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Anup Das, Ph. D.

Postdoctoral Research Scientist

Phone: (858) 356-8512

Office: Electrophysiology, Memory, and
Navigation Laboratory
530 W. 120th Street, 419 CEPSR
New York, NY 10027

Email: ad3772@columbia.edu

Department of Biomedical Engineering
Columbia University
500 W. 120th Street #351
New York, NY 10027

Research overview

My current research interests are in computational cognitive neuroscience which include development and implementation of advanced computational methods to investigate human brain functional organization and development. During my postdoctoral fellowship at Stanford University, with professor Menon, I mainly worked on the Montreal Neurological Institute (MNI) and University of Pennsylvania Restoring Active Memory (UPENN-RAM) open, human intracranial electroencephalography (iEEG) datasets. Major focus of my work was on the salience and default-mode networks, two large-scale brain networks which play a prominent role in human cognition.

During my Ph. D., with professor Sejnowski, I mainly worked on brain connectivity estimation during epileptic seizures from human electrocorticography (ECoG) recordings using tools from statistics, sparse signal processing, and network neuroscience.

In my M. S. thesis, I worked on array signal processing and spectral estimation using methods from statistical signal processing, sparse signal processing, and Bayesian inference.

For a complete list of my publications, please refer to my google scholar page here.

Theses

Ph. D. Thesis (2018): The Importance of Latent Inputs for Analyzing the Human Brain.
Committee: Terrence J. Sejnowski (advisor, co-chair), Kenneth Kreutz-Delgado (co-chair), Paul H. Siegel, Eric Halgren, Vikash Gilja.

M. S. Thesis (2015): Multipath Resolution using Compressed Sensing.
Committee: William S. Hodgkiss (chair), Terrence J. Sejnowski, Bhaskar D. Rao.

Columbia postdoctoral research-related publications as peer-reviewed journal articles

[2] A. Das, E. Zabeh, J. Jacobs,"How to Detect and Analyze Traveling Waves in Human Intracranial EEG Oscillations?," in Intracranial EEG: A Guide for Cognitive Neuroscientists, chapter 30, pp. 487–505, Axmacher, N. (eds) Intracranial EEG. Studies in Neuroscience, Psychology and Behavioral Economics. Springer, Cham., 2023.

[1] A. Das*, J. Myers*, R. Mathura, B. Shofty, B. A. Metzger, K. Bijanki, C. Wu, J. Jacobs**, S. A. Sheth**,"Spontaneous neuronal oscillations in the human insula are hierarchically organized traveling waves," eLife, vol. 11, pp. e76702, 2022 (*Equal contribution, **Co-senior authors).

Ph. D. research-related publications as peer-reviewed journal articles

[3] A. Das, S. S. Cash, and T. J. Sejnowski,"Heterogeneity of Preictal Dynamics in Human Epileptic Seizures," IEEE Access, vol. 8, pp. 52738-52748, 2020.

[2] A. Das, D. Sexton, C. Lainscsek, S. S. Cash, and T. J. Sejnowski,"Characterizing Brain Connectivity from Human Electrocorticography Recordings with Unobserved Inputs during Epileptic Seizures," Neural Comput., vol. 31, no. 7, pp. 1271-1326, 2019.

[1] A. Das, A. L. Sampson, C. Lainscsek, L. Muller, W. Lin, J. C. Doyle, S. S. Cash, E. Halgren, and T. J. Sejnowski,"Interpretation of the precision matrix and its application in estimating sparse brain connectivity during sleep spindles from human electrocorticography recordings," Neural Comput., vol. 29, no. 3, pp. 603-642, 2017.

M. S. research-related publications as peer-reviewed journal articles

[7] A. Das,"Real-Valued Sparse Bayesian Learning for Off-Grid Direction-of-Arrival (DOA) Estimation in Ocean Acoustics," IEEE J. Ocean. Eng., vol. 46, no. 1, pp. 172-182, 2021.

[6] A. Das,"Deterministic and Bayesian Sparse Signal Processing Algorithms for Coherent Multipath Directions-of-Arrival (DOAs) Estimation," IEEE J. Ocean. Eng., vol. 44, no. 4, pp. 1150-1164, 2019.

[5] A. Das, D. Zachariah, and P. Stoica,"Comparison of Two Hyperparameter-Free Sparse Signal Processing Methods for Direction-of-Arrival Tracking in the HF97 Ocean Acoustic Experiment," IEEE J. Ocean. Eng., vol. 43, no. 3, pp. 725-734, 2018.

[4] A. Das, and T. J. Sejnowski,"Narrowband and Wideband Off-Grid Direction-of-Arrival Estimation via Sparse Bayesian Learning," IEEE J. Ocean. Eng., vol. 43, no. 1, pp. 108-118, 2018.

[3] A. Das,"Theoretical and Experimental Comparison of Off-Grid Sparse Bayesian Direction-of-Arrival Estimation Algorithms," IEEE Access, vol. 5, pp. 18075-18087, 2017.

[2] A. Das,"A Bayesian Sparse-plus-Low-Rank Matrix Decomposition Method for Direction-of-Arrival Tracking," IEEE Sensors J., vol. 17, no. 15, pp. 4894-4902, 2017.

[1] A. Das, W. S. Hodgkiss, and P. Gerstoft,"Coherent Multipath Direction-of-Arrival Resolution Using Compressed Sensing," IEEE J. Ocean. Eng., vol. 42, no. 2, pp. 494-505, 2017.

Editorial activity

I serve in the following editorial boards.

  • Review Editor, Frontiers in Signal Processing (Special Section: Statistical Signal Processing)
  • Guest Associate Editor, Frontiers in Signal Processing (Special Section: Radar Signal Processing)

Reviewing activity

I am an invited reviewer for the following journals.

  • Translational Psychiatry
  • Frontiers in Neuroscience
  • IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • IEEE Journal of Biomedical and Health Informatics
  • IEEE Transactions on Signal Processing
  • IEEE Open Journal of Signal Processing
  • IEEE Transactions on Radar Systems
  • IEEE/ACM Transactions on Audio, Speech, and Language Processing
  • IEEE Transactions on Circuits and Systems II: Express Briefs
  • IEEE Transactions on Evolutionary Computation
  • IEEE Transactions on Industrial Informatics
  • IEEE Sensors Journal
  • IEEE Systems Journal
  • IEEE Journal of Oceanic Engineering
  • IEEE Transactions on Aerospace and Electronic Systems
  • IEEE Transactions on Vehicular Technology
  • IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
  • IEEE Access
  • IEEE Signal Processing Letters
  • IEEE Sensors Letters
  • IEEE Communications Letters
  • Signal Processing
  • Journal of the Acoustical Society of America
  • IET Signal Processing
  • Neural Computation
  • Sensors
  • Applied Sciences
  • Remote Sensing
  • Digital Signal Processing