Mohammad Reza Khalghani

Dr. Mohammad Reza Khalghani is an associate professor in the Department of Electrical, Computer and Cybersecurity Engineering at Florida Polytechnic University, where he joined in August 2019 as an assistant professor.

His research spans smart grids, power system control and dynamics, and cyber-physical security. His recent work focuses on applying artificial intelligence for cyber-physical anomaly detection and mitigation, as well as advancing modeling and resilient control of renewable energy and power grids.

At Florida Poly, Khalghani has led curriculum and concentration development, served on key university committees, and developed and taught more than 10 courses in electrical and cybersecurity engineering. He has secured multiple funded research projects, industry collaborations, and educational grants as principal investigator. He has also worked with industry partners to address emerging challenges in the power and energy sector and has disseminated findings through invited talks and panel sessions.

Dedicated to advancing student success, he has mentored undergraduate and graduate students through funded research and theses. His scholarly contributions include more than 40 peer-reviewed conference papers, journal articles, and industry technical reports.

Beyond the University, Khalghani is an IEEE senior member and serves in leadership roles, including Technical Committee program chair for the IEEE Power & Energy Society’s (PES) Power System Communication and Cybersecurity Committee and vice chair of the IEEE PES Career Promotion and Workforce Development Subcommittee. He also regularly reviews research proposals for federal agencies, including the Department of Energy, as well as technical papers and textbooks.

Through his technical innovation, academic leadership, and professional service, Khalghani is dedicated to promoting resilient, sustainable, and secure energy systems for the future.

Education

• Ph.D. in Electrical Engineering, West Virginia University, 2019
• M.S. in Electrical Engineering, University of Birjand, 2012

Expertise

• Smart Grid
• Renewable Energy
• Cyber-Security
• Control Theories and Application
• Electric Vehicle Integration

Professional Activities

• Member, IEEE
• Member, IEEE Power & Energy Society

Select Publications

• M. R. Khalghani, S. K. Solanki, J. Solanki, and A. Sargolzaei, Resilient and stochastic load frequency control of microgrids,” in 2019 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2019, pp. 1-5.
• M. R. Khalghani, S. Khushalani-Solanki, J. Solanki, and A. Sargolzaei, Stochastic load frequency control of microgrids including wind source based on identification method,” in Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEICI&CPS Europe), 2018 IEEE International Conference on. IEEE, 2018, pp. 1-6.
• M. R. Khalghani, M. H. Khooban, E. Mahboubi-Moghaddam, N. Vafamand, and M. Goodarzi, \A self-tuning load frequency control strategy for microgrids: Human brain emotional learning,” International Journal of Electrical Power Energy Systems, vol. 75, pp. 311-319, 2016.
• H. Heydari-Doostabad, M. R. Khalghani, M. H. Khooban, “A Novel Control System Design to Improve LVRT Capability of Fixed Speed Wind Turbines using STATCOM in Presence of Voltage Fault,” International Journal of Power and Energy Systems, Vol. 77, pp. 280-286, 2016.
• M. R. Khalghani, and M.H. Khooban, “A Novel Self-Tuning Control Method Based on Regulated Bi-objective Emotional Learning Controller’s Structure with TLBO Algorithm to Control DVR Compensator,” Journal of Applied Soft Computing, Vol. 24, pp. 912–922, November 2014.
• M. R. Khalghani, and M.H. Khooban, “A Novel Self-Tuning Control Method Based on Regulated Bi-objective Emotional Learning Controller’s Structure with TLBO Algorithm to Control DVR Compensator,” Journal of Applied Soft Computing, Vol. 24, pp. 912–922, November 2014.
• M.R. Khalghani, M.A. Shamsi-nejad and M. H. Khooban,“DVR Control Using Bi-objective Optimization to Improve Power Quality’s Indices,” IET Science, Measurement & Technology, Vol. 8, Issue 4, pp. 203–213, July 2014.