Publications

Additional links to my preprints can be found on arXiv.org and ResearchGate. My published work can also be tracked on Scopus and Google Scholar.

Preprints

Proximal Galerkin: A structure-preserving finite element method for pointwise bound constraints with Thomas M. Surowiec arXiv: 2307.12444 [math.NA] [preprint]

Software

DRDMannTurb: A python package for scalable, data-driven synthetic turbulence with Alexey Izmailov, Matthew Meeker, and Georgios Deskos Python Package (2024) [PyPI] [documentation]

Peer-Reviewed Scientific Articles

	Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization with Tobias Duswald, Boyan Lazarov, Socratis Petrides, and Barbara Wohlmuth Computer Methods in Applied Mechanics and Engineering (2024) [preprint] [journal doi]
	High-performance finite elements with MFEM with Julian Andrej, Nabil Atallah, Jan-Phillip Bäcker, John Camier, Dylan Copeland, Veselin Dobrev, Yohann Dudouit, Tobias Duswald, Dohyun Kim, Tzanio Kolev, Boyan Lazarov, Ketan Mittal, Will Pazner, Socratis Petrides, Syun’ichi Shiraiwa, Mark Stowell, and Vladimir Tomov The International Journal of High Performance Computing Applications (2024) [preprint] [journal doi]
	DynAMO: Multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws with Tarik Dzanic, Ketan Mittal, Dohyun Kim, Jiachen Yang, Socratis Petrides, and Robert Anderson Journal of Computational Physics (2024) [preprint] [journal doi]
	Learning robust marking policies for adaptive mesh refinement with Andrew Gillette and Socratis Petrides SIAM Journal on Scientific Computing (2024) [preprint] [journal doi]
	An Adaptive Sampling Augmented Lagrangian Method for Stochastic Optimization with Deterministic Constraints with Raghu Bollapragada, Cem Karamanli, Boyan Lazarov, Socratis Petrides, and Jingyi Wang Computers & Mathematics with Applications (2023) [preprint] [journal doi]
	Adaptive sampling strategies for risk-averse stochastic optimization with constraints with Florian Besier, Simon Urbainczyk, and Barbara Wohlmuth IMA Journal of Numerical Analysis (2022) [preprint] [journal doi]
	Risk-averse design of tall buildings for uncertain wind conditions with Anoop Kodakkal, Ustim Khristenko, Andreas Apostolatos, Kai-Uwe Bletzinger, Barbara Wohlmuth, and Roland Wuechner Computer Methods in Applied Mechanics and Engineering (2022) [preprint] [journal doi]
	Learning orbital dynamics of binary black hole systems from gravitational wave measurements with Akshay Khadse and Scott E. Field Physical Review Research (2021) [preprint] [journal doi] [code] Press release about this work!
	A priori error analysis of high-order LL* (FOSLL*) finite element methods Computers & Mathematics with Applications (2021) [preprint] [journal doi] [code]
	Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer with Ustim Khristenko and Barbara Wohlmuth Physics of Fluids (2021) [preprint] [journal doi] [code1] [code2]
	A fractional PDE model for turbulent velocity fields near solid walls with Ustim Khristenko and Barbara Wohlmuth Journal of Fluid Mechanics (2021) [preprint] [journal doi]
	The surrogate matrix methodology: Accelerating isogeometric analysis of waves with Daniel Drzisga and Barbara Wohlmuth Computer Methods in Applied Mechanics and Engineering (2020) [preprint] [journal doi]
	The DPG-star method with Leszek Demkowicz and Jay Gopalakrishnan Computers & Mathematics with Applications (2020) [preprint] [journal doi]
	The surrogate matrix methodology: A reference implementation for low-cost assembly in isogeometric analysis with Daniel Drzisga and Barbara Wohlmuth MethodsX (2020) [journal doi] [code1] [code2]
	The surrogate matrix methodology: Low-cost assembly for isogeometric analysis with Daniel Drzisga and Barbara Wohlmuth Computer Methods in Applied Mechanics and Engineering (2020) [preprint] [journal doi]
	The surrogate matrix methodology: a priori error estimation with Daniel Drzisga and Barbara Wohlmuth SIAM Journal on Scientific Computing (2019) [preprint] [journal doi]
	Goal-oriented adaptive mesh refinement for discontinuous Petrov–Galerkin methods with Ali Varizi Astaneh and Leszek Demkowicz SIAM Journal on Numerical Analysis (2019) [preprint] [journal doi]
	On perfectly matched layers for discontinuous Petrov–Galerkin methods with Ali Varizi Astaneh and Leszek Demkowicz Computational Mechanics (2019) [preprint] [journal doi]
	Discrete least-squares finite element methods with Socratis Petrides, Federico Fuentes, and Leszek Demkowicz Computer Methods in Applied Mechanics and Engineering (2017) [preprint] [journal doi]
	An ultraweak DPG method for viscoelastic fluids with Philipp Knechtges, Nathan V. Roberts, Stefanie Elgeti, Marek Behr, and Leszek Demkowicz Journal of Non-Newtonian Fluid Mechanics (2017) [preprint] [journal doi]
	Coupled variational formulations of linear elasticity and the DPG methodology with Federico Fuentes, Leszek Demkowicz, and Patrick Le Tallec Journal of Computational Physics (2017) [preprint] [journal doi]
	The DPG methodology applied to different variational formulations of linear elasticity with Federico Fuentes and Leszek Demkowicz Computer Methods in Applied Mechanics and Engineering (2016) [preprint] [journal doi]
	Orientation embedded high order shape functions for the exact sequence elements of all shapes with Federico Fuentes, Leszek Demkowicz, and Sriram Nagaraj Computers & Mathematics with Applications (2015) [preprint] [journal doi] [code]

Conference Proceedings

	Improving explainability of softmax classifiers using a prototype-based joint embedding method with Hilarie Sit and Karianne Bergen Proceedings of the Workshop on Explainable AI at IJCAI [preprint]
	Multi-agent reinforcement learning for adaptive mesh refinement with Jiachen Yang, Ketan Mittal, Tarik Dzanic, Socratis Petrides, Brenden Petersen, Daniel Faissol, and Robert Anderson Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS-2023) [preprint] [link]

Other

	The technique that can find a system’s state through data alone Nature, News & Views (2023) [journal doi] Associated press release!
	A saddle-point paradigm for finite element analysis and its role in the DPG methodology PhD Dissertation, The University of Texas at Austin (2018) [link]
	DPG* Method with Leszek Demkowicz and Jay Gopalakrishnan Technical Report (2017) [link]
	Lagrangian coherent structures in three-dimensional steady flows Master’s Thesis, McGill University (2014) [link]
	The Wave Equation and Multi-Dimensional Time The Waterloo Mathematics Review (2011) [link]