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Doctor of Engineering (D.Eng.), Electrical and Computer Engineering, University of Michigan –
Dearborn
Master of Business Administration (MBA), University of Michigan – Ann Arbor
Master of Science (M.S.), Electrical Engineering, University of Michigan – Dearborn
Bachelor of Science (B.S.), Electrical Engineering, University of Michigan – Ann Arbor
Bachelor of Science (B.S.), Physics, University of Michigan – Ann Arbor

1. O’Donnell, J.; Su, W. Attention-Focused Machine Learning Method to Provide the Stochastic Load
Forecasts Needed by Electric Utilities for the Evolving Electrical Distribution System. Energies 2023,
16, 5661, doi:10.3390/en16155661
2. O’Donnell, J.; Su, W. A Stochastic Load Forecasting Approach to Prevent Transformer Failures and
Power Quality Issues Amid the Evolving Electrical Demands Facing Utilities. Energies 2023, 16,
7251, doi:10.3390/en16217251.
3. Sharma, S.; O’Donnell, J.; Su, W.; Mueller, R.; Roald, L.; Rehman, K.; Bernstein, A. Engineering
Microgrids Amid the Evolving Electrical Distribution System. Energies 2024, 17, 4764.
https://doi.org/10.3390/en17194764
4. Gaurish S. Gokhale, Bruce A. Mork, John O’Donnell, Steven R. Brehmer Ferroresonance case study
in a distribution network and the potential impact of DERs and CVR/VVO, Electric Power Systems
Research, Volume 220, 2023, 109303, ISSN 0378-7796.

2022 EPRI Technology Transfer Award for Microgrid Viability Analysis
Engineering Society of Detroit’s Outstanding Young Engineer of the Year in 2000