Daniel Mercier is a Principal Research Engineer at Autodesk Research and a member of the Computational Science Research group. Daniel joined Research in 2014 after collaborating with the group over two years on process optimization. His research interests include simulation, automated systems, data processing, graphical representations, highly dispersed computing, machine learning and AI.
Before joining Autodesk Research, Daniel worked for Autodesk in Australia for the simulation group. His work initially involved improving solver technologies; but progressively, with the growth towards cloud computing, moved to optimization solutions. He was the architect for the current optimization solver inside Autodesk Moldflow.
Daniel received his bachelor in Process Engineering from Mines School in Albi, France; and his PhD in Mechanical Engineering from Lehigh University, Pennsylvania, USA. While his education was focused on mechanical and process engineering, he spent most of his PhD implementing Applied Mathematics to process simulation and data processing.
In his spare time, Daniel enjoys playing guitar, likes hiking, scuba diving and martial arts.
Partners: Hong Kong University of Science and Technology, Concordia University, Université Laval, University of Toronto
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