About Me
Rakesh Kumar Rai is a researcher in Computer Science and
Computational Neuroscience, currently pursuing his PhD at
Motilal Nehru National Institute of Technology (MNNIT), Allahabad.
His research focuses on EEG signal analysis and computational
neuroscience, particularly the development of deep learning frameworks
for cognitive state detection and neurological disorder analysis.
Research Highlights
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Research on EEG-based cognitive and neurological state analysis
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Deep learning and interpretable AI for healthcare applications
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Research on wearable sensing, sleep-stage analysis, and edge intelligence
Research Interests
- Computational Neuroscience
- Multimodal Neurophysiological Signal Processing
- Brain–Computer Interface (BCI)
- Application of AI/ML in Healthcare
- Human-computer interaction (HCI)
- EEG and Multimodal AI for Human Movement and Neuromotor Rehabilitation
Selected Research Publications
Journal Publications
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Rakesh Kumar Rai, et al.
"
A3S-Net: An Adaptive State-Space Framework for Resource-Efficient
EEG-Based Cognitive State Monitoring in Industrial Human–Machine Interaction
."
IEEE Transactions on Industrial Informatics,
IEEE, 2026.
EARLY ACCESS | SCI Q1 | IF: 9.8
-
Rakesh Kumar Rai, Sumana Achar, et al.
"
FedTrust-UNLEARN: Trust-Aware Federated Learning with Auditable
Unlearning for Privacy-Preserving Consumer IoMT EEG Intelligence
."
IEEE Transactions on Consumer Electronics,
IEEE, 2026.
SCI Q1 | IF: 9.9
-
Rakesh Kumar Rai, Dushyant Kumar Singh, et al.
"
SleepXNet: DeepSeek-Guided Hybrid Transformer Model for
Clinically Interpretable EEG-Based Sleep Stage Classification
."
IEEE Transactions on Emerging Topics in Computational Intelligence,
IEEE, 2026.
SCI Q1 | IF: 6
-
Rakesh Kumar Rai, Dushyant Kumar Singh, et al.
"
PHyena–DurCRF: A Quantum-Inspired, Edge-Efficient Analytics
Framework for Human-Centric Wearable Sensing
."
IEEE Transactions on Consumer Electronics,
IEEE, Vol. 72, No. 2, pp. 3949–3956, 2026.
SCI Q1 | IF: 9.9
-
Rakesh Kumar Rai and Dushyant Kumar Singh.
"
Stress Detection Through Wearable EEG Technology:
A Signal-Based Approach
."
Computers and Electrical Engineering,
Elsevier, Vol. 126, Article 110478, 2025.
SCI Q1 | IF: 5.5
Conference Publications
Education
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PhD – Computer Science
Motilal Nehru National Institute of Technology (MNNIT), Allahabad
2022 – Present
-
M.Tech – Computer Science
Maharshi Dayanand University
2019 – 2021
-
B.Tech – Computer Science
National Institute of Technology Nagaland
2012 – 2016
Personal Email:
rakeshnitn25@gmail.com
Official Email:
rakesh.2021rcs54@mnnit.ac.in
