Directory profile for Dr. John O’Donnell

Picture of Dr. John O’Donnell
Contact
  • 276 Hardaway Hall
  • Phone (205) 348-5779
  • Email
Request a Directory Profile Update

Dr. John O’Donnell

Teaching Assistant Professor

Contact

  • 276 Hardaway Hall
  • phone (205) 348-5779
  • Email

Education

  • Ph.D., Mechanical Engineering, The University of Alabama, 2023
  • M.S., Mechanical Engineering, The University of Alabama, 2016
  • B.S., Mechanical Engineering, The University of Alabama, 2013

John O’Donnell is an assistant professor in the Department of Mechanical Engineering. His work focuses on the development of methods to predict and characterize continuous, multi-modal failure states as well as the application of artificial intelligence techniques in engineering design, prototyping, optimization, and manufacturing. Prior to joining The University of Alabama, he pursued postdoctoral work in the Engines and Combustion Lab as part of the University’s Center for Advanced Vehicle Technology, where his work explored real-time combustion optimization and engine control development utilizing artificial intelligence. He employs a wide range of techniques including data-driven methods such as machine learning, deep learning, reinforcement learning, generative AI, and large language models as well as techniques such as linear controls and nonlinear controls.

Affiliated Areas
Mechanical Engineering

Selected Publications

  • O’Donnell, J., and Yoon, H. (August 14, 2023). “Determination of Multi-Component Failure in Automotive System Using Deep Learning.” ASME. J. Comput. Inf. Sci. Eng. February 2024; 24(2): 021005. https://doi.org/10.1115/1.4063003
  • Zargarani, A., O’Donnell, J., and Mahmoodi, S. N. (February 21, 2022). “Coupled Flexural–Torsional Forced Vibration Analysis of a Piezoelectrically Actuated Double-Cantilever Structure.” ASME. J. Vib. Acoust. August 2022; 144(4): 041004. https://doi.org/10.1115/1.4053714
  • O’Donnell, J., and Yoon, H. (May 26, 2020). “Determination of Time-to-Failure for Automotive System Components Using Machine Learning.” ASME. J. Comput. Inf. Sci. Eng. December 2020; 20(6): 061003. https://doi.org/10.1115/1.4046818

The University of Alabama     |     Lee J. Styslinger Jr. College of Engineering