Dr. Raed Alotaibi
Ph.D. in Electrical and Computer Engineering | Oakland University
Raed Alotaibi completed doctoral research at Oakland University under Mohamed Zohdy. His dissertation investigates how deep reinforcement learning can support the restoration of power distribution systems after disasters. The work coordinates distributed energy resources while accounting for operating constraints and restoration priorities.
Doctoral research (2026): Resilience Enhancement of Post-Disaster Power Distribution Systems Using Deep Reinforcement Learning
Research & Publications
2 verified research records · Newest first
Selected publications and doctoral research records. This list may not include every publication.
Resilience Enhancement of Post-Disaster Power Distribution Systems Using Deep Reinforcement Learning
View Doctoral Record ↗Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
Optimizing Distributed Energy resource Integration using deep reinforcement learning for Post-Disaster Recovery
View Publication ↗Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
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