Chiara Fusar Bassini

Chiara Fusar Bassini is a PhD candidate and research associate at the Hertie School’s Center for Sustainability and Data Science Lab in Berlin, Germany. Her research focuses on applying machine learning methods to analyze European energy data, particularly time-series data from grid operators to identify bottlenecks in the renewable energy transition. She holds a Master of Science in Scientific Computing from the Technical University of Berlin and a Bachelor of Science in Economics, Management, and Computer Science from Bocconi University. Under the supervision of Prof. Lynn Kaack and collaborating with Prof. Priya Donti at MIT’s Laboratory for Information and Decision Systems (LIDS), she explores optimizing energy systems through robust machine learning approaches.

Chiara’s academic background combines economics, computer science, and applied mathematics, supported by professional experience in the energy sector. Her work addresses challenges in energy market designs, aiming to enhance sustainability and resilience. She is currently engaged in a research stay at MIT, where she investigates how machine learning can improve electricity market incentives and operational efficiency.

Her research interests span data-driven solutions for energy systems, renewable integration, and future market design innovations. Chiara is actively involved in various academic events, including the 2025 DACH+ Conference on Energy Informatics and the Summer School on Sustainable Energy Markets & Optimization.

Chiara’s interdisciplinary approach bridges technical and economic aspects of energy systems, leveraging her expertise in machine learning and policy-relevant analysis. She contributes to initiatives like the Hertie School’s Policy Lab and collaborates with institutions such as MIT’s LIDS, fostering international research networks to advance sustainable energy solutions.