D. (Deepali) Singh MSc

D. (Deepali) Singh MSc



Deepali is a Ph.D. student in the wind energy/ aerodynamics group at TU Delft, supervised by Dr. Richard Dwight. She holds a Master’s degree in Aerospace Engineering from ISAE-Supaero, Toulouse, with majors in advanced fluid dynamics and turbulence modeling. During and after graduation, the primary focus of her research was on the Lattice Boltzmann method (LBM). She worked for over four years at Dassault Systemes and Safran Group on high-fidelity LBM simulations of a vast range of aerodynamic, aerothermal, and aeroacoustic problems in commercial aviation. She is an early-stage researcher in the STEP4WIND project (https://step4wind.eu/), a European industrial doctorate program granted under the H2020 Marie-Curie ITN initiative. She uses state-of-the-art machine learning methods to build reliable data-driven surrogates for floating offshore wind turbines. She is currently interested in Bayesian models that form a powerful, data-efficient, and flexible statistical framework for stochastic surrogate modeling. 
She is an avid reader (https://www.goodreads.com/user/show/50624503-deepalisings ) and enjoys painting, creating, traveling, and being in nature.


probabilistic machine learning, generative models, floating wind, lattice Boltzmann method, CFD


2014-2016: ISAE-MBDA programme of excellence for India scholarship

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  • 2022-2-25

    PhD Academic Event Poster Prijs

    Op 25 februari was de faculteit het toneel van het succesvolle PhD Academic Event. Naast alle presentaties en netwerk mogelijkheden werd er ook een posterprijs uitgereikt. Dit jaar won Deepali Singh, een van de STEP4WIND-promovendi, deze prijs voor haar werk aan probabilistische surrogaatmodellen voor de emulatie van drijvende windturbines. Onder supervisie van Dr. Richard Dwight en Dr. Axelle Viré, en in samenwerking met Siemens Gamesa Renewable Energy, helpt Singh zowel technologische als economische uitdagingen aan te gaan met betrekking tot de ontwikkeling van drijvende offshore windparken.