Nikolai Demydov

Spearheading the deployment of artificial intelligence in energy management systems (EMS) and advanced distribution management systems (ADMS+DERMS) to heighten capabilities and enhance operational efficiency in grid management:

• Pioneering the integration of sophisticated AI analytics across descriptive, predictive, and prescriptive models to advance the operational intelligence of grid systems.
• Leading the implementation of cutting-edge deep learning technologies, such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), and reinforcement learning models including Soft Actor-Critic (SAC) and Deep Deterministic Policy Gradient (DDPG), to refine the performance of grid management software.
• Driving the incorporation of Machine Learning Operations (MLOps) into Continuous Integration/Continuous Deployment (CI/CD) practices into o ensure continuous training and efficient management of machine learning models.