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Lesia Mitridati is an Assistant Professor specializing in Energy Markets Analytics. She actively contributes to research topics related to the United Nations Sustainable Development Goals, specifically focusing on the optimization of energy systems through machine learning and data-driven methodologies. Her expertise spans across various projects involving AI-powered electricity markets and the design of ancillary services. Lesia supervises several PhD students, guiding them in innovative projects that leverage machine learning for market-based operation in virtual power plants and other renewable energy systems. Through her role, she undertakes significant responsibility in organizing academic events, including annual summer schools focused on technical and economic challenges in power systems. Her academic endeavors contribute towards new strategies in making energy systems more efficient and sustainable, addressing both technical and societal aspects of energy transition.
Technical University of Denmark • Kgs. Lyngby, Denmark
Specializing in Energy Markets Analytics.
This requirement applies generally across Technical University of Denmark (DTU) MSc programs including Computer Science, Applied Mathematics, and Engineering disciplines. Specific prerequisites vary by department/curriculum.