Ali A. Abushaiba
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Assistant Professor
Also affiliated: Southern Illinois University Carbondale (2014); University of Kansas (2016–2022); University of Arkansas System (2024)
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Ali A. Abushaiba's research interests include machine learning applications for industrial automation, with a focus on digital twin and edge AI integration. He has investigated real-time control applications through the integration of microcontrollers with simulation software, and studied sensorless control methods for permanent magnet synchronous motors using reduced-order observers. His work also encompasses a comparative evaluation of DC-DC converter topologies, particularly for electric vehicle chargers, and surveys reinforcement learning-based control in DC-DC converters.
Abushaiba collaborates with Kamran Iqbal and Md Farhan Shahrior at the University of Arkansas at Little Rock, with whom he shares multiple publications. His scholarly contributions are reflected in an h-index of 6 and over 111 citations across 11 publications.
Metrics
- h-index: 6
- Publications: 11
- Citations: 138
Positions
-
Assistant Professor publications 2025University of Arkansas at Little Rock Institution web page
Selected Publications
-
Reinforcement Learning-based Control in DC-DC Converters: A Survey (2025)
-
Comparative Evaluation of DC–DC Converter Topologies for Electric Vehicle Chargers (2025)
-
Enabling Intelligent Industrial Automation: A Review of Machine Learning Applications with Digital Twin and Edge AI Integration (2025)
-
Enabling Intelligent Industrial Automation: A Review of Machine Learning Applications with Digital Twin and Edge AI Integration (2025)
-
Integration of C2000 Microcontrollers with MATLAB Simulink Embedded Coder: A Real-Time Control Application (2024)
Collaboration Network
Top Collaborators
- Enabling Intelligent Industrial Automation: A Review of Machine Learning Applications with Digital Twin and Edge AI Integration
- Enabling Intelligent Industrial Automation: A Review of Machine Learning Applications with Digital Twin and Edge AI Integration
- Enabling Intelligent Industrial Automation: A Review of Machine Learning Applications with Digital Twin and Edge AI Integration
- Enabling Intelligent Industrial Automation: A Review of Machine Learning Applications with Digital Twin and Edge AI Integration
- Comparative Evaluation of DC–DC Converter Topologies for Electric Vehicle Chargers
- Reinforcement Learning-based Control in DC-DC Converters: A Survey
- Integration of C2000 Microcontrollers with MATLAB Simulink Embedded Coder: A Real-Time Control Application
Similar Researchers
Based on overlapping research topics