Amit Kumar
University of Naples Federico II, Larsen & Toubro (India), Indian Institute of Technology Delhi, National Institute of Technology Calicut
About
I, Amit Kumar, am a researcher in Biomedical Engineering and Cognitive Neuroscience, currently working in the Department of Electrical Engineering and Information Technology (DIETI) at the University of Naples Federico II, Naples (1224-2026), Italy. My research is guided by a central question: How can neuroscience, physiological sensing, and emerging technologies be integrated to better understand the human brain and develop practical solutions for mental health and well-being?
I completed my PhD in Cognitive Neuroscience at the Indian Institute of Technology (IIT) Delhi as a Prime Minister’s Research Fellow (PMRF), Government of India. My doctoral research investigated the neural and physiological correlates of mental stress and examined how mindfulness- and breathing-based interventions can modulate stress-related brain and physiological responses. Before my PhD, I completed an M.Tech. in Neurorehabilitation from IIT Delhi and a B.Tech. in Electrical and Electronics Engineering from NIT Calicut. To broaden my understanding of the human mind, behavior, cognition, and values, I also pursued interdisciplinary academic training through a Master of Arts in Psychology and a Master of Arts in Philosophy from IGNOU.
My research interests span wearable sensors, physiological monitoring, biomedical instrumentation, mental stress assessment, objective assessment of mindfulness, mini-meditation and breathing-based interventions, mind-wandering, EEG and MEG signal analysis, neurorehabilitation, cognitive neuroscience, biomedical signal processing, sleep, pain, and artificial intelligence for healthcare.
My current research focuses on developing EEG-guided adaptive LLM-based avatars (digital twins) and neurosymbolic AI systems for personalized mindfulness guidance for regulation of stress, anxiety, pain, and emotional regulation. These systems are designed to adapt to an individual's personality, cognitive state, and physiological condition while emphasizing explainability, safety, personalization, and clinical supervision. Alongside this work, I am interested in the development of wearable low-channel EEG systems, EEG artifact characterization and mitigation, real-time assessment of mental stress and mind-wandering, multimodal physiological monitoring, and personalized strategies for emotional and cognitive regulation.
Another important direction of my research is the investigation of cortical and subcortical brain dynamics using high-density EEG, MEG, and related neurophysiological approaches. Through this work, I aim to better understand how measurable neural activity relates to cognition, emotion, behavior, mental states, and responses to therapeutic or mindfulness-based interventions.
My long-term research vision is to integrate biomedical engineering, wearable technologies, biomedical instrumentation, neuroscience, psychology, philosophy,and responsible artificial intelligence to develop scientifically grounded, accessible, and human-centered solutions for mental health, emotional and cognitive regulation, neurorehabilitation, and overall human well-being.
Employment
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University of Naples Federico II Research Fellow2025 - 2026
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Larsen & Toubro (India) Assistant Electrical Engineer2016 - 2017
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Larsen & Toubro (India) Assistant Electrical Engineer2015 - 2016
Education
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Indian Institute of Technology Delhi Phd, Prime Minister's Research Fellows (PMRF)2021 - 2025
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Indian Institute of Technology Delhi M.Tech2017 - 2019
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National Institute of Technology Calicut B.Tech2011 - 2015
Projects & Funding
Projects & funding information is unavailable.
Publications (13)
- Toward an adaptive EEG-guided avatar for personalized mindfulness training: A rule-grounded LLM framework with ex post clinical supervision Save
- MORA: A Rule-Constrained LLM Framework for Conflict-Aware Adaptive Mindfulness Guidance Save
- Uncertainty-aware comparison of tES, DBS, and stereo-EEG stimulation assessment: A critical narrative review Save
- Nasal Dominance and Nostril Breathing Variability: Potential Biomarkers of Acute Stress Save
- Connecting Brains and Interfaces: Real-Time EEG-Based Stress Detection via Spiking Neural Networks Save
- Deep learning-based classification of dementia using image representation of subcortical signals Save
- StreXNet: A Novel End-to-End Deep-Learning-Based Improved Multilevel Mental Stress Classification From EEG Sensors Save
- Effects of mini-meditation-based breathing exercise as intervention on induced mental stress: An EEG power spectrum evidence-based study Save
- Effect of Mini-Meditation on EEG Alpha Activity and Global Graph Measures with Induced Mental Stress Save
- Effect of ambient temperature and respiration rate on nasal dominance: preliminary findings from a nostril-specific wearable Save