World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
77
Citations
28610
World Ranking
1250
National Ranking
665

Electronics and Electrical Engineering

D-Index
59
Citations
12609
World Ranking
1769
National Ranking
707

Research.com Recognitions

  • 2009 - IEEE Fellow For contributions to nonlinear and complex-valued statistical signal processing
  • 2008 - Fellow of the Indian National Academy of Engineering (INAE)

Overview

Tulay Adali is a researcher affiliated with the University of Maryland, Baltimore County in the United States. Their work spans multiple areas within neuroscience and signal processing, focusing primarily on cognitive neuroscience and advanced neuroimaging techniques. Their publication record includes significant contributions to understanding neural dynamics, functional brain connectivity, and the application of tensor decomposition methods to brain data analysis.

The scientist has authored papers in various peer-reviewed journals and conference venues. Some recent publications include:

  • Space: A Missing Piece of the Dynamic Puzzle, 2020, Trends in Cognitive Sciences
  • Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fMRI datasets, 2023, Human Brain Mapping
  • Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness, 2022, IEEE Signal Processing Magazine
  • Independent vector analysis for common subspace analysis: Application to multi-subject fMRI data yields meaningful subgroups of schizophrenia, 2020, NeuroImage
  • Reproducibility and replicability in neuroimaging data analysis, 2022, Current Opinion in Neurology

Their research covers a range of topics, including:

  • Functional Brain Connectivity Studies
  • Blind Source Separation Techniques
  • Neural dynamics and brain function
  • EEG and Brain-Computer Interfaces
  • Advanced Neuroimaging Techniques and Applications
  • Tensor decomposition and applications
  • Muscle activation and electromyography studies

Tulay Adali's primary fields of study are:

  • Neuroscience

The subfields they have contributed to include:

  • Cognitive Neuroscience
  • Signal Processing
  • Radiology, Nuclear Medicine and Imaging
  • Artificial Intelligence
  • Computational Mathematics

Frequent publication venues for their work are:

  • IEEE Signal Processing Magazine
  • IEEE Journal of Selected Topics in Signal Processing
  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Sensors

They have collaborated extensively with several coauthors, including:

  • Vince D. Calhoun
  • Ben Gabrielson
  • Athina P. Petropulu
  • M. A. B. S. Akhonda
  • Ahmed H. Tewfik

Tulay Adali has received recognition through awards such as:

  • IEEE Fellow in 2009 for contributions to nonlinear and complex-valued statistical signal processing
  • Fellow of the Indian National Academy of Engineering (INAE) in 2008

Best Publications

  • A method for making group inferences from functional MRI data using independent component analysis

    V.D. Calhoun;T. Adali;G.D. Pearlson;J.J. Pekar;J.J. Pekar

  • The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery

    Vince D. Calhoun;Vince D. Calhoun;Robyn Miller;Godfrey Pearlson;Tulay Adalı

  • A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data.

    Vince D. Calhoun;Jingyu Liu;Jingyu Liu;Tülay Adalı

  • Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects

    Dana Lahat;Tulay Adali;Christian Jutten

  • Estimating the number of independent components for functional magnetic resonance imaging data.

    Yi Ou Li;Tülay Adali;Vince D. Calhoun

  • Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms.

    V.D. Calhoun;T. Adali;G.D. Pearlson;J.J. Pekar;J.J. Pekar

  • Comparison of multi-subject ICA methods for analysis of fMRI data.

    Erik Barry Erhardt;Srinivas Rachakonda;Edward J. Bedrick;Elena A. Allen

  • Multisubject Independent Component Analysis of fMRI: A Decade of Intrinsic Networks, Default Mode, and Neurodiagnostic Discovery

    V. D. Calhoun;T. Adali

  • Complex-Valued Signal Processing: The Proper Way to Deal With Impropriety

    T. Adali;P. J. Schreier;L. L. Scharf

  • A review of multivariate methods for multimodal fusion of brain imaging data

    Jing Sui;Tülay Adali;Qingbao Yu;Jiayu Chen

  • Joint Blind Source Separation by Multiset Canonical Correlation Analysis

    Yi-Ou Li;T. Adali;Wei Wang;V.D. Calhoun

  • Unmixing fMRI with independent component analysis

    V.D. Calhoun;T. Adali

  • fMRI activation in a visual-perception task: network of areas detected using the general linear model and independent components analysis.

    Vince D. Calhoun;Tülay Adali;V. B. McGinty;James J. Pekar;James J. Pekar

  • Different activation dynamics in multiple neural systems during simulated driving.

    Vince D. Calhoun;James J. Pekar;James J. Pekar;Vince B. McGinty;Tulay Adali

  • Canonical Correlation Analysis for Data Fusion and Group Inferences

    Nicolle M Correa;Tülay Adali;Yi-Ou Li;Vince D Calhoun

  • Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data.

    Vince D. Calhoun;T. Adali;N. R. Giuliani;J. J. Pekar;J. J. Pekar

  • Approximation by fully complex multilayer perceptrons

    Taehwan Kim;Tülay Adali

  • Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+ joint ICA model.

    Jing Sui;Godfrey D. Pearlson;Arvind Caprihan;Tülay Adali

  • A Complex Generalized Gaussian Distribution— Characterization, Generation, and Estimation

    M. Novey;T. Adali;A. Roy

  • Patterns of gray matter abnormalities in schizophrenia based on an international mega-analysis

    Unknown

  • ICA of functional MRI data: an overview.

    Vince D. Calhoun;Tülay Adali;Lars Kai Hansen;Jan Larsen

Frequent Co-Authors

Vince D. Calhoun
Vince D. Calhoun Georgia State University
Godfrey D. Pearlson
Godfrey D. Pearlson Yale University
James J. Pekar
James J. Pekar Kennedy Krieger Institute
Jing Sui
Jing Sui Beijing Normal University
Yue Wang
Yue Wang Zhejiang University
Curtis R. Menyuk
Curtis R. Menyuk University of Maryland, Baltimore County
Kent A. Kiehl
Kent A. Kiehl University of New Mexico
Tom Eichele
Tom Eichele Haukeland University Hospital
Jan Larsen
Jan Larsen Technical University of Denmark
Christian Jutten
Christian Jutten Grenoble Alpes University

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