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09/01/2023
Application of Deep Learning Methods in Monitoring and Optimization of Electric Power Systems
This PhD thesis thoroughly examines the utilization of deep learning tec...
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05/24/2023
Non-adversarial Robustness of Deep Learning Methods for Computer Vision
Non-adversarial robustness, also known as natural robustness, is a prope...
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04/28/2023
Graph Neural Networks on Factor Graphs for Robust, Fast, and Scalable Linear State Estimation with PMUs
As phasor measurement units (PMUs) become more widely used in transmissi...
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03/01/2023
Supporting Future Electrical Utilities: Using Deep Learning Methods in EMS and DMS Algorithms
Electrical power systems are increasing in size, complexity, as well as ...
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02/28/2023
Scalability and Sample Efficiency Analysis of Graph Neural Networks for Power System State Estimation
Data-driven state estimation (SE) is becoming increasingly important in ...
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02/16/2023
GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow
The Gaussian Process (GP) based Chance-Constrained Optimal Power Flow (C...
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07/23/2022
Distributed Nonlinear State Estimation in Electric Power Systems using Graph Neural Networks
Nonlinear state estimation (SE), with the goal of estimating complex bus...
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07/22/2022
Near Real-Time Distributed State Estimation via AI/ML-Empowered 5G Networks
Fifth-Generation (5G) networks have a potential to accelerate power syst...
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06/06/2022
Robust and Fast Data-Driven Power System State Estimator Using Graph Neural Networks
The power system state estimation (SE) algorithm estimates the complex b...
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01/11/2022
