Sparse matrix factorization on massively parallel computers. - Anshul Gupta; Seid Koric; Thomas George (SC, 2009)

XSEDE OpenACC workshop enables Blue Waters Researchers to Accelerate Key Algorithms. - Galen Wesley Arnold; Manisha Gajbe; Seid Koric; John Urbanic (XSEDE, 2014)

Effective Minimally-Invasive GPU Acceleration of Distributed Sparse Matrix Factorization. - Anshul Gupta; Natalia Gimelshein; Seid Koric; Steven C. Rennich (Euro-Par, 2016)

Evaluation of parallel direct sparse linear solvers in electromagnetic geophysical problems. - Vladimir Puzyrev; Seid Koric; Scott Wilkin (Comput. Geosci., 2016)

Alya: Multiphysics engineering simulation toward exascale. - Mariano Vázquez; Guillaume Houzeaux; Seid Koric; Antoni Artigues; Jazmin Aguado-Sierra; Ruth Aris; Daniel Mira; Hadrien Calmet; Fernando M. Cucchietti; Herbert Coppola-Owen; Ahmed Taha; Evan Dering Burness; et al. (J. Comput. Sci., 2016)

Scalability Challenges of an Industrial Implicit Finite Element Code. - François-Henry Rouet; Cleve Ashcraft; Jef Dawson; Roger Grimes; Erman Guleryuz; Seid Koric; Robert F. Lucas; James S. Ong; Todd A. Simons; Ting-Ting Zhu (IPDPS, 2020)

Parameter Identification of RANS Turbulence Model Using Physics-Embedded Neural Network. - Shirui Luo; Madhu Vellakal; Seid Koric; Volodymyr V. Kindratenko; Jiahuan Cui (ISC Workshops, 2020)

Machine learning accelerated topology optimization of nonlinear structures. - Diab W. Abueidda; Seid Koric; Nahil A. Sobh (CoRR, 2020)

Deep learning collocation method for solid mechanics: Linear elasticity, hyperelasticity, and plasticity as examples. - Diab W. Abueidda; Qiyue Lu; Seid Koric (CoRR, 2020)

Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure. - Eliu A. Huerta; Asad Khan; Edward Davis; Colleen Bushell; William D. Gropp; Daniel S. Katz; Volodymyr V. Kindratenko; Seid Koric; William T. C. Kramer; Brendan McGinty; Kenton McHenry; Aaron Saxton (J. Big Data, 2020)

Turbomachinery Blade Surrogate Modeling Using Deep Learning. - Shirui Luo; Jiahuan Cui; Vignesh Sella; Jian Liu; Seid Koric; Volodymyr V. Kindratenko (ISC Workshops, 2021)

High-Performance Computing Comparison of Implicit and Explicit Nonlinear Finite Element Simulations of Trabecular Bone. - Fereshteh A. Sabet; Seid Koric; Ashraf Idkaidek; Iwona Jasiuk (Comput. Methods Programs Biomed., 2021)

A deep learning energy method for hyperelasticity and viscoelasticity. - Diab W. Abueidda; Seid Koric; Rashid K. Abu Al-Rub; Corey M. Parrott; Kai A. James; Nahil A. Sobh (CoRR, 2022)

Surrogate Neural Network Model for Sensitivity Analysis and Uncertainty Quantification of the Mechanical Behavior in the Optical Lens-Barrel Assembly. - Shantanu Shahane; Erman Guleryuz; Diab W. Abueidda; Allen Lee; Joe Liu; Xin Yu; Raymond Chiu; Seid Koric; Narayana R. Aluru; Placid M. Ferreira (CoRR, 2022)

Enhanced physics-informed neural networks for hyperelasticity. - Diab W. Abueidda; Seid Koric; Erman Guleryuz; Nahil A. Sobh (CoRR, 2022)

Deep energy method in topology optimization applications. - Junyan He; Shashank Kushwaha; Charul Chadha; Seid Koric; Diab W. Abueidda; Iwona Jasiuk (CoRR, 2022)

On the use of graph neural networks and shape-function-based gradient computation in the deep energy method. - Junyan He; Diab W. Abueidda; Seid Koric; Iwona Jasiuk (CoRR, 2022)

A deep learning energy-based method for classical elastoplasticity. - Junyan He; Diab W. Abueidda; Rashid K. Abu Al-Rub; Seid Koric; Iwona Jasiuk (CoRR, 2022)

Toward Exascale Computation for Turbomachinery Flows. - Yuhang Fu; Weiqi Shen; Jiahuan Cui; Yao Zheng 003; Guangwen Yang; Zhao Liu; Jifa Zhang; Tingwei Ji; Fangfang Xie; Xiaojing Lv; Hanyue Liu; Xu Liu; et al. (SC, 2023)

Cybershuttle: An End-to-End Cyberinfrastructure Continuum to Accelerate Discovery in Science and Engineering. - Suresh Marru; Marlon E. Pierce; Beth Plale; Sudhakar Pamidighantam; Dimuthu Wannipurage; Marcus Christie; Isuru Ranawaka; Eroma Abeysinghe; Rob Quick; Emad Tajkhorshid; Seid Koric; Jim Basney; et al. (PEARC, 2023)

Gyroid-like metamaterials: Topology optimization and Deep Learning. - Asha Viswanath; Diab W. Abueidda; Mohamad Modrek; Kamran Ahmed Khan; Seid Koric; Rashid K. Abu Al-Rub (CoRR, 2023)

Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads. - Junyan He; Seid Koric; Shashank Kushwaha; Jaewan Park; Diab W. Abueidda; Iwona Jasiuk (CoRR, 2023)

Sequential Deep Learning Operator Network (S-DeepONet) for Time-Dependent Loads. - Jaewan Park; Shashank Kushwaha; Junyan He; Seid Koric; Diab W. Abueidda; Iwona Jasiuk (CoRR, 2023)

Towards Exascale Computation for Turbomachinery Flows. - Yuhang Fu; Weiqi Shen; Jiahuan Cui; Yao Zheng; Guangwen Yang; Zhao Liu; Jifa Zhang; Tingwei Ji; Fangfang Xie; Xiaojing Lv; Hanyue Liu; Xu Liu; et al. (CoRR, 2023)

Multi-component Predictions of Transient Solution Fields with Sequential Deep Operator Network. - Junyan He; Shashank Kushwaha; Jaewan Park; Seid Koric; Diab W. Abueidda; Iwona Jasiuk (CoRR, 2023)

Material-Response-Informed DeepONet and its Application to Polycrystal Stress-strain Prediction in Crystal Plasticity. - Junyan He; Deepankar Pal; Ali Najafi; Diab W. Abueidda; Seid Koric; Iwona Jasiuk (CoRR, 2024)

Geom-DeepONet: A Point-cloud-based Deep Operator Network for Field Predictions on 3D Parameterized Geometries. - Junyan He; Seid Koric; Diab W. Abueidda; Ali Najafi; Iwona Jasiuk (CoRR, 2024)

Advanced Deep Operator Networks to Predict Multiphysics Solution Fields in Materials Processing and Additive Manufacturing. - Shashank Kushwaha; Jaewan Park; Seid Koric; Junyan He; Iwona Jasiuk; Diab W. Abueidda (CoRR, 2024)

Nonlinear Inverse Design of Mechanical Multi-Material Metamaterials Enabled by Video Denoising Diffusion and Structure Identifier. - Jaewan Park; Shashank Kushwaha; Junyan He; Seid Koric; Qibang Liu; Iwona Jasiuk; Diab W. Abueidda (CoRR, 2024)

Virtual Sensing for Real-Time Degradation Monitoring of Nuclear Systems: Leveraging DeepONet for Enhanced Sensing Coverage for Digital Twin-Enabling Technology. - Raisa Bentay Hossain; Farid Ahmed; Kazuma Kobayashi; Seid Koric; Diab W. Abueidda; Syed Bahauddin Alam (CoRR, 2024)

Univariate Conditional Variational Autoencoder for Morphogenic Patterns Design in Frontal Polymerization-Based Manufacturing. - Qibang Liu; Pengfei Cai; Diab W. Abueidda; Sagar Vyas; Seid Koric; Rafael Gómez-Bombarelli; Philippe H. Geubelle (CoRR, 2024)

Sequential Deep Operator Networks (S-DeepONet) for predicting full-field solutions under time-dependent loads. - Junyan He; Shashank Kushwaha; Jaewan Park; Seid Koric; Diab W. Abueidda; Iwona Jasiuk (Eng. Appl. Artif. Intell., 2024)

Deep learning operator network for plastic deformation with variable loads and material properties. - Seid Koric; Asha Viswantah; Diab W. Abueidda; Nahil A. Sobh; Kamran Ahmed Khan (Eng. Comput., 2024)

Geometry-Informed Neural Operator Transformer. - Qibang Liu; Vincient Zhong; Hadi Meidani; Diab W. Abueidda; Seid Koric; Philippe H. Geubelle (CoRR, 2025)

From Proxies to Fields: Spatiotemporal Reconstruction of Global Radiation from Sparse Sensor Sequences. - Kazuma Kobayashi; Samrendra Roy; Seid Koric; Diab W. Abueidda; Syed Bahauddin Alam (CoRR, 2025)

When Network Architecture Meets Physics: Deep Operator Learning for Coupled Multiphysics. - Kazuma Kobayashi; Jaewan Park; Qibang Liu; Seid Koric; Diab W. Abueidda; Syed Bahauddin Alam (CoRR, 2025)

Bridging Sequential Deep Operator Network and Video Diffusion: Residual Refinement of Spatio-Temporal PDE Solutions. - Jaewan Park; Farid Ahmed; Kazuma Kobayashi; Seid Koric; Syed Bahauddin Alam; Iwona Jasiuk; Diab W. Abueidda (CoRR, 2025)