| Deep learning for topology optimization of 2D metamaterials HT Kollmann, DW Abueidda, S Koric, E Guleryuz, NA Sobh Materials & Design 196, 109098, 2020 | 254 | 2020 |
| Alya: Multiphysics engineering simulation toward exascale M Vázquez, G Houzeaux, S Koric, A Artigues, J Aguado-Sierra, R Arís, ... Journal of computational science 14, 15-27, 2016 | 227 | 2016 |
| Topology optimization of 2D structures with nonlinearities using deep learning DW Abueidda, S Koric, NA Sobh Computers & Structures 237, 106283, 2020 | 159 | 2020 |
| Deep learning for plasticity and thermo-viscoplasticity DW Abueidda, S Koric, NA Sobh, H Sehitoglu International Journal of Plasticity 136, 102852, 2021 | 150 | 2021 |
| Efficient thermo-mechanical model for solidification processes and its applications in steel continuous casting S Koric University of Illinois at Urbana-Champaign, 2006 | 125* | 2006 |
| Thermo-mechanical models of steel solidification based on two elastic visco-plastic constitutive laws S Koric, BG Thomas Journal of materials processing technology 197 (1-3), 408-418, 2008 | 120 | 2008 |
| Explicit coupled thermo‐mechanical finite element model of steel solidification S Koric, LC Hibbeler, BG Thomas International Journal for Numerical Methods in Engineering 78 (1), 1-31, 2009 | 92 | 2009 |
| Meshless physics‐informed deep learning method for three‐dimensional solid mechanics DW Abueidda, Q Lu, S Koric International Journal for Numerical Methods in Engineering 122 (23), 7182-7201, 2021 | 85 | 2021 |
| Evaluation of parallel direct sparse linear solvers in electromagnetic geophysical problems V Puzyrev, S Koric, S Wilkin Computers & Geosciences 89, 79-87, 2016 | 73 | 2016 |
| Precision structural engineering of self-rolled-up 3D nanomembranes guided by transient quasi-static FEM modeling W Huang, S Koric, X Yu, KJ Hsia, X Li Nano letters 14 (11), 6293-6297, 2014 | 62 | 2014 |
| Multiphysics model of metal solidification on the continuum level S Koric, LC Hibbeler, R Liu, BG Thomas Numerical Heat Transfer, Part B: Fundamentals 58 (6), 371-392, 2010 | 51 | 2010 |
| Sparse matrix factorization on massively parallel computers A Gupta, S Koric, T George Proceedings of the Conference on High Performance Computing Networking …, 2009 | 48 | 2009 |
| Data-driven and physics-informed deep learning operators for solution of heat conduction equation with parametric heat source S Koric, DW Abueidda International Journal of Heat and Mass Transfer 203, 123809, 2023 | 47 | 2023 |
| Thermomechanical modeling of beam blank casting LC Hibbeler, K Xu, BG Thomas, S Koric, C Spangler Iron & steel technology 6 (7), 60, 2009 | 47 | 2009 |
| Parallel mesh partitioning based on space filling curves R Borrell, JC Cajas, D Mira, A Taha, S Koric, M Vázquez, G Houzeaux Computers & Fluids 173, 264-272, 2018 | 43 | 2018 |
| A deep learning energy method for hyperelasticity and viscoelasticity DW Abueidda, S Koric, RA Al-Rub, CM Parrott, KA James, NA Sobh European Journal of Mechanics-A/Solids 95, 104639, 2022 | 41 | 2022 |
| Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure EA Huerta, A Khan, E Davis, C Bushell, WD Gropp, DS Katz, ... Journal of Big Data 7, 1-12, 2020 | 40 | 2020 |
| Sparse matrix factorization in the implicit finite element method on petascale architecture S Koric, A Gupta Computer Methods in Applied Mechanics and Engineering 302, 281-292, 2016 | 39 | 2016 |
| Alya: towards exascale for engineering simulation codes M Vazquez, G Houzeaux, S Koric, A Artigues, J Aguado-Sierra, R Aris, ... arXiv preprint arXiv:1404.4881, 2014 | 38 | 2014 |
| Evaluation of massively parallel linear sparse solvers on unstructured finite element meshes S Koric, Q Lu, E Guleryuz Computers & Structures 141, 19-25, 2014 | 37 | 2014 |
