RAHUL SATHEESH

About

Dr. Rahul Satheesh received BTech Degree in Electrical and Electronics Engineering from the University of Kerala, India, and ME. Degree in power systems from Anna University, Chennai, India in 2012 and 2014, respectively. He completed Ph.D. degree in the Department of Electrical Engineering in the domain of power systems at National Institute of Technology Calicut, Kerala, India. He is an active member of IEEE,IEEE PES and IEEE IAS. He is currently an executive committee member for IEEE PES Kerala Chapter and IEEE PES Young Professionals. His research interests include computational and data-driven algorithms, wide-area monitoring systems, power oscillation studies, power grid resilience, smart grids, and optimization techniques. He was honored with the young innovator award 2019 by Kerala state government. He published several research papers in various journals and attended several conferences.

Employment

• Amrita Vishwa Vidyapeetham Assistant Professor
  2023 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (16)

• A robust decomposition-denoising deep learning framework with dynamic intraperiod ramping for cost-effective balancing market operation
  Applied Soft Computing 2026 DOI: 10.1016/j.asoc.2026.115049
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• Bayesian-Optimized Predictive Modelling of Electric Arc Furnace Power Consumption for Industrial Deployment
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3655696
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• Enhanced Electric Vehicle Energy Consumption Prediction With TabTransformer, TabNet, and Bidirectional Encoder Representations From Transformers Embeddings
  IEEE Transactions on Industrial Informatics 2025 DOI: 10.1109/TII.2025.3576840
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• A Comprehensive Approach to Wind Power Forecasting Using Advanced Hybrid Neural Networks
  IEEE Access 2024 DOI: 10.1109/ACCESS.2024.3450096
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• Data-Driven Energy Management of an Electric Vehicle Charging Station Using Deep Reinforcement Learning
  IEEE Access 2024 DOI: 10.1109/ACCESS.2024.3398059
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• Ambient oscillatory mode assessment in power system using an advanced signal processing method
  ISA Transactions 2023 DOI: 10.1016/j.isatra.2023.08.012
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• Analyzing dominant oscillatory modes in power system using unidirectional and bidirectional LSTM Techniques
  Asia-Pacific Power and Energy Engineering Conference, APPEEC 2023 DOI: 10.1109/APPEEC57400.2023.10561940
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• Lower Limb EMG Signal Analysis Using Scattering Transform and Support Vector Machine for Various Walking Conditions
  IEEE Access 2023 DOI: 10.1109/ACCESS.2023.3332664
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• Assessment of Mode Shape in Power System Using TVF-EMD and Spectral Analysis
  Electric Power Components and Systems 2022 DOI: 10.1080/15325008.2022.2136297
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• Estimation of mode shape in power systems under ambient conditions using advanced signal processing approach
  Turkish Journal of Electrical Engineering and Computer Sciences 2022 DOI: 10.55730/1300-0632.3859
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