Discipline of Electrical and Electronics Engineering

Information

Name: Dr. Rahul Ranjeev Kumar
Position: Lecturer in Electrical & Electronics Engineering
Email: rahul.kumar@usp.ac.fj
Phone: +679 32 32992

Detail Information

Rahul R Kumar received his Bachelor’s degree in Electrical and Electronic Engineering from the University of the South Pacific, Suva, Fiji (USP) in 2014. From 2014-2017, he has been a Teaching and Research assistant at USP. In 2016, he completed his Master of Science in Engineering degree from USP. For both his degrees, he received gold medals for being the outstanding graduate and the best MSc thesis, respectively. From 2017 to 2020, he was awarded a prestigious Doctoral fellowship at the University of Padova (UNIPD), Padova, Italy for Ph.D in Industrial Engineering. He successfully defended his Ph.D thesis on 30th March, 2021 (with congratulations from jury), his PhD graduation is set for 2022 (UNIPD’s 8th century cohort). During his MSc and PhD tenure, he has published in international journals and presented his research in many high ranked conferences of which he was awarded the best paper. He has also been the reviewer for a number of IEEE and Springer Journals. From 2016, he has also held the position as the chair of IEEE USP Student Chapter. Currently, he works as a Lecturer in Electrical/Electronic Engineering at USP. His research interests mainly include neural networks (LSTM, Attention Mechanisms and Transformers), computer vision, system identification, fault diagnosis (rotating machines and fuel cells), robotics (armed robots) and data analysis (general). His research & reviewer profiles can be viewed here: ResearchGate | Google Scholar |Publons | ORCID |Scopus

Undergraduate Courses:

  • EE211 – Electrical Machines
  • EE461 – Special Topics in Electrical & Electronics Engineering
  • EE314 – Electrical Systems Design

Postgraduate Course:

  • Guest Lecturer: SC400 – Research methods
  • Guest Lecturer: PH407 – Wind Power: Theory & Applications

My research and teaching encompasses the following areas:

  • Diagnosis of Electrical Drives
  • Industry Applications of electromechanical systems
  • Design and deployment of neural networks & also developing novel neural based techniques
  • Nonlinear Approximation of functions for dynamical modelling (Neural Networks)
  • Development of novel feature engineering methods
  • Study of Data Geometry and Topology
  • Application of Dimensionality Reduction techniques to various forms of data
  • Applications of neural networks for electrical engineering, pattern recognition and classification.
  • Maintenance & Reliability
  • Coordinator and Chair of IEEE USP Student Chapter (Region 10: Asia Pacific) – From 04/2016 – Present
  • IEEE Full Member (Member of IEEE Robotics and Automation Society, Member of IEEE Power Electronics Society, Member of Industry Application Society, Member of IEEE Systems Council)
  • Member of Electric Machines Group (University of Padova)
  • Reviewer for the following Journal and Conferences:
  • IEEE Access
  • IEEE Transactions on Industrial Informatics
  • IEEE Transaction on Industrial Electronics
  • IEEE Transactions on Energy Conversion
  • Computer Communications
  • Neural Computing and Applications (Springer Nature)
  • Complex and Intelligent Systems (Spinger Nature)
  • Cognitive Systems and Science
  • Concurrency and Computation Practice and Experience
  • IEEE ICEMS 2019-2020
  • The Italian Workshop on Neural Networks (WIRN)
  • Organizer (ITS Support Staff)/Committee member for the 7th Symposium on Sensorless Control for Electrical Drives, 2016. (SLED 2016 – Denerau, Fiji)
  • Graduate Assistantship for MSc – University of the South Pacific Research Office, 2014 (FJD $19,674)
  • Project: Development of a wireless robotic arm with an intelligent gripper – University of the South Pacific Research Office, 2014 (FJD $10,200)
  • Contributing researcher for the following Projects (grant awarded by University of the South Pacific Research Office):
    • Development of the Eco-Trike for sustainable transportation in PIC’s (FJD $49,963).
    • Power Routers Interfaces for microgrids supplied by renewable energy sources and flywheels for the sustainable energy supply of areas which are either remote or affected by natural hazards (FJD $50,000).
  • Contributing researcher for the following projects (grant awarded by French Pacific Fund):
  • “Design of a REnewable energy source system with a Flywheel Energy storage system for supplying energy in Pacific Island CountrieS with weakgrid I” (REFEPICS I)
  • “Design of a REnewable energy source system with a Flywheel Energy storage system for supplying energy in Pacific Island CountrieS with weakgrid II” (REFEPICS II)
  • Project Collaboration: Innovative Techniques for Electrical Machine Diagnosis – collaboration with University of Padova – ongoing research & publication can be found under my Researchgate Profile.
  1. R. Kumar, G. Cirrincione, M. Cirrincione, A. Tortella and M. Andriollo, “Induction Machine Fault Detection and Classification Using Non-Parametric, Statistical-Frequency Features and Shallow Neural Networks,” in IEEE Transactions on Energy Conversion, 2021, doi: 10.1109/TEC.2020.3032532 (Q1)
  2. R. Kumar, G. Cirrincione, M. Cirrincione, A. Tortella and M. Andriollo, “A Topological Neural-Based Scheme for Classification of Faults in Induction Machines,” in IEEE Transactions on Industry Applications, vol. 57, no. 1, pp. 272-283, Jan.-Feb. 2021, doi: 10.1109/TIA.2020.3032944 (Q1)
  3. R. Kumar et al., “Induction Machine Stator Fault Tracking Using the Growing Curvilinear Component Analysis,” in IEEE Access, vol. 9, pp. 2201-2212, 2021, doi: 10.1109/ACCESS.2020.3047202 (Q1)
  4. Cirrincione, R. R. Kumar, A. Mohammadi, S. H. Kia, P. Barbiero and J. Ferretti, “Shallow Versus Deep Neural Networks in Gear Fault Diagnosis,” in IEEE Transactions on Energy Conversion, vol. 35, no. 3, pp. 1338-1347, Sept. 2020, doi: 10.1109/TEC.2020.2978155 (Q1)
  5. R Kumar, U. Mehta (2017), “A Low Cost Linear Force Feedback Control System for a Two-Fingered Parallel Configuration Gripper”, Procedia Computer Science, In Elsevier., 105, pp.264-269. (Q2)
  6. R Kumar et.al. (2017),”Maze solving robot with automated obstacle avoidance”,Procedia Computer Science,In Elsevier., 05, pp.57-61. (Q2)
  7. Chand, P., Lal, S., & Kumar, R R., (2016). Development of a Force Feedback System for a SCORBOT Robotic Arm Gripper. ARPN Journal of Engineering and Applied Sciences, 11(23), pp.13766-13774. http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_1216_5454.pdf (Q2)
  8. Assaf., R. R. Kumar., B. Sharma., (2022), Tongue Driven System in Education Technology, Education and Information Technologies. (under review – minor revision)
  1. Cirrincione G., Randazzo V., Kumar R. R, Cirrincione M., Pasero E. (2020) Growing Curvilinear Component Analysis (GCCA) for Stator Fault Detection in Induction Machines. In: Esposito A., Faundez-Zanuy M., Morabito F., Pasero E. (eds) Neural Approaches to Dynamics of Signal Exchanges. Smart Innovation, Systems and Technologies, vol 151. Springer, Singapore. https://doi.org/10.1007/978-981-13-8950-4_22
  2. Kumar R. R, Sharma K., Assaf M., Sharma B., Naidu S. (2019) Development of an Assistive Tongue Drive System for Disabled Individuals. In: Nayak A., Sharma A. (eds) PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. Lecture Notes in Computer Science, vol 11672. Springer, Cham. https://doi.org/10.1007/978-3-030-29894-4_41
  3. Assaf M., Kumar R.R, Sharma K., Narayan S. (2020) Enabling Students with Severe Disablities to Communicate with Learning Environments. In: Naidu S., Narayan S. (eds) Teaching and Learning with Technology: Pushing boundaries and breaking down walls, USP Press, Suva, Fiji, pp. 165-184. ISBN 978-982-01-0998-8. http://repository.usp.ac.fj/12032/1/
  1. K. Raj, S. H. Joshi and R. R. Kumar, “A state-space model for induction machine stator inter-turn fault and its evaluation at low severities by PCA,” 2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), 2021, pp. 1-6, doi: 10.1109/CSDE53843.2021.9718479.
  2. Bula, E. Arukelana, A. Bali, B. Sharma, R. R. Kumar and M. Assaf, “Human Behavior Identification and Recognition System,” 2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), 2021, pp. 1-6, doi: 10.1109/CSDE53843.2021.9718456.
  3. Kumar et al., “Power Switch Open-Circuit Fault-Diagnosis Based on a Shallow Long-Short Term Memory Neural Network: Investigation of an Interleaved Buck Converter for Electrolyzer applications,” 2021 IEEE Energy Conversion Congress and Exposition (ECCE), 2021, pp. 483-488, doi: 10.1109/ECCE47101.2021.9595018.
  4. Narayan, R. R. Kumar, G. Cirrincione and M. Cirrincione, “Detection of Stator Fault in Synchronous Reluctance Machines Using Shallow Neural Networks,” 2021 IEEE Energy Conversion Congress and Exposition (ECCE), 2021, pp. 1347-1352, doi: 10.1109/ECCE47101.2021.9595518.
  5. Chand, K. Chand, R. R. Kumar et.al, “An Optimized Tongue Drive System for Disabled Persons”, IEEE International Instrumentation and Measurement Technology Conference, Glasgow, Scotland, 2021, pp. 1-6., doi: 10.1109/I2MTC50364.2021.9460029
  6. Andriollo, R. R. Kumar, A. Tortella and R. Zavagnin, “FEM based Assessment of Winding Inter-Tum Fault Indicators in Line Connected Induction Motors,” 2020 AEIT International Annual Conference (AEIT), Catania, Italy, 2020, pp. 1-6, doi: 10.23919/AEIT50178.2020.9241186
  7. R. Kumar, A. Tortella and M. Andriollo, “Spectral and Discriminant Analysis Based Classification of Faults in Induction Machines,” 2020 AEIT International Annual Conference (AEIT), Catania, Italy, 2020, pp. 1-6, doi: 10.23919/AEIT50178.2020.9241115.
  8. Assaf, Mansour and Kumar, Rahul and Nambiar, Karthiyani and Narayan, Sharishna and Nath, Niraj N. and Reddy, Yogesh and Sharma, Krishneel K. and Sharma, Bibhya N. (2019), “Enabling Students with Severe Disabilities to Communicate with Learning Environments,” 2018 5th Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE), Nadi, Fiji, 2018, pp. 201-206, doi: 1109/APWConCSE.2018.00040
  9. R. Kumar, G. Cirrincione, M. Cirrincione, A. Tortella and M. Andriollo, “Induction Machine Fault Diagnosis Using Stator Current Subspace Spectral Estimation,” 2018 21st International Conference on Electrical Machines and Systems (ICEMS), Jeju, 2018, pp. 2565-2570, doi: 10.23919/ICEMS.2018.8549374
  10. R. Kumar, G. Cirrincione, M. Cirrincione, A. Tortella and M. Andriollo, “A Topological and Neural Based Technique for Classification of Faults in Induction Machines,” 2018 21st International Conference on Electrical Machines and Systems (ICEMS), Jeju, 2018, pp. 653-658, doi: 10.23919/ICEMS.2018.8549509 (BEST PAPER AWARD)
  11. R. Kumar, G. Cirrincione, M. Cirrincione, M. Andriollo and A. Tortella, “Accurate Fault Diagnosis and Classification Scheme Based on Non-Parametric, Statistical-Frequency Features and Neural Networks,” 2018 XIII International Conference on Electrical Machines (ICEM), Alexandroupoli, 2018, pp. 1747-1753, doi: 10.1109/ICELMACH.2018.8507213
  12. Cirrincione, V. Randazzo, R. R. Kumar, M. Cirrincione and E. Pasero (2017), “Growing Curvilinear Component Analysis (GCCA) for Stator Fault Detection in Induction Machines”, The Italian Workshop on Neural Networks (WIRN) on, June 14th to 16th in Vietri sul Mare, Italy.
  13. R. Kumar, V. Randazzo, G. Cirrincione, M. Cirrincione and E. Pasero, “Analysis of stator faults in induction machines using growing curvilinear component analysis,” 2017 20th International Conference on Electrical Machines and Systems (ICEMS), Sydney, NSW, 2017, pp. 1-6, doi: 10.1109/ICEMS.2017.8056240
  14. Kumar, P. Chand., “Inverse Kinematics Solution for Trajectory Tracking using Artificial Neural Network for SCORBOT-ER 4u”, The 6th International Conference on Automation, Robotics and Applications – IEEE 2015, Rydges Lakeland Resort, Queenstown, New Zealand., 17 – 19 February, 2015., 6 pages.
  15. Kumar, S. Kumar, S. Lal, P. Chand., “Object Detection and Recognition for a Pick and Place Robot”, IEEE Asia-Pacific World Congress on Computer Science and Engineering 2014, Plantation Island, Fiji, 4-5 November, 2014., 6 pages.
  16. Kumar, H. Reddy & R. Chand., “The Study of Transients in Grid Coupled Synchronous Generators”, The 2014 International Capstone Design Contest on Renewable Energy Technology, Presented on, January 8th, 2014., pp 11-14. (Sponsored by Mokpo National University LINC)
  1. Rahul Ranjeev Kumar, (2021), “A Topological Neural Network for the On-line Diagnosis of Induction Machines: Manifold based Shallow & Deep learning, Theoretical Aspects and Experimental Tests”, PhD Thesis, University of Padova, Italy, 217 leaves, http://paduaresearch.cab.unipd.it/13527 *
  2. Rahul Ranjeev Kumar, (2016), “Development of an autonomous wireless robotic arm with intelligent gripper”, Masters Thesis, The University of the South Pacific, Fiji, 148 leaves*
  3. Rahul Ranjeev Kumar, (2013), “Mobile Robot Navigation on Vehicle Platform”, BE Final Year Report, The University of the South Pacific, Fiji*

Master’s Research Students (Principal Tutor)

  • Reece Pene (USP): Thesis Title – Pothole Detection and Evaluation for Fijian Roads using Artificial Intelligence Techniques
  • Davide Brotto (UNIPD): Thesis Title – Machine Design Parameter Optimization using Neural Networks

PhD Research Students (Co-tutor)

  • Priynka Sharma: Thesis Title – Fuel Cell Diagnostics using AI techniques