Dr. Alex Bihlo

Department of Mathematics and Statistics

Department of Computer Science (cross-appointed)

Memorial University of Newfoundland

Room HH-2008

St. John’s, NL, Canada A1C 5S7

1 709 864 8078

abihlo (at) mun [dot) ca

Research

My research interests mainly lie in the study of geometric properties of differential equations (in particular, symmetries and conservation laws) and the construction of efficient numerical schemes preserving these properties, but I have a growing interest in machine learning as well. Concerning applications, I am primarily interested in the models of (geophysical) fluid mechanics.

Below you will find a list of my papers and some recent preprints. They are ordered by 'research field' although several papers would easily fit into more than one category.

Machine learning

  • R. Brecht, L. Bakels, A. Bihlo and A. Stohl, 2022. Improving trajectory calculations using deep learning inspired single image superresolution, arXiv:2206.04015.
  • R. Brecht and A. Bihlo, 2022. Computing the ensemble spread from deterministic weather predictions using conditional generative adversarial networks, arXiv:2205.09182.
  • A. Bihlo and R.O. Popovych, 2022. Physics-informed neural networks for the shallow-water equations on the sphere. J. Comput. Phys. 456 111024, arXiv:2104.00615 .
  • A. Bihlo, 2020. A generative adversarial network approach to (ensemble) weather prediction. Neural Netw. 139 1–16, arXiv:2006.07718.
  • A. Bihlo, 2019. Precipitation nowcasting using a stochastic variational frame predictor with learned prior distribution, arXiv:1905.05037.

Group analysis of differential equations

  • O. Vaneeva, A. Bihlo and R.O. Popovych, 2020. Equivalence groupoid and group classification of a class of nonlinear wave and elliptic equations. Commun. Nonlinear Sci. Numer. Simul. 91, 105419 (28 pp), arXiv:2002.08939.
  • A. Bihlo, N. Poltavets and R.O. Popovych, 2020. Lie symmetries of two-dimensional shallow water equations with variable bottom topography. Chaos 30 073132 (17 pp), arXiv:1911.02097.
  • A. Bihlo and R.O. Popovych, 2020. Zeroth-order conservation laws of two-dimensional shallow water equations with variable bottom topography. In press Stud. Appl. Math., arXiv:1912.11468.
  • S. Opanasenko, A. Bihlo and R.O. Popovych, 2020. Equivalence groupoid and group classification of a class of variable-coefficient Burgers equations. J. Math. Anal. Appl. 490, 124215 (22 pp), arXiv:1910.13500.
  • S. Opanasenko, A. Bihlo, R.O. Popovych and A. Sergyeyev, 2020. Generalized symmetries, conservation laws and Hamiltonian structures of an isothermal no-slip drift flux model. Phys. D 411, 132546 (19 pp), arXiv:1908.00034.
  • S. Opanasenko, A. Bihlo, R.O. Popovych and A. Sergyeyev, 2020. Extended symmetry analysis of isothermal no-slip drift flux model. Phys. D 402, 132188 (16 pp), arXiv:1705.09277.
  • R.O. Popovych and A. Bihlo, 2020. Inverse problem on conservation laws. Phys. D 401, 132175 (16 pp), arXiv:1705.03547.
  • E.M. Dos Santos Cardoso-Bihlo, A. Bihlo and R.O. Popovych, 2019. Differential invariants for a class of diffusion equations. In Collection of Works of Institute of Mathematics, Kyiv 16 (1), 50–65, arXiv:1909.00477.
  • S. Opanasenko, A. Bihlo and R.O. Popovych, 2017. Group analysis of general Burgers–Korteweg–de Vries equations. J. Math. Phys. 58 (8), 081511 (37 pp), arXiv:1703.06932.
  • A. Bihlo and R.O. Popovych, 2017. Group classification of linear evolution equations. J. Math. Anal. Appl. 448, 982–1005, arXiv:1605.09251.
  • A. Bihlo, E.M. Dos Santos Cardoso-Bihlo and R.O. Popovych, 2015. Algebraic method for finding equivalence groups. J. Phys.: Conf. Ser. 621, 012001 (17 pp), arXiv:1503.06487.
  • S. Szatmari and A. Bihlo, 2014. Symmetry analysis of a system of modified shallow-water equations. Commun. Nonlinear Sci. Numer. Simul. 19 (3), 530–537, arXiv:1212.5823.
  • A. Bihlo and G. Bluman, 2013. Conservative parameterization schemes. J. Math. Phys. 54, 083101 (24 pp), arXiv:1209.4279.
  • A. Bihlo, E.M. Dos Santos Cardoso-Bihlo and R.O. Popovych, 2012. Complete group classification of a class of nonlinear wave equations. J. Math. Phys. 53 (12), 123515, 32 pp, arXiv:1106.4801.
  • R.O. Popovych and A. Bihlo, 2012. Symmetry preserving parameterization schemes. J. Math. Phys. 53 (7), 073102 (36 pp), arXiv:1010.3010.
  • A. Bihlo and R.O. Popovych, 2012. Lie reduction and exact solutions of the vorticity equation on the rotating sphere. Phys. Lett. A 376 (14), 1179–1184, arXiv:1112.3019.
  • A. Bihlo and R.O. Popovych, 2011. Lie symmetry analysis and exact solutions of the quasi-geostrophic two-layer problem. J. Math. Phys. 52 (3), 033103, 24 pp, arXiv:1010.1542.
  • E.M. Dos Santos Cardoso-Bihlo, A. Bihlo and R.O. Popovych, 2011. Enhanced preliminary group classification of a class of generalized diffusion equations. Commun. Nonlinear Sci. Numer. Simul. 16 (9), 3622–3638, arXiv:1012.0297.
  • A. Bihlo and R.O. Popovych, 2011. Point symmetry group of the barotropic vorticity equation. In Proceedings of the 5th workshop “Group Analysis of Differential Equations & Integrable Systems”, 15–27, arXiv:1009.1523.
  • A. Bihlo and R.O. Popovych, 2009. Lie symmetries and exact solutions of the barotropic vorticity equation. J. Math. Phys. 50 (12), 123102, 12 pp, arXiv:0902.4099
  • A. Bihlo and R.O. Popovych, 2009. Symmetry analysis of barotropic potential vorticity equation. Commun. Theor. Phys. 52 (4), 697–700, arXiv:0811.3008.
  • A. Bihlo, 2009. Symmetries in atmospheric sciences. In Proceedings of the 4th workshop “Group Analysis of Differential Equations & Integrable Systems”, 6–12, arXiv:0902.4112.

Geometric numerical integration

  • H. Jahandari and A. Bihlo, 2021. Forward modelling of geophysical electromagnetic data on unstructured grids using an adaptive mimetic finite-difference method. Computat. Geosci. 25, 1083–1104.
  • H. Jahandari, A. Bihlo and F. Donzelli, 2021. Forward modelling of gravity data on unstructured grids using an adaptive mimetic finite-difference method. J. Appl. Geophy. 190 104340 (21 pages).
  • A. Bihlo, J. Jackaman and F. Valiquette, 2020. On the development of symmetry-preserving finite element schemes for ordinary differential equations. J. Comput. Dyn. 7(2), 339–368. arXiv:1907.00961.
  • R. Brecht, W. Bauer, A. Bihlo, F. Gay-Balmaz, S. MacLachlan, 2019. Variational integrator for the rotating shallow-water equations on the sphere. Q. J. Royal Meteorol. Soc., 145, 1070–1088, arXiv:1808.10507.
  • A. Bihlo and F. Valiquette, 2019. Symmetry-preserving finite element schemes: An introductory investigation. SIAM J. Sci. Comput. 41(5), A3300–A3325, arXiv:1803.10058.
  • A. Wan, A. Bihlo and J.-C. Nave, 2017. Conservative methods for dynamical systems. SIAM J. Numer. Anal. 55 (5), 2255–2285, arXiv:1612.02417.
  • A. Bihlo and F. Valiquette, 2017. Symmetry-preserving numerical schemes. In Symmetries and Integrability of Difference Equations, 261–324, Springer, arXiv:1608.02557.
  • A. Wan, A. Bihlo and J.-C. Nave, 2016. The multiplier method to construct conservative finite difference schemes for ordinary and partial differential equations. SIAM J. Numer. Anal. 54 (1), 86–119, arXiv:1411.7720.
  • A. Bihlo, X. Coiteux-Roy and P. Winternitz, 2015. The Korteweg-de Vries equation and its symmetry-preserving discretization. J. Phys. A 48, 055201 (25 pp), arXiv:1409.4340.
  • A. Bihlo and J.-C. Nave, 2014. Convecting reference frames and invariant numerical models. J. Comput. Phys. 271, 656–663, arXiv:1301.5955.
  • A. Bihlo and J.-C. Nave, 2013. Invariant discretization schemes using evolution-projection techniques. SIGMA 9, 052, 23 pp, arXiv:1209.5028.
  • A. Bihlo, 2013. Invariant meshless discretization schemes. J. Phys. A: Math. Theor. 46 (6), 062001 (12 pp), arXiv:1210.2762.
  • A. Bihlo and R.O. Popovych, 2012. Invariant discretization schemes for the shallow-water equations. SIAM J. Sci. Comput. 34 (6), B810-B839, arXiv:1201.0498.

Geophysical fluid dynamics

  • A. Bihlo, E.M. Dos Santos Cardoso-Bihlo and R.O. Popovych, 2019. Invariant parameterization of geostrophic eddies in the ocean. arXiv:1908.06345.
  • B. Khouider and A. Bihlo, 2019. A new stochastic model for the regimes of stratocumulus phase transition: open cells, closed cells, and convective rolls. J. Geophys. Res. Atmos. 124 (1), 367–386.
  • R. Brecht, A. Bihlo, S. MacLachlan and J. Behrens, 2018. A well-balanced meshless tsunami propagation and inundation model. Adv. Water Resour. 115, 273–285, arXiv:1705.09831.
  • A. Bihlo and S. MacLachlan, 2018. Well-balanced mesh-based and meshless schemes for the shallow-water equations. BIT Numer. Math. 58 (3), 579–598, arXiv:1702.07749.
  • A. Bihlo., E.M. Dos Santos Cardoso-Bihlo and R.O. Popovych, 2015. Invariant and conservative parameterization schemes, in volume 2 of Parameterization of Atmospheric Convection, (R. S. Plant and J. I. Yano, Eds.), Imperial College Press, 483-524.
  • A. Bihlo, E.M. Dos Santos Cardoso-Bihlo and R.O. Popovych, 2014. Invariant parameterization and turbulence modeling on the beta-plane. Phys. D 269, 48–62, arXiv:1112.1917.
  • A. Bihlo and J. Staufer, 2011. Minimal atmospheric finite-mode models preserving symmetry and generalized Hamiltonian structures. Phys. D 240 (7), 599–606, arXiv:0909.1957.
  • A. Bihlo and R.O. Popovych, 2009. Symmetry justification of Lorenz’ maximum simplification. Nonlin. Dyn. 61 (1), 101–107, arXiv:0805.4061.
  • A. Bihlo, 2008. Rayleigh-Bénard Convection as a Nambu–metriplectic problem. J. Phys. A 41 (29), 292001 (6 pp), arXiv:0803.4458.

Domain decomposition

  • F. Donzelli, A. Bihlo, M. Kischinhevsky, C.G. Farquharson, 2019. Massively parallel stochastic solution of the geophysical gravity problem. arXiv:1709.07469.
  • A. Bihlo, C.G. Farquharson, R.D. Haynes, J.C. Loredo-Osti, 2017. Stochastic domain decomposition for the solution of the two-dimensional magnetotelluric problem. Computat. Geosci. 21 (1), 117–129, arXiv:1603.09311.
  • A. Bihlo and R.D. Haynes, 2016. A stochastic domain decomposition method for time dependent mesh generation. LNCSE, 107–115, arxiv:1402.0266.
  • A. Bihlo, R.D. Haynes and E.J. Walsh, 2015. Stochastic domain decomposition for time dependent adaptive mesh generation. J. Math. Study 48 (2), 106–124, arXiv:1504.00084.
  • A. Bihlo and R.D. Haynes, 2014. Parallel stochastic methods for PDE based grid generation. Comput. Math. Appl. 68 (8), 804–820, arxiv:1310.3435.

Theses

  • A. Bihlo, 2019. Geometric modeling in geophysical fluid dynamics. Habilitation thesis, University of Vienna, 177 pp.
  • A. Bihlo, 2010. Symmetry methods in the atmospheric sciences. PhD thesis, University of Vienna, 165 pp. (Supervisors: Professor Dr. Michael Hantel, Professor Dr. Roman O. Popovych) (download)
  • A. Bihlo, 2007. Solving the vorticity equation with Lie groups. Master thesis, In Wiener Meteorologische Schriften, Vol. 6, facultas.wuv, Wien. (Supervisor: Professor Dr. Michael Hantel)

Talks

If you are interested in getting the slides of any of the talks listed below, just send me an email!

Invited talks

  • A multi-model physics-informed neural network approach for solving the shallow-water equations on the sphere (2022 CMS Summer Meeting, St. John's, June 2022)
  • Deep neural networks for solving differential equations on general orientable surfaces (CRM Applied Math Seminar, Montreal, Jan 2022)
  • Invariant parameterization schemes for turbulence modeling (Symmetry and Integrability of Equations of Mathematical Physics, Kiev, Dec 2021)
  • A multi-model approach to physics-informed neural networks for the shallow-watere equations on the sphere (2021 CMS Winter meeting, Vancouver, 2021)
  • Deep learning in dynamic meteorology (University of Vienna, Nov 2021)
  • Physics-informed neural networks for the shallow-water equations on the sphere (CAIMS 2021, Waterloo, June 2021)
  • Invariant numerical modeling for dynamic meteorology (National Academy of Sciences of Ukraine, Kiev, Feb 2021)
  • An introduction to geometric numerical integration (National Academy of Sciences of Ukraine, Kiev, Jan 2021)
  • Deep learning in the atmospheric sciences (McMaster University, Jan 2021)
  • A gentle introduction to deep learning and AI safety (University of Ottawa, Oct 2020)
  • A conditional variational autoencoder for precipitation nowcasting (CAIMS 2019, Whistler, June 2019)
  • Invariant parameterization in geophysical fluid dynamics (University of St Andrews, Oct 2018)
  • Geometry-preserving numerical modeling in geophysical fluid dynamics (CAIMS 2018, Toronto, June 2018)
  • A meshless tsunami propagation and inundation model (CAIMS 2018, Toronto, June 2018)
  • Symmetry-preserving discretization schemes (ASIDE, Montreal, June 2016)
  • Conservative discretization schemes (University of Vienna, May 2016)
  • Novel methods for geometric numerical integration (University of Saskatchewan, May 2015)
  • Geometry-preserving numerical modeling (Memorial University of Newfoundland, Oct 2014)
  • Conservative parameterization schemes (University of Vienna, Feb 2013)
  • Invariant discretization schemes (University of Vienna, Feb 2013)
  • Geometry-preserving modeling in meteorology (University of Reading, Feb 2013)
  • Invariant subgrid-scale closure schemes for turbulence modeling (2012 CMS Winter Meeting, Montréal, Dec 2012)
  • Invariant discretization schemes (2012 CMS Winter Meeting, Montréal, Dec 2012)
  • Invariant parameterization schemes and turbulence modeling (University of British Columbia, June 2012)
  • Invariant turbulence modeling, (Center for Turbulence Research, Stanford University, June 2012)
  • A tutorial on Hamiltonian mechanics (COST working group meeting, University of Munich, May 2011)
  • A method for constructing exact solutions of partial differential equations (University of Lisbon, Sept 2010)
  • Symmetry methods in dynamics meteorology (University of Frankfurt, Jan 2009)
  • Symmetrien und einige Anwendungen in der dynamischen Meteorologie (University of Bonn, July 2008)

Other presentations

  • Solving the shallow-water equations with neural networks (PDEs on the Sphere, May 2021)
  • Geometry-preserving numerical modeling in geophysical fluid dynamics (Habilitation research talk, University of Vienna, May 2020)
  • An introduction to geometric numerical integration (Habilitation teaching talk, University of Vienna, April 2020)
  • An introduction to deep learning and artificial intelligence (Memorial University of Newfoundland, Nov 2019)
  • Exactly conservative discretization schemes (Fields Institute, Sept 2019)
  • Machine learning and artificial intelligence - how to use math to make computers smarter (and avoid getting extinct in the process) (38th Blundon Seminar, Memorial University of Newfoundland, May 2019)
  • Exactly conservative discretization schemes for dynamical systems (Memorial University of Newfoundland, April 2018)
  • Invariant discretization beyond finite differences (Memorial University of Newfoundland, March 2018)
  • A well-balanced meshless tsunami propagation and inundation model (University of British Columbia, Jan 2018)
  • Well-balanced mimetic mesh-based and meshless schemes for the shallow-water equations with bottom topography (2016 CMS Winter Meeting, Niagara Falls, Dec 2016)
  • Recent advancements in geometric numerical integration (University of British Columbia, Mar 2015)
  • Stochastic domain decomposition for parallel grid generation (University of British Columbia, Mar 2015)
  • Invariant and conservative numerical schemes: Theory and applications (University of British Columbia, Feb 2015)
  • Invariant discretization schemes (XXIInd International Conference on Integrable Systems and Quantum symmetries, Prague, Czech Republic, June 2014)
  • Grid generation using stochastic domain decomposition (University of Vienna, June 2014)
  • Parallel stochastic domain decomposition for PDE based grid adaptation (McGill University, Nov 2013)
  • Invariant discretization schemes (CAIMS 2013, Quebec City, Canada, June 2013)
  • Complete group classification of a class of nonlinear wave equations (2012 CMS Winter Meeting, Montréal, Dec 2012)
  • Invariant discretization of partial differential equations (McGill University, Nov 2012)
  • Invariant turbulence modeling (Conference "Symmetries of Differential Equations: Frames, Invariants and Applications", University of Minnesota, May 2012)
  • Invariant parameterization schemes (Conference "Symmetries of Differential Equations: Frames, Invariants and Applications", University of Minnesota, May 2012)
  • Invariant numerical schemes for the shallow-water equations (Centre de recherches mathématiques, Sept 2011)
  • Symmetry methods in the atmospheric sciences (University of Vienna, Dec 2010)
  • Symmetry preserving parameterization schemes (Fifth International Workshop on Group Analysis of Differential Equations and Integrable systems, Protaras, Cyprus, June 2010)
  • Symmetry preserving discretization schemes (EGU General Assembly, Vienna, May 2010)
  • Minimal atmospheric finite-mode models preserving symmetry and generalized Hamiltonian structures (University of Vienna, Dec 2009)
  • Der Nambu Kalkül in der dynamischen Meteorologie (3rd Austrian Meteorology Day, Graz, Nov 2009)
  • Symmetrien, Erhaltungssätze und Low-order Modelle in der dynamischen Meteorologie (University of Vienna, May 2009)
  • Symmetry methods in dynamics meteorology (EGU General Assembly, Vienna, April 2009)
  • Symmetry methods in dynamics meteorology (ACA 2008 conference, Hagenberg, Austria, July 2008)
  • Application of finite and infinite dimensional Nambu mechanics in dynamic meteorology (EGU General Assembly, Vienna, July 2008)
  • Nambu Mechanik. Vom Kreisel zum Chaos (FU Berlin, Dec 2007)
  • Can Lie groups improve weather forecasts? (University of Vienna, Dec 2006)

Conferences

  • PDEs on the Sphere, Deutscher Wetterdienst, Germany (17–21 May 2021)
  • Workshop on Variational Discretization for Geophysical Fluid Dynamics, Fields Institute, Toronto, ON, Canada (9–13 Sept 2019)
  • CAIMS 2019, Annual Meeting of the Canadian Applied and Industrial Mathematics Society, Whistler, BC, Canada (9–13 June 2019)
  • CAIMS 2018, Annual Meeting of the Canadian Applied and Industrial Mathematics Society, Toronto, ON, Canada (4–7 June 2018)
  • CAIMS 2017, Annual Meeting of the Canadian Applied and Industrial Mathematics Society, Halifax, NS, Canada (17–21 July 2017)
  • Connections in Geometric Numerical Integration and Structure-Preserving Discretization, Banff International Research Station, Banff, AB, Canada (11–16 June 2017)
  • SIDE 12 - Symmetries and Integrability of Difference Equations, Sainte-Adèle, QC, Canada (3–9 July 2016)
  • ASIDE - Abecedarian of SIDE, Montréal, QC, Canada (27 June–1 July 2016)
  • Recent Developments in Adaptive Methods for PDEs, Collaborative Workshop and Short Course, St. John's, NL, Canada (17–22 Aug 2014)
  • XXIInd International Conference on Integrable Systems and Quantum symmetries (ISQS-22), Prague, Czech Republic (26–27 June 2014)
  • CAIMS 2013, Annual Meeting of the Canadian Applied and Industrial Mathematics Society, Quebec City, QC, Canada (16–20 June 2013)
  • Canadian Mathematical Society Winter Meeting, Montréal, QC, Canada (7 Dec–10 Dec 2012)
  • Symmetries of Differential Equations: Frames, Invariants and Applications, Minneapolis, USA (17–20 May 2012)
  • Workshop Balance, Boundaries and Mixing in the Climate Problem, Université de Montréal, Montréal, QC, Canada (28–30 Sept 2011)
  • Workshop of COST-Action ES0905 Basic concepts for convection parameterization in weather forecast and climate model, Cambridge, UK (22–25 March 2011)
  • Fifth International Workshop Group Analysis of Differential Equations and Integrable Systems, Protaras, Cyprus (6–10 June 2010)
  • European Geosciences Union – General Assembly, Vienna (5 May 2010)
  • Third Austrian Meteorology Day, Graz (6 Nov 2009)
  • Kickoff-Workshop Nambu Calculus, Vienna (15–19 June 2009)
  • European Geosciences Union – General Assembly, Vienna (23 April 2009)
  • Application of Computer Algebra (ACA) – RISC Summer 2008, Hagenberg, Austria (27–28 July 2008)
  • European Geosciences Union – General Assembly, Vienna (17 April 2008)

Short-term scientific visits

  • Department of Mathematics, University of British Columbia, Vancouver, BC, Canada (22 Jan–26 Jan 2018)
  • Department of Mathematics and Statistics, McGill University, Montréal, QC, Canada (15 Aug–19 Aug 2017)
  • Department of Mathematics, Imperial College London, London, UK (5 July–8 July 2017)
  • Faculty of Mathematics, University of Vienna, Vienna, Austria (10 April–10 May 2017)
  • Department of Mathematics and Statistics, University of Victoria, Victoria, BC, Canada (16 Aug–26 Aug 2016)
  • Institute of Meteorology and Geophysics, University of Vienna, Vienna, Austria (10 May–4 June 2016)
  • Faculty of Mathematics, University of Vienna, Vienna, Austria (10 May–4 June 2016)
  • Department of Mathematics and Statistics, University of Saskatchewan, Saskatoon, SK, Canada (3–8 May 2015)
  • Centre de recherches mathématiques, Université de Montréal, Montréal, QC, Canada (19–26 July 2014)
  • Department of Mathematics, University of British Columbia, Vancouver, BC, Canada (3–31 Aug 2013)
  • Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John’s, NL, Canada (24 May–14 June 2013)
  • Department of Mathematics, University of British Columbia, Vancouver, BC, Canada (21 May–14 June 2012)
  • Centro de Matematica e Aplicacoes, Instituto Superior Tecnico, Lisbon, Portugal (Sep 2010)
  • Department of Meteorology, FU Berlin, Berlin, Germany (10–14 Dec 2007)

Teaching

Memorial University

  • CMSC 6920 Applied Scientific Programming (Winter 2017, Winter 2018, Winter 2019, Winter 2020, Winter 2021)
  • DSCI 5003 An introduction to Python and R (Summer 2022)
  • MATH 2051 Linear algebra II (Fall 2019)
  • MATH 2130 Technical writing (Fall 2020, Fall 2021)
  • MATH 3132 Numerical analysis I (Fall 2016, Fall 2018, Fall 2019)
  • MATH 3202 Vector calculus (Fall 2017)
  • MATH 6201 Numerical methods for time-dependent differential equations (Winter 2016, Winter 2017)
  • MATH 6205 Deep learning and deep reinforcement learning (Winter 2021)
  • MATH 6210 Numerical methods for differential equations (Fall 2018)
  • MATH 6261 Geometric numerical integration (Fall 2017)

McGill University

  • MATH 262 Intermediate calculus (Fall 2013)

University of Vienna

  • Geophysical fluid dynamics (Summer 2008, Summer 2016)
  • Lectures on selected topics of dynamical meteorology (Summer 2011)
  • Fluid dynamics (Summer 2009)
  • Numerical and mathematical methods in meteorology (Winter 2007, Winter 2009)

The Team

I am part of Memorial University's Centre for Numerical Analysis and Scientific Computing as well as the Data Science Research Group. Please note that I am currently not accepting any new graduate students.

Postdocs

  • Dmytro Popovych (PhD Kiev; 2022–)
  • Stanislav Opanasenko (PhD Memorial; 2021)
  • James Jackaman (PhD Reading; 2019–2021)
  • Hormoz Jahandari (PhD Memorial; 2018–2021)
  • Fabrizio Donzelli (PhD Miami; 2016–2019)

PhD students

  • Rüdiger Brecht (2017–2021, with S. MacLachlan): Variational integrators for the rotating shallow water equations
  • Stanislav Opanasenko (2017–2021): Symmetry analysis of hydrodynamic-type systems

MSc students

  • Hamideh Mehri (2021–, with H. Usefi): TBD
  • Youssef Zaazou (2021–, with T. Tricco): Deep learning for cheque fraud detection
  • Serhii Koval (2021–): Extended group analysis for Fokker–Planck equations
  • Evan Kielley (2017–2020, with J. Munroe and S. MacLachlan): Iceberg drift ensemble forecasting
  • Nataliia Poltavets (2017–2019): Complete group classification of shallow water equations
  • Lada Atamanchuk-Anhel (2017–2019): Classification of conservation laws of shallow-water equations
  • Oleksandr Abramov (2016–2018, with R. Haynes): Parallelization of a Winslow variational mesh generator
  • Stanislav Opanasenko (2016–2017): Extended symmetry analysis of isothermal no-slip drift flux model
  • Rüdiger Brecht (2016–2017, with J. Behrens, University of Hamburg): Solution of the shallow-water equations with wetting and drying boundary conditions through RBF discretisation

Undergraduate students

  • Wasiim Muhammad Kausmally (2021, with J. Jackaman): Reinforcement learning for the win!
  • Youssef Zaazou (2020–2021): Deep learning for galaxy classification; Solving the shallow-water equations with deep learning
  • Zhuoer Zhao (2020): Time-series prediction with deep neural networks
  • Wasiim Muhammad Kausmally (2020, with J. Jackaman): Physics-informed neural networks for weather prediction
  • Sarah Stone (2019): Deep learning for weather nowcasting
  • Ben Morrison (2017, with S. MacLachlan): Parallelization of a meshless tsunami propagation model
  • Leah Genge (2016–2017, with R. Haynes): Parallel stochastic domain decomposition

A few current and past collaborators

About Me

I obtained my Magister der Naturwissenschaften (MSc equivalent) and PhD in meteorology from the University of Vienna, but I consider myself both an applied mathematician and a meteorologist (I actually learned how to do a weather forecast!). My research is frequently inspired by problems arising in geophysical fluid mechanics. I always try to stay grounded in applications but do not mind taking detours in more theoretical realms if necessary. Despite planning to stay in Austria, thanks to an unsuccessful project application right after I finished my PhD I had to come up with a new plan which led me to become a postdoc at the CRM in Montreal. Gradually falling in love with Canada, I moved around the whole country, with stops at McGill University, Memorial University and the University of British Columbia. Back at Memorial, I started a faculty postition and became a Canada Research Chair in November 2015.

Education

  • Habilitation (mathematics), University of Vienna (2020)
  • PhD (meteorology), University of Vienna (2010)
  • Magister der Naturwissenschaften (meteorology), University of Vienna (2007)

Experience

  • Associate professor, Department of Computer Science (cross-appointed), Memorial University of Newfoundland (May 2021–now)
  • Tier II Canada Research Chair in Numerical Analysis and Scientific Computing, Department of Mathematics and Statistics, Memorial University of Newfoundland (Nov 2015–now)
  • Associate professor, Department of Mathematics and Statistics, Memorial University of Newfoundland (Sept 2019–now)
  • Assistant professor, Department of Mathematics and Statistics, Memorial University of Newfoundland (Nov 2015–Aug 2019)
  • Visiting professor, Institute of Meteorology and Geophysics, University of Vienna (May 2016)
  • Visiting postdoctoral fellow, Department of Mathematics, University of British Columbia (Jan 2015–Oct 2015)
  • Postdoctoral fellow, Department of Mathematics and Statistics, Memorial University of Newfoundland (Jan 2014–Oct 2015)
  • Postdoctoral fellow, Department of Mathematics and Statistics, McGill University (Aug 2013–Dec 2013)
  • Visiting postdoctoral fellow, Department of Mathematics and Statistics, McGill University (June 2012–July 2013)
  • Postdoctoral fellow, Centre de recherches mathématiques, Université de Montréal (Aug 2011–July 2013)
  • Postdoctoral fellow, Faculty of Mathematics, University of Vienna (Jan 2011–July 2011)
  • PhD student, Faculty of Mathematics, University of Vienna (Oct 2008–Dec 2010)
  • Research assistant, Department of Meteorology and Geophysics, University of Vienna (Oct 2007–Sept 2008)

Grants

  • AARMS CRG Mathematical foundations of Scientific Machine Learning (2021–2022)
  • Canada Research Chair in Numerical Analysis and Scientific Computing (2020–2025)
  • NSERC Discovery Grant (2016–2022)
  • IgniteR&D project of the Research & Development Corporation of Newfoundland and Labrador (RDC) (2016–2018)
  • Canada Research Chair in Numerical Analysis and Scientific Computing (2015–2020)
  • Postdoctoral fellowship of the Pacific Institute for the Mathematical Sciences (2014–2016)
  • APART Fellowship of the Austrian Academy of Sciences (2014–2018)
  • Schrödinger Fellowship of the Austrian Science Fund (2011–2014)
  • DOC-Fellowship of the Austrian Academy of Sciences (2009–2010)

Awards

  • CAIMS-PIMS Early Career Award 2018
  • Würdigungspreis des Bundesministeriums für Wissenschaft und Forschung (Award of Excellence of the Austrian Ministry for Science and Research) 2011
  • Awarded the doctor’s degree Sub Auspiciis Praesidentis rei publicae (highest distinction in Austria) in 2011
  • Merit scholarships of the University of Vienna in 2005, 2006, 2007