Dr. Davis’s research group is called the Cyber-Physical Modeling and Analysis (CPMA) team. Our vision is cohesive, comprehensive cyber-physical modeling and analysis for secure and resilient future power systems and their coupled critical infrastructures.
CPMA team focuses on protecting society against a wide range of threats to critical cyber-physical energy infrastructure through improved modeling, situational awareness, analysis, and response, and by efforts to ensure the integrity of the entire control loop by securing and verifying the information flows and the process flows, from monitoring to analysis to control.
Prospective Collaborators and Students
Our research interests involve large-scale modeling, analysis, and simulations of cyber-physical power system critical infrastructure, especially security-oriented control system analysis techniques.
Highly motivated prospective graduate students and post-docs are always encouraged to apply.
CPMA team is always interested in industry, government, and academic partners working with us in research and/or demonstration and development, outreach, technology transition. To find out more, you are encouraged to contact Dr. Davis at email@example.com. CPMA team welcomes collaboration on the difficult challenges in cyber-physical-human system modeling and analysis.
Email Subject Line: $ApplicationTerm Prospective Students $Name
Please highlight your publications (if applicable), GPA/ranking, TOEFL and GRE scores, and anything important
- A short paragraph about what you are looking for in this lab and at Texas A&M
Attach your CV and Transcript
Some of our research projects are described below.
A next-generation secure energy management system that would enable stakeholders across energy industrial control domains to better prepare, mitigate, repair, and recover from cyber-related threats
A secure end-to-end system for managing the energy system, communications, security, modeling and analytics, and response that is fully cyber-physical
An efficient and robust FDI attack detection mechanism via deep neural network (DNN) architectures
Investigating the potential of ecosystems to provide new robust design and operating principles for power grids.
A self-sufficient low cost model to improve resilience in the wildfire response of critical power system infrastructure.
- [10/06/2022] Pursuing greater resilience through nature-inspired power grids. Full news story can be viewed here.
- [5/25/2022] Protecting the power grid through cyber-physical threat response. Full news story can be viewed here.
- [04/21/2022] Department of Energy- DOE Announces $12 Million to Enhance Cybersecurity of America’s Energy Systems. The relevant information can be viewed here.
- [06/24/2021] Organizing Committee for “Innovative Early-Career Engineers Selected to Participate in NAE’s 2021 US Frontiers of Engineering Symposium“. The press release can be viewed here
- [09/29/2020] Drawing on principles from bio designed systems such as the food web will help scientists build more resilience into the electrical power grid. – ASME. The relevant information can be viewed here.