Galerkin spectral element method. Journal of Computational Physics, 441, p.110475.

Ning, J., Su, X. and Xu, X., 2022. Improved fifth-order weighted essentially non-oscillatory scheme with low dissipation and high resolution for compressible flows. Physics of Fluids, 34(5).

Zhang, X., Huang, L., Jiang, Z. and Yan, C., 2022. A class of high-order improved fast weighted essentially non-oscillatory schemes for achieving optimal order at any critical points. Physics of Fluids, 34(12).

Wang, Z., Zhu, J., Wang, C. and Zhao, N., 2022. Finite difference alternative unequal-sized weighted essentially non-oscillatory schemes for hyperbolic conservation laws. Physics of Fluids, 34(11).

Drozda, L., Mohanamuraly, P., Cheng, L., Lapeyre, C., Daviller, G., Realpe, Y., Adler, A., Staffelbach, G. and Poinsot, T., 2023. Learning an optimised stable Taylor-Galerkin convection scheme based on a local spectral model for the numerical error dynamics. Journal of Computational Physics, 493, p.112430.

VI.5 - Participation in conducting (leading) the most important research projects or art projects over the last six years

DAAD-MŠ ENANEFA – Efficient Numerical Approximation of Nonlinear Equations in Financial Applications

VII. - Overview of organizational experience related to higher education and research/artistic/other activities

VIII. - Overview of international mobilities and visits oriented on education and research/artistic/other activities in the given field of study

IX. - Other relevant facts

Date of last update

2025-01-24

Name and surname:	Dr. rer. nat. Tatiana Kossaczká, MSc.
Document type:	Research/art/teacher profile of a person
The name of the university:	Comenius University Bratislava
The seat of the university:	Šafárikovo námestie 6, 818 06 Bratislava