Academic Credentials
  • Ph.D., Mechanical Engineering, Michigan Technological University, 2017
  • M.S., Mechanical Engineering, K.N. Toosi University of Technology, Iran, 2012
  • B.S., Mechanical Engineering, K.N. Toosi University of Technology, Iran, 2010
Academic Appointments
  • Assistant Research Scientist, Department of Naval Architecture & Marine Engineering, University of Michigan, Ann Arbor, MI USA, 2019-2023
Professional Honors
  • Best Paper Award, 2022, Internal Short Circuit Detection for Parallel-Connected Battery Cells Using Convolutional Neural Network, Journal of Automotive Innovation, Springer.
  • Best Paper Award Finalist, 2022, Automotive and Transportation Systems Technical Committee, American Control Conference, Atlanta, GA, USA
  • Ph.D. Finishing Fellowship, 2017, Michigan Tech. University, Houghton, MI, USA
Professional Affiliations
  • Institute of Electrical and Electronics Engineers (IEEE) - Automotive Controls Technical Committee, 2017 – Current
  • The American Society of Mechanical Engineers (ASME) - Automotive and Transportation Systems Technical Committee, 2016 - Current
  • The American Society of Mechanical Engineers (ASME) - Energy Systems Technical Committee, 2016 - Current

Dr. Amini offers his clients a robust and diverse expertise in vehicle engineering, supported by over a decade of experience in the automotive industry and academia. He specializes in the development and evaluation of advanced driver assistance systems (ADAS), connected and automated vehicles (CAV), and battery management technologies for electric vehicles (EVs) and other battery powered devices. Dr. Amini has hands-on experience, from research and development to production, verification, and validation, and deep understanding of automotive control algorithm software and hardware. Additionally, he has expertise in artificial intelligence and machine learning, which are integral to the development and assessment of emerging vehicle technologies and critical for diagnosing and prognosticating potential safety-critical vehicle faults and malfunctions.

Prior to joining Exponent, Dr. Amini was a technical specialist at Stellantis focused on battery control and estimation algorithms, contributing to the development of software-defined EV platforms with stringent safety and reliability functional requirements. At Ford Motor Company's Research and Advanced Engineering department, he advanced cooperative adaptive cruise control and autonomous driving technologies. As a research scientist at the University of Michigan in Ann Arbor, he led multiple federally (Department of Energy, Office of Naval Research) and industry (Ford, Toyota) sponsored projects, pushing the boundaries of electrification and advanced automated driving technologies with a focus on enhancing vehicle safety and performance.

During his tenure at Ford, Dr. Amini conducted and led successful demonstrations that showcased the potential of infrastructure-informed cooperative adaptive cruise control (CACC) for connected vehicles. He played a crucial role in the design and integration of cutting-edge control algorithms that were instrumental in fostering cooperative driving capabilities, thereby transforming connected vehicle ecosystems. His efforts were pivotal in setting new benchmarks for safety and enhancing the overall comfort of the driving experience.

In a partnership between the University of Michigan and Ford between 2018 to 2023, Dr. Amini harnessed the power of machine learning to develop and create patents for innovative methods in electric vehicle (EV) range and speed prediction. Leveraging real-world traffic data, his research yielded a 20-30% improvement in the accuracy of EV range estimations. The predictive algorithms he developed not only optimized driving range but also amplified fast-charging efficiency and reduced energy consumption for electrified vehicles. These advancements were substantiated through comprehensive simulations and rigorous road tests.

Dr. Amini's academic journey culminated in a Ph.D. in Mechanical Engineering from Michigan Tech in 2017. His research in system dynamics and control, electrified mobility, intelligent transportation, and energy storage systems has yielded over 50 peer-reviewed articles and patents. Dr. Amini is a member of the Transportation and Automotive Controls Technical Committees within IEEE and ASME, where he has been instrumental in organizing and chairing numerous technical sessions and panels at internationally recognized conferences on emerging vehicle technologies since 2017.