Theodoros (Theo) Zanos is an Assistant Professor at the Feinstein Institute for Medical Research and the head of the Neural Encoding and Data Analytics lab at the Center of Bioelectronic Medicine. He lives in New York, NY.

Resume (1-page) | Curriculum Vitae (5 pages)

Before joining Feinstein Institute, he was a research associate and a postdoctoral fellow at the laboratory of Dr. Christopher Pack, in the department of Neurology and Neurosurgery, at the Montreal Neurological Institute at McGill University. He acquired his MSc and PhD in Biomedical Engineering in 2006 and 2009 respectively, at the Viterbi School of Engineering at University of Southern California, under the supervision of Dr. Vasilis Marmarelis. In 2004, he graduated with an Electrical and Computer Engineering diploma from the Aristotle University of Thessaloniki.

Theo has a proven track record in developing quantitative models of neuronal circuits and neuroprosthetic algorithms decoding neuronal activity in the visual cortex, the hippocampus and peripheral nerves, performing single and multi-electrode recordings and stimulation (intracortical, transcranial and epineural) in behaving primates, rats and mice, relating research results to visual perception, eye movement behavior, learning and memory, as well as inflammatory and metabolic states. He also serves as the project lead for the Real-Time Diagnostics and Monitoring, the Electronic Pancreas and the Neural Bypass Decoding projects at the Center for Bioelectronic Medicine.

He has been awarded the Center of Excellence in Commercialization and Research Grant ($80k – 2010), the Jean Timmins Fellowship Grant ($40k – 2012) and the Research Assistant Fellowship Grant ($120k - 2004).

He has p
ublished his research results in 15 peer-reviewed papers, in journals like Neuron, Journal of Neuroscience, Journal of Neurophysiology, IEEE Transactions in Neural Systems, Annals of Biomedical Engineering and others, with over 250 citations (h-index=7), presented work in 16 international conferences, awards for best Senior Thesis (2004) and best oral presentation (2006)

His expertise includes the following areas:

Computational Neuroscience: nonlinear neural systems modeling; functional connectivity algorithms; cortical wave detection algorithms; neural signal processing; FEM-based EEG source localization

Signal Processing - Systems Identification: predictive Volterra models; time-frequency analysis of signals; statistical signal processing; nonlinear dynamic systems modeling; machine learning

Neuroengineering: neuroprosthetic multi-input multi-output computational algorithms predicting neuronal ensemble activity; invasive (intracortical microstimulation - iCMS) and non-invasive (transcranial current stimulation - tCS) neurostimulation; decoding of nerve recordings to detect inflammatory or metabolic states; optimization of nerve stimulation parameters to optimize treatment outcomes; optimization of deep brain stimulation; big data problems in neuroengineering

Neurophysiology: chronic electrode arrays; visual cortex and hippocampal recordings from behaving primates; hippocampal recordings from behaving rats and slice preparations; vagus nerve recordings from mice; temporal lobe recordings from humans; eye tracking signal analysis & saccade dynamics analysis; single and multi-electrode recordings; EEG; tCS; deep brain stimulation recordings; closed-loop visual stimulation; monkey behavior and training

Programming: Matlab; GUI Development; Toolbox Development; Parallel Processing Programming; Python

He is a reviewer for the Cerebral Cortex journal, Journal of Neurophysiology, IEEE Transactions in Biomedical Engineering, Frontiers in Neural Circuits, Annals of Biomedical Engineering, IEEE Signal Processing Letters journal, IEEE Engineering in Medicine and Biology Conferences and IEEE Neural Engineering Conferences. He is a lecturer for the Bioelectronic Medicine Course of the Elmezzi Graduate School of Molecular Medicine, a guest lecturer for the 2017 Bioelectronic Medicine Course at the Karolinska Institute in Sweden and for four years a guest lecturer for the Computational Neuroscience Course (Neur 603) of the Integrated Program in Neuroscience (IPN) at McGill University. He served as a chair or scientific committee member in several scientific symposia, as a consultant for NIH grants and as the lead research scientist for a wearables project developing Closed-Loop Mobile EMG-based Arm Rehabilitation App (CLM-ARP). He is a member of the New York Academy of Sciences, the Society for Neurosciences, the Institute of Electrical and Electronic Engineers (IEEE) and the Engineering in Medicine and Biology Society of IEEE.


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