Dr. Kate Davis is an Associate Professor in the Department of Electrical and Computer Engineering at Texas A&M University. Dr. Davis’s work has pioneered significant enhancements to power system cyber-physical security by advancing cyber-physical modeling and analysis capabilities. Prior to joining Texas A&M in 2017, Dr. Davis was a Software Engineer and Senior Consultant for PowerWorld Corporation and with University of Illinois’s Information Trust Institute as a Research Scientist. Her expertise includes large scale modeling, analysis, and simulations of cyber-physical power system critical infrastructure, where she has particular interest in security-oriented control system analysis techniques. She also works to facilitate transition to practice of state-of-the-art cyber-physical situational awareness capabilities for power utilities. She was recognized as IEEE Senior Member (2018), received the Texas A&M Engineering Experiment Station Engineering Genesis Award (2019), and became a Texas A&M Engineering Experiment Station (TEES) Young Faculty Fellow (2021). She leads the Resilient Energy Systems Lab (RESLab), the cyber-physical emulation testbed created by her group, fully functional since 2020.
Education
- Ph. D. in Electrical Engineering, Power and Energy Systems, University of Illinois, Urbana-Champaign, IL, 2011
- M.S. in Electrical Engineering, Power and Energy Systems, University of Illinois, Urbana-Champaign, IL, 2009
- B.S. in Electrical Engineering, University of Texas, Austin 2007
Research Interests
Professor Kate Davis studies power system modeling, analysis, and control with a focus on data-driven, security-oriented techniques that consider the interdependencies of electrical and cyber infrastructures. Her research interest(s) include:
- Power Systems Operation and Control
- Power System Stability
- Power System Analysis by Computer Methods
- Power System Visualization
- Renewable Electric Energy Systems
- Smart Grid Cyber Security
- Cyber-Physical System Modeling
- Power System Geomagnetic Disturbance Modeling