معرفی
Satya Aditya Akundi is an Assistant Professor in the Department of Industrial & Manufacturing Engineering at the University of Wisconsin-Milwaukee (UWM), within the College of Engineering & Applied Science. His research focuses on complex systems engineering, including Model-Based Systems Engineering (MBSE), Cyber-Physical Systems, Digital Engineering, and Workforce Development. His work is supported by the National Science Foundation (NSF), U.S. Department of Education (DoEd), and industry partnerships. Dr. Akundi holds a PhD in Electrical and Computer Engineering from the University of Texas at El Paso and has a Graduate Certificate in Systems Engineering.
His research interests span systems engineering methodologies, digital transformation in manufacturing, and advancing educational strategies in engineering. He has published extensively on topics like MBSE applications in UAV systems, automated quality control using deep learning, and industry adoption trends of systems engineering practices. His work bridges theoretical frameworks with practical implementations, emphasizing interdisciplinary approaches.
- Education:
- PhD, Electrical and Computer Engineering (Industrial & Systems Engineering Track), University of Texas at El Paso (2016)
- Graduate Certificate in Systems Engineering, University of Texas at El Paso (2016)
- MS, Electrical and Computer Engineering, University of Texas at El Paso (2012)
- BS, Electronics and Communications Engineering, Jawaharlal Nehru Technological University (2009)
Dr. Akundi has been recognized with awards including the Outstanding Junior Faculty Award and an award for service to manufacturing education from the ASEE Manufacturing Division. He actively contributes to professional organizations like the Institute of Industrial and Systems Engineers (IISE) and the American Society for Engineering Education (ASEE).
His research portfolio reflects a balance between foundational systems engineering principles and applied industry challenges, with a strong emphasis on workforce development through workshops and educational initiatives. Recent work highlights include exploring Industry 5.0 trends, developing digital twins for manufacturing systems, and advancing automated quality control in smart factories.
