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

Biography

Seid Koric received his B.S. in Mechanical Engineering from the University of Sarajevo (1993). He earned M.S. in aerospace engineering (1999) and Ph.D. in mechanical engineering (2006) from the University of Illinois at Urbana-Champaign. Dr. Koric is currently the associate technical director at the National Center for Supercomputing Applications (NCSA) and a full-rank research professor in the Mechanical Science and Engineering Department at the University of Illinois. He provides technical and strategic leadership for the NCSA’s Research Consulting directorate, whose staff works on solutions for grand challenges in industry and academia.

Earlier in his career, Dr. Koric developed, implemented, and tested several ground-breaking numerical methods for solving highly nonlinear multiphysics and multiphase problems in materials processing. They have been used worldwide to optimize continuous casting and other steel-making processes and minimize their defects and CO₂ footprint. Later, Dr. Koric led research projects on the world’s first sustained open-science petascale supercomputing system of Blue Waters that demonstrated the scalability of engineering industrial applications on the peta and even potentially exascale computing level. Since 2019, Dr. Koric has led novel interdisciplinary research at the University of Illinois, demonstrating how artificial intelligence (AI) with innovative machine and deep learning methods could assist and drastically accelerate (up to 100,000x speedups) classical numerical methods and solve some previously considered unsolvable engineering and scientific problems in modeling, design, optimizations, sensitivity analysis, online controls, and digital twins.

Dr. Koric also worked in multiphysics, advanced manufacturing processes, sparse linear solvers, biomechanics, finite element methods, GPUs, and industrial HPC computing. His research has been highly influential, earning him an array of prestigious HPC and engineering awards – most notably the two top supercomputing achievement awards in 2014 and 2017. He has published or contributed to over 90 research papers and articles on a diverse range of topics.

Academic Positions

• Research Professor, Mechanical Science and Engineering Department, University of Illinois Urbana-Champaign, 2024-Present
• 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, 2016-2024
• 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

• Member of Bosnian-Herzegovinian American Academy of Arts and Sciences (BHAAAS), 2024-present https://www.bhaaas.org/
• Affiliate of the Center for Artificial Intelligence Innovation (CAII) at UIUC, 2019-present https://ai.ncsa.illinois.edu/directory/center-affiliates/
• ASME Member
• U of Illinois Continuous Casting Consortium Research Member

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

• Kushwaha, S.; Park, J.; Koric, S.; He, J.; Jasiuk, I.; Abueidda, D., “Advanced deep operator networks to predict multiphysics solution fields in materials processing and additive manufacturing”, Additive Manufacturing, 104266, 2024
• He, J.; Koric, S.; Abueidda, D.; Najafi, A.; Jasiuk, I., “Geom-DeepONet: A point-cloud-based deep operator network for field predictions on 3D parameterized geometries”, Computer Methods in Applied Mechanics and Engineering 429, 117130, 2024
• He, J.; Kushwaha, S.; Park, J.; Koric,  S.; Abueidda, D.; Jasiuk, I., “Predictions of transient vector solution fields with sequential deep operator network”,  Acta Mechanica, 1-16, 2024
• He, J.; Pal, D.; Najafi, A.; Abueidda, D.; Koric, S.; Jasiuk, I., “Material-Response-Informed DeepONet and Its Application to Polycrystal Stress–Strain Prediction in Crystal Plasticity, JOM, 1-11, 2024
• Qibang, L.; Abueidda, D.; Vyes, S.; Gao, Y.; Koric, S.; Geubelle, P.; “Adaptive Data-Driven Deep-Learning Surrogate Model for Frontal Polymerization in Dicyclopentadiene,” The Journal of Physical Chemistry B, 128, 5, 1220–1230, (2024)
• He, J.; Kushwaha, S.; Park J.; Koric, S.; Abueidda, D.; Jasiuk, I.; “Sequential Deep Operator Networks (S-DeepONet) for Predicting Full-field Solutions Under Time-dependent Loads”, Engineering Applications of Artificial Intelligence, 127 (2024), Part A.  
• He, J.; Koric S.; Kushwaha, S.; Park, J.; Abueidda D.W.; Jasiuk, I., “Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads”, Comput. Methods Appl. Mech. Engrg. 415 (2023) 116277
• 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)