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
Education
- Ph.D. in Electrical and Computer Engineering — Oakland University, 2026
Research statistics
Verified ICCC collection
- Documented research records
- 2
- Publication records
- 1
- Degree research records
- 1
Indexed citation figures
- Indexed research works
- 1
- Citations to indexed works · all years
- 0
- Citations received · 2024–2026
- 0
- 20240
- 20250
- 20260
Annual citations: 2024: 0 · 2025: 0 · 2026: 0. Retrieved 2026-10-28. Work 1Checked 2026-10-28Verified publication only; not a complete career total. Degree theses in ICCC are counted separately. An author profile is not required to report this paper’s indexed citations.
ICCC counts cover the verified collection. Citation figures cover only the displayed indexed source records, not guaranteed career totals. OpenAlex coverage and author clustering can be incomplete. These figures differ from Google Scholar and include self-citations. Compare available member metrics →
Research & Publications
1 publications · 1 degree thesis · Newest first
Authored and co-authored publications, with authors shown in the source order. This list reflects the records currently verified by ICCC and may not be complete.
Resilience Enhancement of Post-Disaster Power Distribution Systems Using Deep Reinforcement Learning
View DissertationStart 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 PublicationOpenAlex: 0 citations Source ↗
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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