Gregory Duthé

Additional information

Gregory holds Bsc (2017) and MSc (2019) degrees in Mechanical Engineering from EPFL. During his MSc, he specialized in fluid mechanics and machine learning, with an additional focus on energy systems. For his Master thesis, Gregory worked on using deep learning methods to predict wind flow over complex terrain for use on UAVs at ETH’s Autonomous Systems Lab.

Currently, Gregory is a Ph.D. candidate at the Chair of Structural Mechanics and Monitoring at ETH Zürich, working on the SNSF Bridge-funded project AeroSense: a novel MEMS-based surface pressure and acoustic IoT measurement system for wind turbines. This project is a collaborative effort between the Chair of Structural Mechanics and Monitoring, Windenergie@OSTcall_made and ETH’s Center for Project-Based Learning.

His research will focus on the development of deep learning learning tools that process aerodynamic data to provide information on the status of a wind turbine structure.