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Narges Taran
Electric Machines Research Engineer at Ford Motor Company
About
Narges Taran is an accomplished Electric Machines Research Engineer with a demonstrated history of working in the automotive industry. She has a special interest in enabling practical solutions for computationally expensive problems. Narges is highly skilled in Transportation Electrification, High Performance Electric Machines, Stochastic and Evolutionary Optimization Algorithms, Multi-physics and multi-disciplinary Design, Design of Experiments, Response Surface Methodology, Meta Models, Kriging Surrogate Models, and exploring Innovative Electric Machine Design Paradigms. Currently, Narges is working as a Research Engineer, Electric Machines at Ford Motor Company, where she designs electric machines and contributes to the development of advanced electric powertrain technologies. Prior to this, she worked as a Sr. Engineer, Electric Machine Design at BorgWarner, where she designed electric machines and conducted performance analysis using finite element analysis (FEA) tools. Narges holds a Doctor of Philosophy - PhD in Electrical Machines and Drives from the University of Kentucky, where she conducted research on multi-objective optimization of electric machines using stochastic and evolutionary algorithms. She also holds a Master of Science - MS in Electrical Machines and Power Electronics from K. N. Toosi University of Technology. Narges is a Research Scientist with 3.35 years of relevant experience. She is passionate about designing innovative electric machines that can contribute to the development of sustainable transportation solutions. Narges is a team player with excellent communication and interpersonal skills. She is always eager to learn and explore new technologies and techniques that can help her design better electric machines.
Education Overview
• university of kentucky
• k. n. toosi university of technology
Companies Overview
• ford
• borgwarner
• university of kentucky
• researcher at k. n. toosi university of technology
Experience Overview
4.7 Years
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