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Satya Akundi

Satya Aditya Akundi

  • Assistant Professor, Industrial & Manufacturing Engineering

Dr. Akundi's primary research is in complex systems engineering, including Model-based Systems Engineering, Cyber-Physical Systems, and Digital Quality Control. He also pursues research in engineering education. Akundi's research is funded by the National Science Foundation (NSF), the U.S. Department of Education (DoEd), and industry.

Education

  • PhD, Electrical and Computer Engineering, Industrial and Systems Engineering Track, University of Texas at El Paso, 2016
  • Graduate Certificate, 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

Research Interests

  • Systems Engineering
  • Model based Systems Engineering
  • Digital Engineering
  • Workforce Development
  • Cyber Physical Systems

Publications

Google Scholar Link

  • Akundi, Aditya, et al. "State of Industry 5.0—Analysis and identification of current research trends." Applied System Innovation 5.1 (2022): 27.
  • Lopez, Viviana, and Aditya Akundi. "Modeling A UAV Surveillance Scenario-An Applied MBSE Approach." 2023 IEEE International Systems Conference (SysCon). IEEE, 2023.
  • Mandapaka, S., Diaz, C., Irisson, H., Akundi, A., Lopez, V., & Timmer, D. (2023, April). Application of Automated Quality Control in Smart Factories-A Deep Learning-based Approach. In 2023 IEEE International Systems Conference (SysCon) (pp. 1-8). IEEE.
  • Akundi, A., & Mondragon, O. (2022). Model based systems engineering—A text mining based structured comprehensive overview. Systems Engineering, 25(1), 51-67.
  • Hossain, N. U. I., Lutfi, M., Ahmed, I., Akundi, A., & Cobb, D. (2022). Modeling and Analysis of Unmanned Aerial Vehicle System Leveraging Systems Modeling Language (SysML). Systems, 10(6), 264.
  • Akundi, A., Ankobiah, W., Mondragon, O., & Luna, S. (2022, April). Perceptions and the extent of Model-Based Systems Engineering (MBSE) use–An industry survey. In 2022 IEEE International Systems Conference (SysCon) (pp. 1-7). IEEE.
  • Lopez, V., & Akundi, A. (2022, April). A conceptual model-based systems engineering (mbse) approach to develop digital twins. In 2022 ieee international systems conference (syscon) (pp. 1-5). IEEE.
  • Akundi, A., Mondragon, O., Ortiz, M., Tseng, B., Luna, S., & Lopez, V. (2022, April). Online Model-based Systems Engineering (MBSE) Bootcamp: A Report on Two Day Workforce Development Workshop. In 2022 IEEE International Systems Conference (SysCon) (pp. 1-6). IEEE.
  • Akundi, A., Tseng, T. L. B., Almeraz, C. N., Lopez-Terrazas, R. J., & Luan, H. (2021, April). A novel approach to behavior design for model based systems engineering application using design structure matrix. In 2021 IEEE International Systems Conference (SysCon) (pp. 1-7). IEEE.
  • Akundi, A., & Smith, E. (2021). Quantitative Characterization of Complex Systems—An Information Theoretic Approach. Applied System Innovation, 4(4), 99.
  • Akundi, A., & Lopez, V. (2021). A review on application of model based systems engineering to manufacturing and production engineering systems. Procedia Computer Science, 185, 101-108.
  • Akundi, A., & Reyna, M. (2021). A machine vision based automated quality control system for product dimensional analysis. Procedia Computer Science, 185, 127-134.
  • Akundi, Aditya, et al. "Text mining to understand the influence of social media applications on smartphone supply chain." Procedia Computer Science 140 (2018): 87-94.

Community Involvement

  • American Society for Engineering Education (ASEE), Executive board of the ASEE Manufacturing Division
  • Institute of Industrial and Systems Engineers (IISE). Committee Member-IISE Cup

Awards

  • Recipient of numerous awards, including the outstanding junior faculty award and an award for his service to the manufacturing profession from the ASEE Manufacturing division