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Personal Profile

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Malik Hassanaly uses his expertise in statistical methods, machine learning, and computational fluid dynamics to develop more accurate and efficient numerical models. While obtaining his doctorate, Malik mostly worked on turbulent combustion applications with an emphasis on aircraft engines and continues to work on combustion-related topics. At NREL, he also works on manufacturing processes for solar cells, uncertainty quantification for weather prediction and battery modeling.

Research Interests

Design optimization

Data-assisted uncertainty quantification

Scientific machine learning

Multi-fidelity methods

Data reduction

Surface chemistry modeling

Anomaly detection/prevention

Professional Experience

Intern, R&D, Maia Eolis (2012–2013) 

Intern, Software Development, RTE (2012) 

Intern, Managing Solutions, Areva NP (2010)

Education/Academic Qualification

PhD, Aerospace Engineering, University of Michigan

Master, Aerospace Engineering, University of Texas at Austin

Master, General Engineering, École centrale de Lille

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