Rahul Ranjeev Kumar

About

Dr. Rahul Ranjeev Kumar is a Lecturer in Electrical Engineering at Charles Darwin University, Australia, bringing over 10 years of teaching experience. He previously served as Lecturer (2021–2023) and Senior Lecturer (2024–2025) in Electrical & Electronics Engineering at the University of the South Pacific before joining CDU in August 2025. He holds a PhD in Industrial Engineering from the University of Padova (Italy) and an MSc in Electrical Engineering from the University of the South Pacific, both awarded with Gold Medals for outstanding research. His research spans artificial intelligence for electrical machine diagnostics, deep learning, power electronics, renewable energy systems, and microgrid applications. Dr. Kumar has authored over 50 peer-reviewed papers in IEEE transactions and international conferences, alongside 15 book chapters with Springer and CRC Press. He serves as a reviewer for IEEE and Elsevier journals. Recognised with the Best Early Career Researcher Award (2023), he welcomes PhD/MSc candidates in AI-driven diagnostics, power electronics, and smart microgrids.

Employment

• Charles Darwin University Lecturer in Electrical Engineering
  2025 - Present
• University of the South Pacific Senior Lecturer in Electrical & Electronic Engineering
  2024 - Present
• The University of the South Pacific Lecturer in Electricla & Electronic Engineering
  2021 - 2023
• University of Padua Doctoral Student
  2017 - 2020
• The University of the South Pacific Teaching Assistant
  2014 - 2021
• Charles Darwin University

Education

• The University of the South Pacific Post Graduate Certificate in Tertiary Teaching
  2021 - 2022
• University of the South Pacific MAster of Science in Engineering
  2014 - 2016
• University of the South Pacific Bacholer of Electrical/Electronic Engineering
  2011 - 2013

Projects & Funding

Projects & funding information is unavailable.

Publications (61)

• Image-Based Fault Detection and Severity Classification of Broken Rotor Bars in Induction Motors Using EfficientNetB3
  Energies 2026 1 citation DOI: 10.3390/en19041110
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• A Novel Compact Hierarchical Deep Convolutional Neural Network Architecture for Faulty Switch Detection and Localization in Power Converters
  IEEE Transactions on Industry Applications 2026 1 citation DOI: 10.1109/TIA.2026.3661948
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• Video-Based System for Detecting Falls in Elderly Individuals
  Computing and Machine Learning - Proceedings of CML 2025 2026 1 citation DOI: 10.1007/978-981-95-2875-2_16
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• Collapse-Free Prototype Readout Layer for Transformer Encoders
  2026 0 citations DOI: 10.2139/ssrn.6735035
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• Development of a Tongue Motion Translator: Enhancing Communication for Individuals with Severe Disabilities
  2026 1 citation DOI: 10.1007/978-981-95-0493-0_34
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• Optimized Vehicular Energy Network: Energy Path Design and Power Loss Minimization for Smart Cities
  2026 0 citations DOI: 10.1007/978-981-96-9771-7_5
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• Smart Heat Drying with an IoT-Integrated Framework for Sustainable and High-Quality Processing
  2026 0 citations DOI: 10.1007/978-3-032-23945-7_32
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• Bearing Remaining Useful Life Estimation Using Proximal Policy Optimization (PPO): Validation on the XJTU-SY Run-to-Failure Dataset
  Machines 2026 0 citations DOI: 10.3390/machines14060672
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• Advanced Encryption Techniques in Satellite Communications With Chaotic Injection and Quantum Collapse for Enhanced Security
  International Journal of Satellite Communications and Networking 2025 2 citations DOI: 10.1002/sat.70009
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• Detection and Classification of Low-Severity Stator Inter-Turn Faults in Induction Motors Using Temporal Features
  Intelligent Machinery Fault Diagnostics and Prognostics 2025 0 citations DOI: 10.1201/9781003480822-5
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