John Baugh

Professor

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

Ph. D. 1989

Civil Engineering

Carnegie Mellon University

M.S. 1984

Civil Engineering

Carnegie Mellon University

B.C.E. 1983

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

View all publications via NC State Libraries

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)