Ralph Smith
Mathematics
- Phone: 919-515-7552
- Email: rsmith@ncsu.edu
- Office: SAS Hall 4140
- Website: https://rsmith.math.ncsu.edu/
Research Interests
- Mathematical modeling of smart materials
- Numerical analysis and numerical methods for physical systems
- Parameter estimation
- Control theory
- Uncertainty quantification
- Sensitivity analysis.
Publications
- Local Identifiability Analysis, Parameter Subset Selection and Verification for a Minimal Brain PBPK Model
- Dadashova, K., Smith, R. C., & Haider, M. A. (2024), BULLETIN OF MATHEMATICAL BIOLOGY, 86(2). https://doi.org/10.1007/s11538-023-01234-4
- Quantifying collective motion patterns in mesenchymal cell populations using topological data analysis and agent-based modeling
- Nguyen, K. C., Jameson, C. D., Baldwin, S. A., Nardini, J. T., Smith, R. C., Haugh, J. M., & Flores, K. B. (2024), MATHEMATICAL BIOSCIENCES, 370. https://doi.org/10.1016/j.mbs.2024.109158
- Controller Design for Distributed Parameter Systems
- Smith, R. C. C. (2023, February), IEEE CONTROL SYSTEMS MAGAZINE, Vol. 43, pp. 98–100. https://doi.org/10.1109/MCS.2022.3216693
- Effects of problem complexity reduction on parameter sensitivity and classification in charring ablator scenarios
- Rostkowski, P., Meurisse, J. B. E., Thornton, J. M., Smith, R. C., & Panesi, M. (2022), AEROSPACE SCIENCE AND TECHNOLOGY, 124. https://doi.org/10.1016/j.ast.2022.107522
- A hierarchical Bayesian model for background variation in radiation source localization
- Michaud, I. J., Schmidt, K., Smith, R. C., & Mattingly, J. (2021), NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 1002. https://doi.org/10.1016/j.nima.2021.165288
- Modeling and Parameter Subset Selection for Fibrin Polymerization Kinetics with Applications to Wound Healing
- Pearce, K. J., Nellenbach, K., Smith, R. C., Brown, A. C., & Haider, M. A. (2021), Bulletin of Mathematical Biology, 83(5). https://doi.org/10.1007/s11538-021-00876-6
- SURROGATE BASED MUTUAL INFORMATION APPROXIMATION AND OPTIMIZATION FOR URBAN SOURCE LOCALIZATION
- Hollis, A. N., Smith, R. C., & Wilson, A. G. (2021), INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION, 11(5), 39–55. https://doi.org/10.1615/Int.J.UncertaintyQuantification.2021034400
- The maximum entropy method for data fusion and uncertainty quantification in multifunctional materials and structures
- Gao, W., Miles, P. R., Smith, R. C., & Oates, W. S. (2021, October 8), JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES, Vol. 10. https://doi.org/10.1177/1045389X211048220
- Uncertainty Quantification and Sensitivity Analysis of Partial Charges on Macroscopic Solvent Properties in Molecular Dynamics Simulations with a Machine Learning Model
- Peerless, J. S., Kwansa, A. L., Hawkins, B. S., Smith, R. C., & Yingling, Y. G. (2021), JOURNAL OF CHEMICAL INFORMATION AND MODELING, 61(4), 1745–1761. https://doi.org/10.1021/acs.jcim.0c01204
- Bayesian inference and uncertainty propagation using efficient fractional-order viscoelastic models for dielectric elastomers
- Miles, P. R., Pash, G. T., Smith, R. C., & Oates, W. S. (2021), JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES, 32(4), 486–496. https://doi.org/10.1177/1045389X20969847
