Sajjad Mohammadi
Contact
Assistant Professor, Faculty of Engineering - Electrical & Computer Engineering Dept
Overview
Area of Study / Keywords
Electric Machines Power Magnetics Power Electronics Motor Drives Control Systems Electric Vehicles Renewable Energies Energy Systems
About
Sajjad Mohammadi is an assistant professor at the Department of Electrical and Computer Engineering. He received the B.S. degree from Kermanshah University of Technology, Kermanshah, Iran, in 2011, and the M.S. degree from Amirkabir University of Technology, Tehran, in 2014, all in electrical engineering. He also received the M.Sc. and Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, in 2018 and 2021, respectively.
Previously, he was with Apple Inc., and was a Postdoctoral Fellow at MIT. He is a coauthor of the textbook Electromagnetic Analysis of Electric Machines: First Principles, Modeling, and Design (Wiley–IEEE Press, 2025). His research interests include electromechanical energy conversion, electric machines, power magnetics, and power electronic drives. He is the recipient of several awards, including the 2022 George M. Sprowls Outstanding PhD Thesis Award from the Department of Electrical Engineering and Computer Science at MIT, Best M.Sc. Thesis Awards, and awards in robotics and Chem-E-Car competitions.
Research
I am accepting PhD students and postdoctoral fellows to join my research group in the following areas to advance the development of next-generation power and energy systems:
Electromechanical Devices and Power Electronic Drives
Multidisciplinary research on novel electric machines, motor drives, and actuators with an emphasis on the integrated design of magnetics, electronics, controls, thermal management, and structural dynamics, with applications in transportation electrification, energy storage systems, renewable energy, robotics, medical devices, and semiconductor manufacturing technologies.Power Magnetics
More accurate modeling and characterization techniques along with innovative designs for magnetic components in power electronic converters with higher power density and efficiency, with applications in high-frequency power converters, vertical power delivery systems for AI, and related areas.Physics-Informed AI
Combining physics-based analytical modeling with data-driven AI/ML/NN approaches for the modeling, design, optimization, and characterization of motor drives and power magnetics.
If you are interested and have a strong theoretical background along with hands-on experience in any of the above areas, please consider applying to our graduate program. You may also send me your CV along with relevant information.
Courses
ECE 432 - Variable Speed Drives
Introduction to variable speed drives. Frequency, phase and vector control of induction motors. Dynamic models for induction motors. Permanent magnet synchronous and brushless dc motor drives. Prerequisite: ECE 332 or E E 332. Credit may be obtained in only one of ECE 432 or E E 432.