Dr Karim Seghouane

  • Room: Level: 03 Room: 7
  • Building: Electrical and Electronic Engineering
  • Campus: Parkville

Research interests

  • Analysis of Physiological Signals
  • Biomedical Image Analysis
  • Statistical Signal and Image Processing

Biography

Dr. Karim Seghouane is an ARC Future Fellow in the Department of Electrical And Electronic Engineering at the University of Melbourne. He completed his PhD in Signal Processing and Control from Universite Paris Sud (Paris XI) in 2003.

Before Moving to the University of Melbourne, he was with NICTA (formaly National ICT Australia) Canberra Research Laboratory and the College of Engineering & Computer Science, Australian National University (ANU) from 2005 to 2012.

Recent publications

  1. Iqbal A, Seghouane A. A dictionary learning algorithm for multi-subject fMRI analysis based on a hybrid concatenation scheme. Digital Signal Processing: A Review Journal. Academic Press - Elsevier Science. 2018, Vol. 83. DOI: 10.1016/j.dsp.2018.09.007
  2. Desai N, Seghouane A, Palaniswami M. Algorithms for two dimensional multi set canonical correlation analysis. PATTERN RECOGNITION LETTERS. Elsevier Science. 2018, Vol. 111. DOI: 10.1016/j.patrec.2018.04.038
  3. Seghouane A, Iqbal A. Consistent adaptive sequential dictionary learning. Signal Processing. Elsevier Science. 2018, Vol. 153. DOI: 10.1016/j.sigpro.2018.07.018
  4. Seghouane A, Shokouhi N. Consistent Estimation of Dimensionality for Data-Driven Methods in fMRI Analysis. IEEE Transactions on Medical Imaging. IEEE - Institute of Electrical and Electronic Engineers. 2018. DOI: 10.1109/TMI.2018.2866640
  5. Zhou X, Seghouane A, Shah A, Innes-Brown H, Cross W, Litovsky R, McKay C. Cortical Speech Processing in Postlingually Deaf Adult Cochlear Implant Users, as Revealed by Functional Near-Infrared Spectroscopy. TRENDS IN HEARING. Sage Publications. 2018, Vol. 22. DOI: 10.1177/2331216518786850
  6. Nait-Meziane M, Abed-Meraim K, Seghouane A, Mesloub A. Hybrid Joint Diagonalization Algorithms. IEEE SIGNAL PROCESSING LETTERS. IEEE - Institute of Electrical and Electronic Engineers. 2018, Vol. 25, Issue 10. DOI: 10.1109/LSP.2018.2868408
  7. Seghouane A, Iqbal A. The adaptive block sparse PCA and its application to multi-subject FMRI data analysis using sparse mCCA. Signal Processing. Elsevier Science. 2018, Vol. 153. DOI: 10.1016/j.sigpro.2018.07.021
  8. Seghouane A, Shokouhi N. Two-Dimensional Whitening of Face Images for Improved PCA Performance. IEEE SIGNAL PROCESSING LETTERS. IEEE - Institute of Electrical and Electronic Engineers. 2018, Vol. 25, Issue 4. DOI: 10.1109/LSP.2018.2805308
  9. Seghouane A, Iqbal A. A REGULARIZED SEQUENTIAL DICTIONARY LEARNING ALGORITHM FOR FMRI DATA ANALYSIS. 2017 IEEE 27TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING. IEEE. 2017. Editors: Ueda N, Watanabe S, Matsui T, Chien JT, Larsen J.
  10. Iqbal A, Seghouane A. An approach for sequential dictionary learning in nonuniform noise. DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications. 2017, Vol. 2017-December. DOI: 10.1109/DICTA.2017.8227405
  11. Seghouane A, Iqbal A. Basis Expansion Approaches for Regularized Sequential Dictionary Learning Algorithms With Enforced Sparsity for fMRI Data Analysis. IEEE TRANSACTIONS ON MEDICAL IMAGING. IEEE - Institute of Electrical and Electronic Engineers. 2017, Vol. 36, Issue 9. DOI: 10.1109/TMI.2017.2699225
  12. Seghouane A, Iqbal A, Desai N. BSMCCA: A BLOCK SPARSE MULTIPLE-SET CANONICAL CORRELATION ANALYSIS ALGORITHM FOR MULTI-SUBJECT FMRI DATA SETS. 2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP). Institute of Electrical and Electronics Engineers. 2017. DOI: 10.1109/ICASSP.2017.7953373
  13. Seghouane A, Iqbal A. CSMSDL: A COMMON SEQUENTIAL DICTIONARY LEARNING ALGORITHM FOR MULTI-SUBJECT FMRI DATA SETS ANALYSIS. 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP). Institute of Electrical and Electronics Engineers. 2017, Vol. 2017-September. DOI: 10.1109/ICIP.2017.8297056
  14. Ubaru S, Saad Y, Seghouane A. Fast Estimation of Approximate Matrix Ranks Using Spectral Densities. NEURAL COMPUTATION. MIT Press. 2017, Vol. 29, Issue 5. DOI: 10.1162/NECO_a_00951
  15. Seghouane A, Shah A, Ting C-M. fMRI hemodynamic response function estimation in autoregressive noise by avoiding the drift. DIGITAL SIGNAL PROCESSING. Academic Press - Elsevier Science. 2017, Vol. 66. DOI: 10.1016/j.dsp.2017.04.006

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile