Dr. Aidibi earned his Ph.D. in Electrical & Computer Systems Engineering and dual M.S. degrees in Electrical & Computer Engineering and Embedded Systems from Oakland University, and his B.S. in Electrical & Computer Engineering from Lawrence Technological University.

With over 25 years of experience as a Principal Software Engineer and Technical Specialist in Embedded Software Engineering, Dr. Aidibi has led the development of real time embedded control software in both production and research environments. His career spans power electronics, EV fast charging, inverter control, automotive communication protocols, driver information and driver awareness systems with wide experience in signal processing, machine learning applications, and standards-based embedded system integration.

» Education

• Ph.D. in Electrical & Computer Systems Engineering, Oakland University
• M.S. in Electrical & Computer Engineering, Oakland University
• M.S. in Embedded Systems, Oakland University
• B.S. in Electrical & Computer Engineering, Lawrence Technological University

» Academic Teaching

Dr. Aidibi teaches undergraduate and graduate courses in areas including:

• Microprocessors & Embedded Systems Courses and Labs
• Digital Electronics Courses and Labs
• Real Time Systems, Digital Control Systems
• Electric Machines & Lab
• Computer Networking, Computer Architecture
• Data Structures I & II
• Circuits, Electronics & Lab, and Directed Study in Embedded Software Engineering

» Technical/Professional Focus & Competencies

• Expert guidance from proof of concept through production rollout
• Full stack embedded software architecture and development
• Hands on experience in power electronics system design and control
• Automotive communications protocols
• Modeling, simulation, debugging, quality control, and standards compliance
• Intelligent classification, signal transformation, and control systems

» Professional Experience

• Drive System Design: Technical Specialist
  • Design firmware for high-power DC–AC inverter systems.
  • Develop embedded software for high-power DC–AC inverters and motor control systems. Core responsibilities include real-time control algorithms, base modulation, and low-level driver implementation for FlexPWM, ADC, and CTU modules to enable synchronized signal acquisition and control execution.
  • Integrate and develop RTOS-based systems, real-time fault detection, communication, and diagnostic interfaces.
• BorgWarner: Senior Embedded Systems Software Engineer
  • Developed firmware for DC fast charging solutions compliant with DIN/ISO 15118, CHAdeMO, and GB/T protocols.
  • Implemented software control and dynamic power allocation for 120 kW / 60 kW flexible charging architecture, enabling load balancing between dual charge points to accommodate different vehicle capabilities and grid constraints.
  • Collaborated with the Global Product Development architecture team for designing and implementing real-time embedded systems on Linux-based and RTOS-based platforms, optimizing power flow control between DRB (Dispenser RTOS Board) and ROB (Rich OS Board).
• Lear Corporation: Principal Software Engineer
  • Designed and implemented fully digital DC–AC inverters, EV EVSE PLC integration (LwIP, GreenPHY, ISO 15118, CHAdeMO, GB/T), and rigorous electronic control features including hysteresis regulation, overcurrent/voltage protection, pre-charge/discharge algorithms, and power calculations.

» Research Statement

• Particularly interested in real-time embedded systems, power electronics, model-based development, embedded system security, and intelligent signal processing for adaptive control and diagnostics.
• Dr. Aidibi’s goal is to bridge practical engineering challenges with applied research, delivering robust, scalable solutions aligned with industry needs in electrification and automotive systems.
• Dr. Aidibi recent research has been in the area of Learning & Control Software with emphasis on utilizing Hybrid Dynamic Systems, Dynamic Programming and Approximate Dynamic Programming algorithms applications to Intelligent Transportation Systems (ITS). In this research, hybrid dynamic systems with shared interactions and performance between the hybrid states are considered as a multistage decision problem.