Clinical neural AI
Interpretable EEG biomarkers and evaluation protocols built for variation across patients, devices, and clinical centres.
Learn moreElectrical Engineering · IIT Mandi
Reliable intelligence for neural signals.
We develop signal-processing and machine-learning methods that make brain and biosignal data more interpretable, efficient, and clinically useful.
2026
Announcements
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Research
From principled models to practical systems.
Our work combines statistical signal processing, neuroscience, dynamical systems, and compact machine learning. Clinical reliability is a design requirement, not an afterthought.
Efficient signal restoration
Compact models that remove physiological artifacts while preserving the neural information clinicians and researchers need.
Learn moreBio-inspired computation
Balanced recurrent systems and connectome-constrained models for studying efficient, sequential neural computation.
Learn moreDynamics & information
Nonlinear and information-theoretic tools for characterising multivariate brain activity and state transitions.
Learn moreSelected publications
Recent work
2026
Robust multi-centre interictal EEG biomarker for distinguishing epilepsy from mimickers
J. B. Lahiri, P. Agarwal, S. Kushwaha, M. Singh, and S. Panwar
2026
2026
People
A small, interdisciplinary team.
Principal investigator
Dr Siddharth Panwar
Assistant Professor, School of Computing and Electrical Engineering
Faculty profile
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