Carl holds a Ph.D in Mathematics from École des Ponts ParisTech and Université Gustave Eiffel in Paris. He has broad interests in statistics and stochastic control, and works on reinforcement learning, generative methods and time series forecasting, with applications in various domains such as energy, finance and physics. He worked with EDF R&D and Finance des Marchés de l’Energie (FiME) laboratory on applications of machine learning to risk management, including time series generation and deep hedging. He joined the SDSC in 2022 as a senior data scientist in the academic team at École Polytechnique Fédérale de Lausanne (EPFL).
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