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Home » Faculty/Staff Directory » Faculty Profile » Getachew Ambaye
Getachew Ambaye

Getachew Ambaye

Assistant Professor

Engineering Technology

 

PhD in Industrial Engineering  - Wichita State University

MSc. in Mechanical System Design Engineering - Jimma Institute of Technology

BSc. in Mechanical Engineering - Jimma Institute of Technology

An educator and researcher focused on soft robotics, intelligent manufacturing, and applied machine learning. Research integrates finite element analysis, mechanical design, and AI to develop advanced robotic systems, with contributions in soft actuator modeling, machine vision, and vibration-based fault detection.

Engages in innovative engineering education through hands-on, simulation-driven, and immersive learning environments. Work includes developing virtual labs, hydraulic and electro-pneumatic simulators, and VR-based experiences, while advancing research in digital twins and smart sensing to connect theory with real-world engineering applications.

Soft robotics and compliant mechanisms; finite element modeling and simulation of flexible systems; machine learning and AI for robotics and manufacturing; digital twins and virtual prototyping;  machine vision and defect detection; structural health monitoring and vibration-based diagnostics; electro-pneumatic and hydraulic system simulation; and immersive engineering education using VR/AR technologies.

  • Ambaye, G., Boldsaikhan, E., & Krishnan, K. (2025). Soft Robot Workspace Estimation via Finite Element Analysis and Machine Learning. Actuators, 14(3), 110. https://doi.org/10.3390/act14030110

  • Ambaye, G., Boldsaikhan, E., & Krishnan, K. (2025). Detecting misalignments of drilled holes using machine vision. In Sustainable Development Research in Manufacturing, Process Engineering, Green Infrastructure, and Water Resources: Advancement of Science and Technology (pp. 17-30). Cham: Springer Nature Switzerland.

  • Ambaye, G., Boldsaikhan, E., & Krishnan, K. (2024). Soft Robot Design, Manufacturing, and Operation Challenges: A Review. Journal of Manufacturing and Materials Processing, 8(2), 79. https://doi.org/10.3390/jmmp8020079

  • Ambaye, G., Boldsaikhan, E. & Krishnan, K. Robot arm damage detection using vibration data and deep learning. Neural Comput & Applic 36, 1727–1739 (2024). https://doi.org/10.1007/s00521-023-09150-3

  • Ambaye, G., Krishnan, K., & Boldsaikhan, E. (2023, October). Detection of small screws using machine learning. In 2023 International conference on information and communication technology for development for Africa (ICT4DA) (pp. 13-18). IEEE.

  • Ambaye, G. A., Lemu, H. G., & Tolcha, M. A. (2022). Contact temperature analysis of the classical Geneva mechanism through numerical methods. Materials Today: Proceedings, 57, 545-552.

  • Ambaye, G. A., & Lemu, H. G. (2021). Dynamic analysis of spur gear with backlash using ADAMS. Materials Today: Proceedings, 38, 2959-2967.

  • Ambaye, G. A., & Lemu, H. G. (2021, October). Numerical stress analysis and fatigue life prediction of the classical external Geneva mechanism. In International workshop of advanced manufacturing and automation (pp. 176-186). Singapore: Springer Singapore.

  • Ambaye, G. (2021). The performance of gear with backlash: A review. Journal of Applied Mechanical Engineering, 10(9), 389.

  • Ambaye, G. A. (2021). Determination of Important Contact Parameters for Spur Gear Design. TechHub Journal, 1(1), 28-38.

  • Ambaye, G. A., & Lemu, H. G. (2020, October). Effect of backlash on transmission error and time varying mesh stiffness. In International Workshop of Advanced Manufacturing and Automation (pp. 18-28). Singapore: Springer Singapore.

  • Ambaye, G. A., & Lemu, H. G. (2020). Numerical study of effect of backlash on flash temperature of spur gear. International Review of Mechanical Engineering, 14(11), 684-692.

  • Ambaye, G. A. Numerical Comparative Modal Analysis of Connecting Rod between Fixed Crankpin and Fixed Piston Pin.

  • Ambaye, G. A. (2020). Time and frequency domain analysis of signals: a review. Int. J. Eng. Res. Technol, 9(12), 271-276.

  • Best Paper Award in EAI ICAST 2023: Detecting Misalignments of Drilled Holes using Machine Vision

  • GOVingTuesday25, Austin Peay State University, $3,570.