Shuva Paul is a power systems cybersecurity researcher in NREL’s Energy Security and Resilience Center. Paul’s current research interests include collaborative autonomy, computational intelligence, reinforcement learning, game theory, and smart grid security for power transmission and distribution systems. He performs event and anomaly detection, vulnerability and resilience assessments, and big data analytics.

Paul has a Ph.D. degree in electrical engineering and computer science from South Dakota State University, and completed his M.S. and B.S. degree in electrical and electronics engineering at American International University – Bangladesh, in Dhaka, Bangladesh.

He has contributed to many research conferences, including serving as the session chair of the 2013 IEEE EnergyTech and the 2019 IEEE Electro Information Technology conference, and as a reviewer for the IEEE PES General Meeting, IEEE Symposium Series on Computational Intelligence, International Joint Conference on Neural Networks, and others. Paul served as a guest editor for the Journal of Sensor and Actuator Networks, and has reviewed for IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Smart Grid, Neurocomputing, IEEE Access, IET The Journal of Engineering, and other journals.

Research Interests

Machine learning, deep learning, and game theory applications in critical infrastructure systems

Events and anomalies detection in critical infrastructure systems

Supply chain cybersecurity for the electric power grid

Cyber-physical energy systems security and resilience

Education

Ph.D., Electrical Engineering, South Dakota State University

M.S., Electrical and Electronics Engineering, American International University – Bangladesh

B.S., Electrical and Electronics Engineering, American International University – Bangladesh

Professional Experience

Researcher III, NREL (2022 – Present)

Postdoctoral Fellow, Georgia Institute of Technology (February 2021 – May 2022)

Postdoctoral Research Associate, Washington State University (June 2020 – January 2021)

Graduate Intern, NREL (May 2019 – May 2020)

Graduate Research Assistant, South Dakota State University (2016 – 2019)

Associations and Memberships

Member, Institute of Electrical and Electronics Engineers (IEEE)

Member, Power and Energy Society

Featured Work

A Cryptographic Method for Defense Against MiTM Cyber Attack in the Electricity Grid Supply Chain, Proceedings of the Thirteenth Conference on Innovative Smart Grid Technologies (2022)

Knowledge-Based Fault Diagnosis for a Distribution System with High PV Penetration, Proceedings of the Thirteenth Conference on Innovative Smart Grid Technologies (2022)

On Vulnerability and Resilience of Cyber-Physical Power Systems: A Review, IEEE Systems Journal (2022)

Planning for Resilient Power Distribution Systems using Risk-Based Quantification and Q-Learning, IEEE Power & Energy Society General Meeting (2021)

Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-learning, IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (2020)

A Learning-Based Solution for an Adversarial Repeated Game in Cyber–Physical Power Systems, IEEE Transactions on Neural Networks and Learning Systems (2020)

A Multistage Game in Smart Grid Security: A Reinforcement Learning Solution, IEEE Transactions on Neural Networks and Learning Systems (2019)