Sayanjit Singha Roy

About

Sayanjit Singha Roy (Graduate Student Member, IEEE) was born in Kolkata, India in 1995. He received the B. Tech degree in Electrical Engineering from Calcutta Institute of Engineering and Management, Kolkata, India in 2018, the M. Tech degree with specialization in Instrumentation from Techno India University, Kolkata, India in 2021 and the Ph.D. degree in High Voltage Engineering from National Institute of Technology Silchar, Assam, India in 2025. Currently, he is working as a National Post Doctoral Fellow in the Electrical Engineering Deaprtment, IIT Kanpur. His areas of research interests include partial discharge diagnostics, insulation condition monitoring using signal and image processing techniques, and exploring suitable application of AI/ML algorithms in the relevant areas.

Employment

• Indian Institute of Technology Kanpur National Post Doctoral Fellow
  2025 - Present

Education

• National Institute of Technology Silchar Doctor of Philosophy (Ph.D.)
  2021 - 2025
• Techno India University Masters of Technology (M.Tech)
  2019 - 2021

Projects & Funding

Projects & funding information is unavailable.

Publications (29)

• Image Visibility Patch-Aided Partial Discharge Recognition Framework for Identifying Defects in XLPE Cables
  IEEE Transactions on Instrumentation and Measurement 2025 DOI: 10.1109/TIM.2025.3581664
  +Save
• Condition Monitoring of Polymeric Insulators: A Remote Diagnostic Framework With Improved Intermediate Hydrophobicity Grade Detection
  IEEE Transactions on Industry Applications 2025 DOI: 10.1109/TIA.2025.3542723
  +Save
• Accurate Sensing of Insulator Surface Contamination Using Customized Convolutional Neural Network
  IEEE Sensors Letters 2023 DOI: 10.1109/LSENS.2022.3232506
  +Save
• Automated Space Charge Classification Inside ±500-kV HVDC Cable Insulation Using Fusion of Superpixel and Deep Features for Remote Condition Assessment
  IEEE Transactions on Instrumentation and Measurement 2023 DOI: 10.1109/TIM.2023.3266523
  +Save
• Characterization and Identification of Electrical Tree Growth Stages Inside High-Voltage Cable Insulation
  IEEE Transactions on Instrumentation and Measurement 2023 DOI: 10.1109/TIM.2023.3295017
  +Save
• Image Visibility Patch Aided Hydrophobic Class Detection of Silicone Rubber Insulators Employing Bi-LSTM Network
  2023 IEEE 3rd International Conference on Smart Technologies for Power, Energy and Control, STPEC 2023 2023 DOI: 10.1109/STPEC59253.2023.10430514
  +Save
• Remote Condition Monitoring of HVDC Cable Insulation Using Deep Learning-Aided Space Charge Classification
  IEEE Transactions on Dielectrics and Electrical Insulation 2023 DOI: 10.1109/TDEI.2022.3214171
  +Save
• Hydrophobicity Grade Detection of Polymeric Insulator Using Image Visibility Graph
  Proceedings of 2022 6th International Conference on Condition Assessment Techniques in Electrical Systems, CATCON 2022 2022 DOI: 10.1109/CATCON56237.2022.10077665
  +Save
• Recognition of Hydrophobicity Class of Polymeric Insulators Employing Residual Morphological Neural Network and Granulometry-Based Image Analysis
  IEEE Transactions on Instrumentation and Measurement 2022 DOI: 10.1109/TIM.2022.3164156
  +Save
• Detection of abnormal electromyograms employing DWT-based amplitude envelope analysis using Teager energy operator
  International Journal of Biomedical Engineering and Technology 2022 DOI: 10.1504/ijbet.2022.126493
  +Save