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Research Staff

Aymeric Rousseau

Aymeric Rousseau is the Manager of the Systems Modeling and Control Section at Argonne National Laboratory. He received his engineering diploma at the Industrial System Engineering School in La Rochelle, France in 1997. After working for PSA Peugeot Citroen in the Hybrid Electric Vehicle research department, he joined Argonne National Laboratory in 1999 where he overviews the development of Autonomie and POLARIS. He received an R&D100 Award in 2004 and a 2010 Vehicle Technologies Program R&D Award in 2010. He has authored or co-authored more than 75 technical papers in the area of advanced vehicle technologies.

Dominik Karbowski

Dominik Karbowski received a Master’s degree in Science and Executive Engineering with a major in Energy Systems from Mines ParisTech, France, in 2006. At Argonne, Dominik works on modeling advanced powertrains such as hybrids or plug-in hybrids, both light- and heavy-duty. He focuses his research on vehicle level control optimization and powertrain design optimization.

Namdoo Kim

Namdoo Kim graduated in 2007 from the University of Sungkyunkwan, Korea, with a Master’s degree in Mechanical Engineering. At Argonne, Namdoo has been working on modeling and control of multi-mode power split configurations.

Pierre Michel

Pierre Michel received his Ph.D. from the University of Orleans, France in 2015. His doctoral work focused on optimal control theory applied the energy management of Hybrid Electric Vehicles. Pierre joined Argonne in June 2015 and his current research focuses on the control and energy analysis of electrified connected and automated vehicles.

Ayman Moawad

Ayman Moawad is a research engineer in the Systems Modeling and Control section at Argonne National Laboratory. He graduated from the Ecole des Mines de Nantes, France, in 2009 with a Master of Science in Mechatronics, Robotics, and Computer Science. His research interests include analyzing the energy consumption of light-duty Hybrid and Electric drive vehicles, developing Large Scale Simulation Processes involving High Performance Computing, as well as predicting trends and performing Quality Assurance on big data using Statistical and Machine Learning techniques. His research supports the U.S. Department of Energy Vehicle Technology Office, the U.S Department of Transportation and the National Highway Traffic Safety Administration.

Sylvain Pagerit

Sylvain Pagerit is a senior software developer and research engineer in the Vehicle Modeling and Simulation group at Argonne National Laboratory. He received a Master of Science in Automatics, Control Systems and Industrial Engineering from the Ecole des Mines de Nantes, France, in 2000, as well as a Master of Science in Electrical and Computer Engineering from the Georgia Institute of Technology, Atlanta, in 2001. At Argonne, he focuses his work on the development of system simulation tools, originally for PSAT and now Autonomie, as well as managing the group development environment. For the last 10 years, he also setup and manage High Performance Computer (HPC) clusters and design tools to facilitate and optimize system simulations on HPCs. He received a patent and several awards for his work on Autonomie and PSAT.

Phillip Sharer

Phillip Sharer is the Principal Investigator behind the Autonomie Process Architecture. He wrote the Automated Model Building Algorithm and authored the XML Argonne Model Descriptor Specification (XAMDS). He has been a Research Engineer at Argonne for 11 years. During this time, he also co-authored the Powertrain Systems Analysis Toolkit (PSAT).  He received a Master of Science in Engineering degree from Purdue University Calumet.

Ram Vijayagopal

Ram Vijayagopal graduated from the University of Michigan in 2008 with a Master’s degree in Mechanical Engineering. He is currently working in Argonne National Laboratory’s Vehicle Modeling and Simulation group, where he is involved in the development of Autonomie. Before Argonne, he worked at Hitachi developing low level motor control algorithms for hybrid electric vehicles.


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