Dr. Patrick Shriwise | Computer Aided Design | Best Researcher Award

Dr. Patrick Shriwise | Computer Aided Design | Best Researcher Award

Argonne National Laboratory | United States

Dr. Patrick Shriwise is a computational scientist specializing in nuclear systems analysis, Monte Carlo particle transport, scientific computing, and software engineering. His work spans advanced simulations for fission and fusion systems, development of OpenMC capabilities, and research in computational geometry and CAD-based radiation transport. He has contributed to high-performance computing, multiphysics applications, visualization, and ray-tracing technologies across national laboratory and academic environments. He is an active member of multiple professional organizations, serves as a reviewer for scientific journals, and regularly contributes to teaching through guest lectures and Software Carpentry instruction. His technical expertise includes C/C++, Python, HPC frameworks, CAD/CAE modeling, cloud computing, and a wide range of nuclear engineering simulation tools.

Romano, P. K., Pasmann, S., Shriwise, P. C., & Swanson, C. P. S. (2025). Computing material volume fractions on a superimposed mesh as applied to Monte Carlo particle transport simulations. Fusion Engineering and Design, 220, 115364.

Romano, P. K., Myers, P. A., Johnson, S. R., Kols̆ek, A., & Shriwise, P. C. (2025). Point containment algorithms for constructive solid geometry with unbounded primitives. Computer-Aided Design, 178, 103803.

Romano, P., Tramm, J., & Shriwise, P. (2024). Language and design evolution of the OpenMC Monte Carlo particle transport code. EPJ Nuclear Sciences & Technologies, 10, 15.

Peterson, E. E., Romano, P. K., Shriwise, P. C., & Myers, P. A. (2024). Development and validation of fully open-source R2S shutdown dose rate capabilities in OpenMC. Nuclear Fusion, 64(5), 056011.

Novak, A. J., Shriwise, P., Romano, P. K., Rahaman, R., Merzari, E., & Gaston, D. (2023). Coupled Monte Carlo transport and conjugate heat transfer for wire-wrapped bundles within the MOOSE framework. Nuclear Science and Engineering, 197(10), 2561–2584.