Ehsan Naderi
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
Also affiliated: Southern Illinois University Carbondale (2020–2023); Razi University (2016–2020); Tarbiat Modares University (2010–2012)
Research Areas
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Biography and Research Information
OverviewAI-generated summary
Ehsan Naderi's research focuses on power systems engineering, particularly in the areas of distribution system planning, optimal power flow, and energy management. His work has explored dynamic approaches for distribution system planning that incorporate distributed generation and energy storage systems. Naderi has investigated the application of optimization algorithms, including particle swarm optimization and hybrid evolutionary algorithms, to solve complex power system problems such as optimal power flow and reactive power dispatch.
His publications include studies on multi-objective dynamic distribution feeder reconfiguration and practical economic dispatch problems. Naderi has also examined novel approaches to energy management in distribution networks. He leads a research group and maintains an active lab website, indicating ongoing research activities. His scholarly output includes 71 publications with over 2,100 citations, and he holds an h-index of 24. Naderi is recognized as a highly cited researcher.
Metrics
- h-index: 24
- Publications: 69
- Citations: 2,163
Positions
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Assistant Professor 2023–presentArkansas State University Electrical Engineering ORCID
Selected Publications
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AI-Driven Automatic Fault Detection and Classification in Smart Microgrids (2026)
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Quantum-Accelerated Digital Twins for Cyber-Resilient Smart Power Systems Against False Data Injection Cyberattacks Using Bitcoin-Mining-Based Virtual Energy Storage Framework for Voltage Restoration (2026)
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Reimagining Bitcoin Mining as a Virtual Energy Storage Mechanism in Grid Modernization: Enhancing Security, Sustainability, and Resilience of Smart Cities Against False Data Injection Cyberattacks (2026)
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Smart Power for a Sustainable Future: Design and Performance Analysis of a Hybrid Renewable Energy Microgrid for Arkansas State University’s Engineering College (2025)
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Securing the future: Integrating quantum computing and digital twin technologies into modern power & transportation systems for resilient smart cities against false data injection cyberattacks (2025)
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Impact of Phase Current Sequencing in Machine Learning Models for Induction Motor Fault Detection (2025)
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Intelligent Remedial Action Scheme Against False Data Injection Cyberattacks Targeting Energy Justice and Equity in Modern Power Systems (2025)
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A Hybrid ML-Digital Twin Framework for Differentiating Cyberattacks from Legitimate Price Fluctuations in Electricity Markets (2025)
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Digital Twin-Enabled Resilient Network Reconfiguration for Cybersecurity of Decarbonized Power Distribution Systems (2025)
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A Remediation Framework Against False Data Injection Cyberattacks Targeting ULTC Transformers to Avoid Voltage Collapse in Smart Distribution Networks (2025)
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Mitigating Voltage Violations in Smart City Microgrids Under Coordinated False Data Injection Cyberattacks: Simulation and Experimental Insights (2025)
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Design of a Standalone Hybrid Renewable Energy System - A Hospital in Lafayette, Indiana, USA (2024)
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A Remedial Action Scheme Against False Data Injection Cyberattacks Targeting ULTC Transformers in Smart Distribution Systems (2024)
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Cyber-Physical Distribution Systems Resilience Against Cyberattacks via a Remediation Framework Based on Static VAR Compensators (SVCs) (2024)
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False Data Injection Cyberattacks Targeting Electric Vehicles in Smart Power Distribution Systems (2024)
Collaboration Network
Top Collaborators
- A Remedial Action Scheme To Mitigate Market Power Caused by Cyberattacks Targeting a Smart Distribution System
- Cyber-Physical Distribution Systems Resilience Against Cyberattacks via a Remediation Framework Based on Static VAR Compensators (SVCs)
- Mitigating Voltage Violations in Smart City Microgrids Under Coordinated False Data Injection Cyberattacks: Simulation and Experimental Insights
- False Data Injection Cyberattacks Targeting Electric Vehicles in Smart Power Distribution Systems
- Stealthy False Data Injection Cyberattack Targeting Under Load Tap Changing Transformers in Smart Power Grid Causing Abnormal Voltage Profile
Showing 5 of 11 shared publications
- False Data Injection Cyberattacks Targeting Electric Vehicles in Smart Power Distribution Systems
- A Remedial Action Scheme Against False Data Injection Cyberattacks Targeting ULTC Transformers in Smart Distribution Systems
- Design of a Standalone Hybrid Renewable Energy System - A Hospital in Lafayette, Indiana, USA
- A Hybrid ML-Digital Twin Framework for Differentiating Cyberattacks from Legitimate Price Fluctuations in Electricity Markets
- Impact of Phase Current Sequencing in Machine Learning Models for Induction Motor Fault Detection
- Load Factor Improvement of the Electricity Grid Considering Distributed Energy Resources Operation and Regulation of Peak Load
- Optimal strategy to reduce energy waste in an electricity distribution network through direct/indirect bulk load control
- Load Factor Improvement of the Electricity Grid Considering Distributed Energy Resources Operation and Regulation of Peak Load
- Optimal strategy to reduce energy waste in an electricity distribution network through direct/indirect bulk load control
- Load Factor Improvement of the Electricity Grid Considering Distributed Energy Resources Operation and Regulation of Peak Load
- Load Factor Improvement of the Electricity Grid Considering Distributed Energy Resources Operation and Regulation of Peak Load
- Load Factor Improvement of the Electricity Grid Considering Distributed Energy Resources Operation and Regulation of Peak Load
- Optimal strategy to reduce energy waste in an electricity distribution network through direct/indirect bulk load control
- Design of a Standalone Hybrid Renewable Energy System - A Hospital in Lafayette, Indiana, USA
- Digital Twin-Enabled Resilient Network Reconfiguration for Cybersecurity of Decarbonized Power Distribution Systems
- A Hybrid ML-Digital Twin Framework for Differentiating Cyberattacks from Legitimate Price Fluctuations in Electricity Markets
- Impact of Phase Current Sequencing in Machine Learning Models for Induction Motor Fault Detection
- Impact of Phase Current Sequencing in Machine Learning Models for Induction Motor Fault Detection
- Smart Power for a Sustainable Future: Design and Performance Analysis of a Hybrid Renewable Energy Microgrid for Arkansas State University’s Engineering College
- AI-Driven Automatic Fault Detection and Classification in Smart Microgrids
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