John Baugh
Professor

- 919-515-7697
- jwb@ncsu.edu
- Fitts-Woolard Hall 3163
- Visit My Website
John Baugh is a Professor of Civil Engineering and Operations Research at North Carolina State University. He received the Ph.D. from Carnegie Mellon University in 1989.
In addition to carrying out research and instructional programs, Dr. Baugh works broadly within the university to improve the educational opportunities and outcomes of its students. Included among those efforts is leadership in creating a new graduate program in the areas of computing and systems engineering, and previously serving as Director of the NC Japan Center.
Before pursuing the Ph.D., he worked as a Research Engineer in Applied Mechanics and Structures at Battelle’s Pacific Northwest National Laboratory. He is a member of ACM, INFORMS, Phi Kappa Phi, Tau Beta Pi, and Chi Epsilon.
Education
Civil Engineering
Carnegie Mellon University
Civil Engineering
Carnegie Mellon University
Civil Engineering
Auburn University
Research Description
Dr. Baugh's research interests include scientific computing and cyber-physical systems, formal methods for safe and trustworthy software, verification and validation, mathematical optimization and control, and applications across civil engineering including coastal, ocean, transportation, and structural systems. Current and past funding sources include the US Department of Energy, National Science Foundation, Department of Homeland Security, Federal Transit Administration, US Environmental Protection Agency, and North Carolina Supercomputing Center.
Publications
- An HPC Practitioner’s Workbench for Formal Refinement Checking
- Benavides, J., Baugh, J., & Gopalakrishnan, G. (2023), In Languages and Compilers for Parallel Computing (pp. 64–72). https://doi.org/10.1007/978-3-031-31445-2_5
- Automatic modelling and verification of AUTOSAR architectures?
- Zhang, M., Teng, Y., Kong, H., Baugh, J., Su, Y., Mi, J., & Du, B. (2023), JOURNAL OF SYSTEMS AND SOFTWARE, 201. https://doi.org/10.1016/j.jss.2023.111675
- Formalisation, Abstraction and Refinement of Bond Graphs
- Banach, R., & Baugh, J. (2023). , . https://doi.org/10.1007/978-3-031-36709-0_8
- Significance of multi-hazard risk in design of buildings under earthquake and wind loads
- Kwag, S., Gupta, A., Baugh, J., & Kim, H.-S. (2021), ENGINEERING STRUCTURES, 243. https://doi.org/10.1016/j.engstruct.2021.112623
- A simple Hybrid Event-B model of an active control system for earthquake protection
- Banach, R., & Baugh, J. (2020), In A. Adamatzky & V. Kendon (Eds.), From Astrophysics to Unconventional Computation (Vol. 35, pp. 157–194). https://doi.org/10.1007/978-3-030-15792-0_7
- Bounded Verification of Sparse Matrix Computations
- Dyer, T., Altuntas, A., & Baugh, J. (2019), 2019 IEEE/ACM 3rd International Workshop on Software Correctness for HPC Applications (Correctness), 36–43. https://doi.org/10.1109/correctness49594.2019.00010
- Formal methods and finite element analysis of hurricane storm surge: A case study in software verification
- Baugh, J., & Altuntas, A. (2018), SCIENCE OF COMPUTER PROGRAMMING, 158, 100–121. https://doi.org/10.1016/j.scico.2017.08.012
- Hybrid theorem proving as a lightweight method for verifying numerical software
- Altuntas, A., & Baugh, J. (2018), PROCEEDINGS OF CORRECTNESS 2018: 2ND IEEE/ACM INTERNATIONAL WORKSHOP ON SOFTWARE CORRECTNESS FOR HPC APPLICATIONS, pp. 1–8. https://doi.org/10.1109/Correctness.2018.00005
- Numerical study on factors influencing typhoon-induced storm surge distribution in Zhanjiang Harbor
- Liu, X., Jiang, W., Yang, B., & Baugh, J. (2018), Estuarine, Coastal and Shelf Science, 215, 39–51. https://doi.org/10.1016/j.ecss.2018.09.019
- State-based formal methods in scientific computation
- Baugh, J., & Dyer, T. (2018), In M. Butler, A. Raschke, T. S. Hoang, & K. Reichl (Eds.), Abstract State Machines, Alloy, B, TLA, VDM, and Z (pp. 392–396). https://doi.org/10.1007/978-3-319-91271-4_29
Grants
- Collaborative Research: FMitF: Track-1: Correctness at Both Ends: Rigorous ML Meets Efficient Sparse Implementations
- National Science Foundation (NSF)(10/01/21 - 9/30/24)
- Development and Application of a Data-Driven Methodology for Validation of Risk Informed Safety Margin Characterization Models
- US Dept. of Energy (DOE)(10/01/16 - 12/30/20)
- Engineering for Resilient Civil Infrastructure Systems: A Graduate Research Fellowship Program
- US Dept. of Homeland Security (DHS)(9/30/09 - 9/30/13)
- Engineering the Civil Infrastructure For Enhanced Resiliance of the Built and Natural Environments
- US Dept. of Homeland Security (DHS)(7/01/08 - 6/30/15)
- Modeling and Optimization of Civil Engineering Infrastructure
- Blue Ridge Analytics, Inc.(12/01/04 - 4/30/06)