Daniel Mercier is a Principal Research Engineer at Autodesk Research and a member of the Computational Science Research group. Daniel acts as project manager as well as field researcher. Daniel technical expertise is in numerical simulation, system engineering and machine intelligence; which he combines with his expertise from education in process engineering, material sciences and manufacturing.
Daniel is currently driving research and development in semantic-based machine intelligence to facilitate user interactions with Autodesk solutions.
Daniel joined Autodesk Research in 2014 after collaborating with the group over a two years period on the building of Autodesk first optimization platform for simulation. Daniel joined the Dreamcatcher initiative as acting Dev Ops manager. In this role, Daniel formalized development practices and drove the development of the infrastructure used by the team of researchers. During this period, Daniel also contributed to the creation of Autodesk cloud infrastructure. His role changed in June 2017 to focus on machine intelligence.
Before joining Autodesk Research in Toronto, Canada, Daniel worked on numerical solvers within Autodesk simulation group in Melbourne, Australia. His work focused on improving solver performances and parallel computations. Notably, Daniel led the development of Autodesk Moldflow current optimization solution. During his time in Australia, Daniel also provided training to the Asia-Pacific sales and support workforce on Autodesk simulation solutions and contributed as technical expert to sales over the Australian territory.
Partners: Hong Kong University of Science and Technology, Concordia University, Université Laval, University of Toronto
Background / CV
French / Australian
- Bachelor and master in Process Engineering from Mines School in Albi, France
- PhD in Mechanical engineering from Lehigh University, Pennsylvania, USA
- PhD in Material Sciences from Mines School in Paris, France
Note: Fulfilled requirements for a PhD in Applied Mathermatics.
- Open Source Jenkins plugin to track the evolution of scalar values between Jenkins builds. Ref: https://plugins.jenkins.io/benchmark
661 University Ave
Toronto, ON M5G 1M1