World's Best Scientists 2026 revealed!
Alexander Bertrand

Alexander Bertrand

D-Index & Metrics

Computer Science

D-Index
38
Citations
5156
World Ranking
10359
National Ranking
99

Electronics and Electrical Engineering

D-Index
38
Citations
5041
World Ranking
4976
National Ranking
108

Overview

Alexander Bertrand is affiliated with KU Leuven in Belgium. Their research spans multiple disciplines, with primary fields of study including Computer Science, Neuroscience, and Engineering.

Their work extensively covers subfields such as Cognitive Neuroscience, Signal Processing, Electrical and Electronic Engineering, Computer Networks and Communications, and Artificial Intelligence. Key topics in their research are EEG and Brain-Computer Interfaces, Blind Source Separation Techniques, Neural Dynamics and Brain Function, Advanced Memory and Neural Computing, Distributed Sensor Networks and Detection Algorithms, Indoor and Outdoor Localization Technologies, and Hearing Loss and Rehabilitation.

Frequent publication venues for their work include arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), IEEE Transactions on Signal Processing, Journal of Neural Engineering, and IEEE Journal of Biomedical and Health Informatics.

Alexander Bertrand has collaborated frequently with several coauthors, notably:

  • Simon Geirnaert
  • Tom Francart
  • Nicolas Heintz
  • Charles Hovine
  • Maarten De Vos

Among their recent papers are:

  • EEG-based detection of the locus of auditory attention with convolutional neural networks, 2021, eLife
  • Fast EEG-Based Decoding Of The Directional Focus Of Auditory Attention Using Common Spatial Patterns, 2020, IEEE Transactions on Biomedical Engineering
  • Change Point Detection in Time Series Data Using Autoencoders With a Time-Invariant Representation, 2021, IEEE Transactions on Signal Processing
  • Effect of number and placement of EEG electrodes on measurement of neural tracking of speech, 2021, PLoS ONE
  • Linear versus deep learning methods for noisy speech separation for EEG-informed attention decoding, 2020, Journal of Neural Engineering

Best Publications

  • Applications and trends in wireless acoustic sensor networks: A signal processing perspective

    Alexander Bertrand

  • Auditory-Inspired Speech Envelope Extraction Methods for Improved EEG-Based Auditory Attention Detection in a Cocktail Party Scenario

    Wouter Biesmans;Neetha Das;Tom Francart;Alexander Bertrand

  • A generic EEG artifact removal algorithm based on the multi-channel Wiener filter.

    Ben Somers;Tom Francart;Alexander Bertrand

  • Distributed Adaptive Node-Specific Signal Estimation in Fully Connected Sensor Networks—Part I: Sequential Node Updating

    Alexander Bertrand;Marc Moonen

  • EEG-Informed Attended Speaker Extraction From Recorded Speech Mixtures With Application in Neuro-Steered Hearing Prostheses

    Simon Van Eyndhoven;Tom Francart;Alexander Bertrand

  • EEG-based Auditory Attention Decoding: Towards Neuro-Steered Hearing Devices

    Simon Geirnaert;Servaas Vandecappelle;Emina Alickovic;Alain de Cheveigné

  • EEG-based detection of the locus of auditory attention with convolutional neural networks

    Servaas Vandecappelle;Lucas Deckers;Neetha Das;Amir Hossein Ansari

  • Diffusion Bias-Compensated RLS Estimation Over Adaptive Networks

    A. Bertrand;M. Moonen;A. H. Sayed

  • EEG-based auditory attention detection: boundary conditions for background noise and speaker positions.

    Neetha Das;Alexander Bertrand;Tom Francart

  • Optimal distributed minimum-variance beamforming approaches for speech enhancement in wireless acoustic sensor networks

    Shmulik Markovich-Golan;Alexander Bertrand;Marc Moonen;Sharon Gannot

  • Distributed Adaptive Node-Specific Signal Estimation in Fully Connected Sensor Networks—Part II: Simultaneous and Asynchronous Node Updating

    Alexander Bertrand;Marc Moonen

  • Distributed Adaptive Estimation of Node-Specific Signals in Wireless Sensor Networks With a Tree Topology

    A Bertrand;M Moonen

  • Robust distributed noise reduction in hearing aids with external acoustic sensor nodes

    Alexander Bertrand;Marc Moonen

  • Consensus-Based Distributed Total Least Squares Estimation in Ad Hoc Wireless Sensor Networks

    A Bertrand;M Moonen

  • Distributed Signal Processing for Wireless EEG Sensor Networks

    Alexander Bertrand

  • The effect of head-related filtering and ear-specific decoding bias on auditory attention detection.

    Neetha Das;Wouter Biesmans;Alexander Bertrand;Tom Francart

  • Distributed Node-Specific LCMV Beamforming in Wireless Sensor Networks

    A. Bertrand;M. Moonen

  • Seeing the Bigger Picture: How Nodes Can Learn Their Place Within a Complex Ad Hoc Network Topology

    A. Bertrand;M. Moonen

  • Distributed adaptive estimation of covariance matrix eigenvectors in wireless sensor networks with application to distributed PCA

    Alexander Bertrand;Marc Moonen

  • Distributed computation of the Fiedler vector with application to topology inference in ad hoc networks

    Alexander Bertrand;Marc Moonen

  • Electroencephalography-Based Auditory Attention Decoding: Toward Neurosteered Hearing Devices

    Simon Geirnaert;Servaas Vandecappelle;Emina Alickovic;Alain de Cheveigne

  • Applications and trends in wireless acoustic sensor networks : a signal processing perspectives

    Alexander Bertrand

Frequent Co-Authors

Marc Moonen
Marc Moonen KU Leuven
Ingrid Moerman
Ingrid Moerman Ghent University
Jan Wouters
Jan Wouters KU Leuven
Bart Nuttin
Bart Nuttin KU Leuven
Sharon Gannot
Sharon Gannot Bar-Ilan University
Edmund C. Lalor
Edmund C. Lalor University of Rochester
Michel M. Maharbiz
Michel M. Maharbiz University of California, Berkeley
Elad Alon
Elad Alon University of California, Berkeley
Jan M. Rabaey
Jan M. Rabaey University of California, Berkeley

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