Dr. RK Tripathy

About

Dr. R.K. Tripathy is an Associate Professor in the Department of Electrical Engineering at the Government College of Engineering, Keonjhar, Odisha, India. He has worked as an Associate Professor and Assistant Professor at Birla Institute of Technology and Science (BITS), Pilani, Hyderabad, India. He has worked as an Assistant Professor in the Faculty of Engineering and Technology at Siksha' O' Anusandhan Deemed to be University. He has completed a Ph.D. in Machine Learning and Digital Signal Processing from IIT Guwahati, India. His areas of research are Biomedical signal processing, sparse representation and compressive sensing, Pattern recognition, machine intelligence, and Medical Image processing. He has published a number of papers in international journals and conferences.

Employment

• Government College of Engineering, Keonjhar Associate Professor
  2026 - Present
• Birla Institute of Technology and Science - Hyderabad Campus Associate Professor
  2024 - 2026
• BITS Pilani Assistant Professor
  2018 - 2024
• Siksha O Anusandhan University Institute of Technical Education and Research Assistant Professor
  2017 - 2018
• Biju Patnaik University of Technology Lecturer
  2009 - 2011

Education

• Indian Institute of Technology Guwahati Ph.D
  2013 - 2017
• National Institute of Technology Rourkela M.Tech
  2011 - 2013
• Biju Patnaik University of Technology B.Tech
  2005 - 2009

Projects & Funding

Projects & funding information is unavailable.

Publications (123)

• Integrated stability analysis and machine learning-based fault identification in microgrids during coupling operations and load effects
  Electrical Engineering 2026 DOI: 10.1007/s00202-026-03559-4
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• A Lightweight Fourier Block Transformer for Android-Based Edge-Enabled Detection of Osteopenia and Osteoporosis Using X-Ray Sensor Imaging Data
  IEEE Sensors Letters 2026 DOI: 10.1109/LSENS.2026.3660889
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• Automated human emotion recognition from EEG signals using chaotic local binary pattern and ensemble learning
  International Journal of Machine Learning and Cybernetics 2026 DOI: 10.1007/s13042-025-02822-7
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• Machine Learning and Deep Learning for Healthcare Data Processing and Analyzing: Towards Data-Driven Decision-Making and Precise Medicine
  Diagnostics 2025 DOI: 10.3390/diagnostics15081051
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• An IoT-Enabled Deep Learning Approach Implemented on Android Device for Automated Identification of Breast Cancer Using Thermal Images
  Smart Wearable Technology 2025 DOI: 10.47852/bonviewSWT52025252
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• Cross-Subject Emotion Recognition From Multichannel EEG Signals Using Multivariate Decomposition and Ensemble Learning
  IEEE Transactions on Cognitive and Developmental Systems 2025 DOI: 10.1109/TCDS.2024.3417534
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• Time–frequency domain machine learning for detection of epilepsy using wearable EEG sensor signals recorded during physical activities
  Biomedical Signal Processing and Control 2025 DOI: 10.1016/j.bspc.2024.107041
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• Automated Detection of Bone Fractures in Muscle X-Ray Images Using Multiband-Frequency Aware Deep Representation Learning
  Healthcare Technology Letters 2025 DOI: 10.1049/htl2.70021
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• Detection of Bundle Branch Block From 12-Lead ECG Using Fifth-Order Tensor-Domain Machine Learning
  IEEE Transactions on Human-Machine Systems 2025 DOI: 10.1109/THMS.2025.3563292
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• SERN-AwGOP: Squeeze-and-Excitation Residual Network With an Attention-Weighted Generalized Operational Perceptron for Atrial Fibrillation Detection
  IEEE Access 2025 DOI: 10.1109/ACCESS.2025.3544493
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