- M.S., Data Science, Northwestern University, 2020
- Ph.D., Materials Science and Engineering, McMaster University, Canada, 2013
- M.Sc., Materials Science, McMaster University, Canada, 2009
- M.Sc., Materials Science, Iran University of Science and Technology, 2006
- B.Eng., Industrial Metallurgy, Imam Khomeini International University, 2004
- PGSD NSERC Scholarship, 2010
- Stelco-McMaster Graduate Fellowship, 2009
Dr. Panahi specializes in materials science with specific expertise in physical metallurgy, material characterization, and microstructural-property relationships of metals. He has extensive experience in product development, industrialization, process optimization and failure mode and effects analysis (process and design FMEA) of advanced high strength steels.
Dr. Panahi is also specialized in data science and analytics management. He leverages his skills to optimize and accelerate product development cycles and customer support activities through data management and development of advanced machine learning and optimization algorithms.
Prior to joining Exponent, Dr. Panahi worked as a Senior Research Engineer at ArcelorMittal global research and development center, where he led multiple projects related to design and industrialization. His areas of focus were on fundamental metallurgical investigation on processing-microstructure-property relationship of complex steel chemistries for improving cold formability, surface quality, weldability, and robustness of new high strength steels for automotive structural components. Under Dr. Panahi's leadership, several 3rd generation steels were developed for major automotive manufacturers through collaboration with different production lines across the world.
Prior to joining ArcelorMittal, Dr. Panahi completed his Ph.D. in materials science at McMaster University, where he studied effect of alloying element segregation into interphase boundaries on kinetics of phase transformations in steels. His fundamental research led to development of an atomistic physically based model for accurate prediction of austenite to ferrite transformation in steels.
While working at ArcelorMittal, Dr. Panahi completed another MSc. degree in data science and analytics management from Northwestern University in Chicago, IL. As a domain expert in materials science, he used his data science knowledge to bridge between the two disciplines and accelerate new material development, optimization and characterization processes through data management, and machine learning techniques.
Dr. Panahi is author of several US and international patents, book chapters, and peer-reviewed journal papers. He has delivered presentations at international conferences, and instructed undergraduate courses related to metal forming and phase transformations.