Seid Koric

Education

• Ph.D., Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, 2006
• M.S., Aerospace Engineering, University of Illinois at Urbana-Champaign, 1999
• B.S., Mechanical Engineering, University of Sarajevo, Bosnia and Herzegovina, 1993

Academic Positions

• Technical Associate Director, National Center for Supercomputer Applications-NCSA, University of Illinois Urbana-Champaign, 2022-present
• Technical Assistant Director, National Center for Supercomputer Applications-NCSA, University of Illinois Urbana-Champaign, 2017-2022
• Research Associate Professor, Mechanical Science and Engineering Department, University of Illinois Urbana-Champaign, 2016-present
• Technical Program Manager, Private Sector Program, National Center for Supercomputer Applications-NCSA, University of Illinois Urbana-Champaign, 2014-2017
• Senior Technical Lead for Industrial Projects National Center for Supercomputer Applications-NCSA, University of Illinois Urbana-Champaign, 2011-2014
• Adjunct Assistant Professor, Mechanical Science and Engineering Department, University of Illinois Urbana-Champaign, 2010-2014
• Engineering Applications Analyst National Center for Supercomputer Applications-NCSA, University of Illinois Urbana-Champaign, 1999-2011
• Graduate Research Assistant, National Center for Supercomputer Applications-NCSA, University of Illinois Urbana-Champaign, 1997-1999

Professional Registrations

• ASME Member
• U of Illinois Continuous Casting Consortium Research Member

Research Interests

• Artificial intelligence; large-scale multiphysics modeling; materials processing; advanced manufacturing, high-performance computing and biomechanics

Books Authored or Co-Authored (Original Editions)

• Koric, S. and B. G. Thomas, Thermo-Mechanical Model of Solidification Processes: Implementation in Abaqus and Application to Continuous Casting of Steel, VDM Verlag Dr. Muller, 2009.

Chapters in Books

• Luo S., Vellakal M., Koric S., Kindratenko V., Cui J. (2020) Parameter Identification of RANS Turbulence Model Using Physics-Embedded Neural Network. In: Jagode H., Anzt H., Juckeland G., Ltaief H. (eds) High Performance Computing. ISC High Performance 2020. Lecture Notes in Computer Science, vol 12321. Springer, Cham.
• Gupta, A., N. Gimelshein, S. Koric, and S. Rennich, "Effective Minimally-Invasive GPU Acceleration of Distributed Sparse Matrix Factorization," in PM., Dutot, D. Trystram editors. "Euro-Par 2016: Parallel Processing" Springer International Publishing 2016, pp. 672-683.
• Giles M., S. Koric, and E. Burness, "U.S. Industrial Supercomputing at NCSA," in: Osseyran A., Giles M. editors. Industrial Applications of High-Performance Computing, CRC Press, 2015, pp. 179-194

Selected Articles in Journals

• Koric, S; Viswanath, A.; Abueidda, D.W., Sobh, N.A.; Kamran, K., “Deep learning operator network for plastic deformation with variable loads and material properties,” Engineering with Computers, 2023
• He, J.; Abueidda, D.W.; Al-Rub, R.A.; Koric, S.; Jasiuk, I., “A deep learning energy-based method for classical elastoplasticity,” International Journal of Plasticity, Volume 162, 103531, 2023
• Koric, S. and Abueidda, D.W, "Data-Driven and Physics-Informed Deep Learning Operators for Solution of Heat Conduction Equation with Parametric Heat Source," International Journal for Heat and Mass Transfer, 203, 123809, 2023
• You, D.;  Celebi, O.K.; Mohammed, A.S.K; Abueidda, D.W; Koric, S.; Sehitoglu, H., “CRSS determination combining ab-initio Framework and Surrogate Neural Networks,” International Journal of Plasticity, 103524, 2023
• He, J.; Chadha, C.; Kushwaha, S.; Koric, S.; Abueidda, D.; Jasiuk, I., “Deep energy method in topology optimization applications,” Acta Mechanica, 1619-6937, 2022
• Grady. K.; Markus, M.; Shu, W.; Fuyao, W.; Koric, S., “Assessment of the benefits of climate model weights for ensemble analysis in three urban precipitation frequency studies,” Journal of the American Water Resources Association (JAWR), 2022
• Perumal, V.; Abueidda, D.W; Koric, S; Kontsos, A., “Temporal convolutional networks for data-driven thermal modeling of directed energy deposition,” Journal of Manufacturing Processes, 85, 2022
• Abueidda, D.W.; Koric, S.; Guleryuz, E.; Sobh, N.A, “Enhanced physics-informed neural networks for hyperelasticity, “ International Journal for Numerical Methods in Engineering, 2022
• He, J.; Abueidda; D.W.; Koric, S.; Jasiuk I., "On the use of graph neural networks and shape-function-based gradient computation in the deep energy method,“ International Journal for Numerical Methods in Engineering, 2022
• Shahane, S.; Guleryuz, E.; Abueidda, D.W; Lee, A.; Liu, J.; Yu, X.; Chiu, R.; Koric, S.; Aluru, N.R.; Ferreira, P.M., “Surrogate neural network model for sensitivity analysis and uncertainty quantification of the mechanical behavior in the optical lens-barrel assembly, “ Computers & Structures, 270, 106843, 2022
• Abueidda, D.,W., Koric, S., Abu Al-Rub, R., Parrott, C.,M., James, K.,A., Sobh, N.,A. "A deep learning energy method for hyperelasticity and viscoelasticity," European Journal of Mechanics - A/Solids 95, 104639, 2022
• Gregg, P. M., Zhan, Y., Amelung F., Geist, D., Mothes P., Koric, S., Yunjun, Z., “Forecasting mechanical failure and the 26 June 2018 eruption of Sierra Negra Volcano, Galápagos, Ecuador, “ Science Advances 8(22), 2022
• Abueidda D.W., Lu Q., Koric S., "Meshless physics-informed deep learning method for three-dimensional solid mechanics," International Journal for Numerical Methods in Engineering 122 (23), 7182–7201, 2021.
• Koric, S.; Abueidda, D.W., "Deep Learning Sequence Methods in Multiphysics Modeling of Steel Solidification," Metals, 11(3), 494, 2021.
• Sabet, F.A.; Koric, S.; Idkaidek, A., Jasiuk I., “High-Performance Computing Comparison of Implicit and Explicit Nonlinear Finite Element Simulations of Trabecular Bone”, Comput Methods Programs Biomed., 200, 105870, 2021
• Abueidda, D.W., Koric, S., Sobh, N.A., Sehitoglu, H., "Deep learning for plasticity and thermo-viscoplasticity, International Journal of Plasticity," 136, 102852, 2021.
• Abueidda, D.W.; Kang, Z.; Koric, S.; James, K.A; Jasiuk, I.M., “Topology optimization for three-dimensional elastoplastic architected materials using a path-dependent adjoint method,” International Journal for Numerical Methods in Engineering, 122(8), 2020
• E. Goli, S. Vyas, S. Koric, N. Sobh, and P. H. Geubelle, ChemNet: "A Deep Neural Network for Advanced Composites Manufacturing," J. Phys. Chem. B, 2020.
• Kollmann, H. T.; Abueidda, D. W.; Koric, S.; Guleryuz, E.; Sobh, N. A. Deep learning for topology optimization of 2D metamaterials. Materials & Design, 109098, 2020.
• Abueidda, D. W., Koric, S., & Sobh, N. A., "Topology optimization of 2D structures with nonlinearities using deep learning. Computers & Structures," 237,106283, 2020.
• Matthew L.S. Zappulla, Seong-Mook Cho, Seid Koric, Hyoung-Jun Lee, Seon-Hyo Kim, Brian G. Thomas, "Multiphysics modeling of continuous casting of stainless steel," Journal of Materials Processing Technology, 278, 2020.
• Huerta, E.A., Khan, A., Davis, E. S. Koric, et al. "Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure," J Big Data 7, 88, 2020.
• D. Liu, S. Koric, A. Kontsos, "A Multiscale Homogenization Approach for Architectured Knitted Textiles," J. Appl. Mech., 86(11): 111006, 2019.
• A.T. Akono, S. Koric, W. Kriven, "Influence of pore structure on the strength behavior of particle- and fiber-reinforced metakaolin-based geopolymer composites," Cement and Concrete Composites, 104:103361, 2019.
• Yang, Y., Dora Cai, Y., Lu, Q., Zhang, Y., Koric, S. & Shao, C., "Hierarchical Measurement Strategy for Cost-Effective Interpolation of Spatiotemporal Data in Manufacturing," Journal of Manufacturing Systems, 53, 159-168, 2019.
• D Liu, S Koric, A Kontsos, "Parallelized finite element analysis of knitted textile mechanical behavior," Journal of Engineering Materials and Technology, 141 (2), 2019.
• Borrell, R., Cajas, J.C., Mira, D., Taha, A., Koric, S., Vázquez, M., Houzeaux, G., "Parallel mesh partitioning based on space filling curves," Computers and Fluids, 173(15), 264-272, 2018.
• Ashraf Idkaidek, Seid Koric, Iwona Jasiuk, "Fracture analysis of multi-osteon cortical bone using XFEM, Computational Mechanics," 62(2), 171-184, 2018.
• F.A. Sabet, O. Jin, S. Koric, I. Jasiuk1, "Nonlinear micro‐CT based FE modeling of trabecular bone – Sensitivity of apparent response to tissue constitutive law and bone volume fraction," International Journal for Numerical Methods in Biomedical Engineering, 34(4), 1-16, 2018.
• Vázquez, M., G. Houzeaux, and S. Koric, “Alya: Multiphysics engineering simulation toward exascale,” Journal of Computational Science v14,15-27, 2016.
• Koric, S. and A. Gupta, ”Sparse Matrix Factorization in the Implicit Finite Element Method on Petascale Architecture,” Computer Methods in Applied Mechanics and Engineering, 2016 v.32,281-292, 2016.
• Puzyrev, V. and S. Koric, “Evaluation of parallel direct sparse linear solvers in electromagnetic geophysical problems,” Computers & Geosciences, v89, 79-87, 2016.
• Kale, S., S. Koric, and M. Ostoja-Starzewski, “Stochastic continuum damage mechanics using spring lattice models,” Applied Mechanics and Materials v784, 350-357, 2015.
• Kale, S., A. Saharan, S. Koric, and M. Ostoja-Starzewski, “Scaling and bounds in thermal conductivity of planar Gaussian correlated microstructures,” Journal of Applied Physics 117 (10), 104301, 2015.
• Wen, H., S. Koric, Y. Xin, K. Hsia and L. Xiuling, "Precision structural engineering of self-rolled-up 3D nanomembranes guided by transient quasi-static FEM modeling," Nano Letters, v14(9) pp. 6293-6297, 2014.
• Koric S., Q. Lu, and E. Guleryuz, “Evaluation of massively parallel linear sparse solvers on unstructured finite element meshes,” Computers and Structures, v141, 2014.
• Saharan, A., M. Ostoja-Starzewski, and S. Koric, “Fractal Geometric Characterization of Functionally Graded Materials,” ASCE Journal of Nanomechanics and Micromechanics, 3(4), 2013.
• Zubelewicz, A., D.G. Thompson, M. Ostoja-Starzewski, A. Ionita, D. Shunk, M.W. Lewis, N.S. Kale, and S. Koric, "Fracture model for cemented aggregates," AIP Advances v3, 2013.
• Li, J., A. Saharan, S. Koric and M. Ostoja-Starzewski, "Elastic-plastic transitions in 3D random materials: Massively parallel simulations, fractal morphogenesis and scaling function," Philosophical Magazine,92(22) pp 2733-2758, 2012.
• Koric S., L. C. Hibbeler, R. Liu, and B. G. Thomas, "Multiphysics Model of Metal Solidification on the Continuum Level," Numerical Heat Transfer B, 58, 371-392, 2010.
• Koric, S., B. G. Thomas, and V. R. Voller, "Enhanced Latent Heat Method to Incorporate Superheat Effects Into Fixed-Grid Multiphysics Simulations," Numerical Heat Transfer B, 57, 396-413, 2010.
• Koric, S. L. C. Hibbeler, and B. G. Thomas, "Explicit Coupled Thermo-mechanical Finite Element Model of Steel Solidification," International Journal for Numerical Methods in Engineering, 78, 1-31, 2009.
• Hibbeler, L. C. S. Koric, K. Xu, C. Spangler, abd B. G. Thomas, "Thermomechanical Modeling of Beam Blank Casting," Iron and Steel Technology, 6(7), 60-73, 2009.
• Koric, S. and B. G. Thomas, "Thermo-mechanical Models of Steel Solidification Based on Two Elastic Visco-plastic Constitutive Laws, Journal of Materials Processing Technology, 197, 408-418, 2008.
• Koric, S., and B. G. Thomas, "Efficient Thermo-mechanical Model for Solidification Processes," International Journal for Numerical Methods in Engineering, 66, 1955-1989, 2006.

Honors

• NCSA Best Collaborative Effort Award 2010
• NCSA Technical Achievement Award, December 2013
• Key Scientific Article Certificate, Advances in Engineering 2016

Research Honors

• High Performance Computing Innovation Excellence Award from the International Data Corporation (IDC) (November 2011)
• High Performance Computing (HPC) Innovation Excellence Award from the International Data Corporation (IDC) (Jun 2014)
• Best Use of an HPC Application in Manufacturing from HPC-wire (November 2014)
• Top Supercomputing Achievement of 2014 from HPC-wire (November 2014)
• Editors Choice, Journal of Applied Physics (Jun 2015)
• HPCwire Editors' Choice Award for Top Supercomputing Achievement, (November 2017)
• Editor's Choice, Best Use of HPC in Automotive from HPC-wire, with Rolls-Royce, Cray and LSTC, November 2018 (November 2018)
• HPC Innovation Excellence Award from Hyperion Research for the first successful implementation of Artificial Intelligence in Materials Processing, November 2020 (November 2020)
• HPC Innovation Excellence Award, with Roll-Royce, Ansys Inc, Cray/HPE  for LS-DYNA Scaling with the direct implicit finite element solver. (November 2022 )

Other Honors

• Chancellor’s List 2005, The US National Recognition for outstanding graduate/professional students (2005)