Computer science × neuroscience

Rakesh
Kumar Rai

Rakesh Kumar Rai develops robust, interpretable, physiology-guided, and computationally efficient AI for EEG and multimodal neurophysiological signals.

Doctoral Researcher Computer Science & Engineering MNNIT Allahabad
Prayagraj, India Updated September 2026

His work sits at the intersection of neural signals, machine intelligence, and human health.

Rakesh Kumar Rai is a PhD researcher in Computer Science and Engineering at Motilal Nehru National Institute of Technology (MNNIT) Allahabad. His work spans artificial intelligence, computational neuroscience, and neurophysiological signal processing.

His research focuses on EEG-based modelling of cognitive and brain states using robust, interpretable, physiology-guided, and computationally efficient learning. His broader interests include multimodal neurophysiological signals, meditation and devotional-practice EEG, temporal representation learning, brain-computer interfaces, human movement, and AI-enabled neurorehabilitation.

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Presented NestedSleepNet at ICPR 2026 in Lyon and presented doctoral research at the ICPR Doctoral Consortium.

PHyena–DurCRF was published online in IEEE Transactions on Consumer Electronics.

SleepXNet was published in IEEE Transactions on Emerging Topics in Computational Intelligence.