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Computer Science

D-Index
50
Citations
10171
World Ranking
5617
National Ranking
2564

Research.com Recognitions

  • 2016 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2009 - Fellow of the Indian National Academy of Engineering (INAE)

Overview

Paul Sajda is affiliated with Columbia University in the United States. Their research primarily focuses on the field of neuroscience with a significant emphasis on cognitive neuroscience as well as subfields such as neurology, radiology, nuclear medicine and imaging, social psychology, and human-computer interaction.

Their work covers a range of main topics including:

  • Functional Brain Connectivity Studies
  • Neural dynamics and brain function
  • EEG and Brain-Computer Interfaces
  • Transcranial Magnetic Stimulation Studies
  • Neural and Behavioral Psychology Studies
  • Advanced MRI Techniques and Applications
  • Gaze Tracking and Assistive Technology

Paul Sajda has published extensively, with frequent appearances in venues such as:

  • Brain stimulation
  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition
  • Scientific Reports

Some recent papers include:

  • "International Brain Initiative: An Innovative Framework for Coordinated Global Brain Research Efforts" (2020, Neuron)
  • "Robust and Interpretable Convolutional Neural Networks to Detect Glaucoma in Optical Coherence Tomography Images" (2020, IEEE Transactions on Biomedical Engineering)
  • "Daily prefrontal closed-loop repetitive transcranial magnetic stimulation (rTMS) produces progressive EEG quasi-alpha phase entrainment in depressed adults" (2022, Brain stimulation)
  • "A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocular biomarkers" (2022, Scientific Reports)
  • "Inferring Macroscale Brain Dynamics via Fusion of Simultaneous EEG-fMRI" (2021, Annual Review of Neuroscience)

Their research collaborations include frequent co-authorships with:

  • Xiaoxiao Sun
  • Josef Faller
  • Jayce Doose
  • Robin I. Goldman
  • Mark S. George

Paul Sajda has been recognized by professional organizations, having received the title of Fellow of the American Association for the Advancement of Science (AAAS) in 2016 and Fellow of the Indian National Academy of Engineering (INAE) in 2009.

Best Publications

  • Recipes for the linear analysis of EEG.

    Lucas C. Parra;Clay D. Spence;Adam D. Gerson;Paul Sajda

  • Neural representation of task difficulty and decision making during perceptual categorization: a timing diagram.

    Marios G. Philiastides;Roger Ratcliff;Paul Sajda

  • Machine Learning for Detection and Diagnosis of Disease

    Paul Sajda

  • Temporal Characterization of the Neural Correlates of Perceptual Decision Making in the Human Brain

    Marios G. Philiastides;Paul Sajda

  • Quality of evidence for perceptual decision making is indexed by trial-to-trial variability of the EEG

    Roger Ratcliff;Marios G. Philiastides;Paul Sajda

  • Cortically coupled computer vision for rapid image search

    A.D. Gerson;L.C. Parra;P. Sajda

  • Blind source separation via generalized eigenvalue decomposition

    Lucas Parra;Paul Sajda

  • EEG-Informed fMRI Reveals Spatiotemporal Characteristics of Perceptual Decision Making

    Marios G. Philiastides;Paul Sajda

  • Linear Spatial Integration for Single-Trial Detection in Encephalography

    Lucas C. Parra;Christopher V. Alvino;Akaysha C. Tang;Barak A. Pearlmutter

  • Compact convolutional neural networks for classification of asynchronous steady-state visual evoked potentials

    Nicholas Waytowich;Vernon J Lawhern;Javier O Garcia;Javier O Garcia;Jennifer Cummings

  • Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain

    P. Sajda;S. Du;T.R. Brown;R. Stoyanova

  • Quantification of the Roles of Trabecular Microarchitecture and Trabecular Type in Determining the Elastic Modulus of Human Trabecular Bone

    Xiaowei S Liu;Paul Sajda;Punam K Saha;Felix W Wehrli

  • Response error correction-a demonstration of improved human-machine performance using real-time EEG monitoring

    L.C. Parra;C.D. Spence;A.D. Gerson;P. Sajda

  • Unmixing Hyperspectral Data

    Lucas C. Parra;Clay Spence;Paul Sajda;Andreas Ziehe

  • A data analysis competition to evaluate machine learning algorithms for use in brain-computer interfaces

    P. Sajda;A. Gerson;K.-R. Muller;B. Blankertz

  • In a Blink of an Eye and a Switch of a Transistor: Cortically Coupled Computer Vision

    P. Sajda;E. Pohlmeyer;Jun Wang;L.C. Parra

  • Detection, synthesis and compression in mammographic image analysis with a hierarchical image probability model

    C. Spence;L. Parra;P. Sajda

  • Spatiotemporal Linear Decoding of Brain State

    L.C. Parra;C. Christoforou;A.D. Gerson;M. Dyrholm

  • Intermediate-level visual representations and the construction of surface perception

    Paul Sajda;Leif H. Finkel

  • Cortical origins of response time variability during rapid discrimination of visual objects.

    Adam D. Gerson;Lucas C. Parra;Paul Sajda

  • Regulation of arousal via online neurofeedback improves human performance in a demanding sensory-motor task.

    Josef Faller;Jennifer Cummings;Sameer Saproo;Paul Sajda

Frequent Co-Authors

Lucas C. Parra
Lucas C. Parra City College of New York
Truman R. Brown
Truman R. Brown Medical University of South Carolina
Jean M. Vettel
Jean M. Vettel United States Army Research Laboratory
Shih-Fu Chang
Shih-Fu Chang Columbia University
George A. Bonanno
George A. Bonanno Columbia University
Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Roger Ratcliff
Roger Ratcliff The Ohio State University
Hauke R. Heekeren
Hauke R. Heekeren Universität Hamburg
Mark S. George
Mark S. George Medical University of South Carolina
Kevin N. Ochsner
Kevin N. Ochsner Columbia University

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