Jian Shi
Jian Shi
Faculty
CV
jian@cavs.msstate.edu

Office: CAVS 2121
Phone: (662) 325-0104





Biography:
Dr. Jian Shi received his Ph.D. in Electrical and Computer Engineering in 2014 at Mississippi State University with a research emphasis in power system modeling&simulation and control system design. Dr. Shi is currently an assistant research professor at the Center for Advanced Vehicular Systems (CAVS) in Mississippi State University.


Research Interest:
electric power system, micro-grid, Electric ship, modeling and simulation, performance management system, model predictive control, distributed control, model-integrated computing, high-performance computing


Hobbies:
\"We cannot solve our problems with the same thinking we used when we created them.\" - Albert Einstein


Selected PublicationsTotal Publications by Jian Shi:  23 
Sockeel, N., Shi, J., Shahverdi, M. S., & Mazzola, M. S. (2018). Sensitivity Analysis of the Vehicle Model Mass for Model Predictive Control Based Power Management System of a Plug-in Hybrid Electric Vehicle. 2018 IEEE Transportation Electrification Conference and Expo (ITEC). Long beach, CA.

Sockeel, N., Shi, J., Shahverdi, M. S., & Mazzola, M. S. (2018). Pareto Front Analysis of the Objective Function in Model Predictive Control Based Power Management System of a Plug-in Hybrid Electric Vehicle. 2018 IEEE Transportation Electrification Conference and Expo (ITEC). Long beach, CA.

Laktarashani, M. B., Shi, J., & Abdelwahed, S. (2018). A Survey on Fault Detection, Isolation, and Reconfiguration Methods in Electric Ship Power Systems. IEEE Access. IEEE. 1, 1-12. DOI:10.1109/ACCESS.2018.2798505.

Shi, J., Sullivan, B., Mazzola, M., Saravi, B., Adhikari, U., & Haupt, T. (2017). A Relaxation-based Network Decomposition Algorithm for Parallel Transient Stability Simulation with Improved Convergence. IEEE Transactions on Parallel and Distributed Systems. 90, 1. [Document Site]

Zohrabi, N., Abdelwahed, S., & Shi, J. (2017). Reconfiguration of MVDC Shipboard Power Systems: a Model Predictive Control Approach. IEEE Electric Ship Technologies Symposium (ESTS), 2017. Washington, DC. [Document Site]