IJCNN Special Session on

Algorithms of Machine Learning and Artificial Intelligence Applied

for Biomedical Data Processing

IEEE International Joint Conference on Neural Networks (IJCNN)

July 18-22, 2021, Shenzhen, China (Virtual Event)


Scope and Aim

Biomedical data processing involves the treatment of the physiological electrical activities measured using sensors placed on a living thing and also the medical imaging, allowing to provide useful process for abnormality detection and diagnosis purposes. Recently, Artificial Intelligence (AI) and Machine Learning (ML) have received a great attention to solve difficult and complex problems related to biosignal and medical image processing; where the traditional signal/image processing algorithms and conventional machine learning techniques have shown their limitations to solve such problems. Indeed, the recent advances in this area have brought an impressive progress to solve several practical and difficult problems in many fields including medicine, healthcare, e-health, neuroscience, brain-computer interface (BCI), neurofeedback, robotics, robotic exoskeletons and biometrics, etc. In this context, the advanced artificial learning and ML techniques such as deep learning, reinforcement learning, deep reinforcement learning, statistical learning have shown their effectiveness to resolve various problems of detection, classification, clustering, segmentation, control, diagnosis, etc.; and thus, becomes useful solutions to be investigated more for other open problems.

The aim of this special session is to bring together researchers and scientists in the fields of biomedical signal and image processing, AI and ML, to present and discuss the recent advances on artificial learning/ML algorithms and methods applied for biomedical data processing.


The main topics that are of interest to this special session include, but are not limited to:

  • AI for biomedical signal and medical image processing
  • ML for biomedical signal and medical image processing
  • Feature engineering for ML applied for biomedical signal and medical image processing
  • Advanced algorithms of ML for biomedical data processing (e.g., deep learning, reinforcement learning, deep reinforcement learning, statistical learning...)
  • Biomedical data processing in Big Data
  • Advanced biomedical data processing methods with application in medicine, healthcare, e-health, neuroscience, BCI, neurofeedback, robotics, robotic exoskeletons, biometrics, etc.
  • Related applications

Important Dates

  • Paper Submissions: January 15, 2021 (Extended to February 10, 2021)
  • Decision notifications: April 15, 2021
  • Camera-ready submission of accepted papers: April 25, 2021
  • Conference: July 18-22, 2021 (Virtual Event)

Submission Guidelines

Journal Special Issue

A selection of accepted papers will be considered for publication in a special issue of a SCOPUS indexed journal (to be announced).


Larbi Boubchir (Lead Organizer)

Associate Professor, LIASD research Lab., Department of Computer Science, University of Paris 8, France

Boubaker Daachi (Co-organizer)

Professor, LIASD research Lab., Department of Computer Science, University of Paris 8, France


Larbi Boubchir (Lead Organizer) (BEng, MAS, PhD, HDR, SMIEEE) is Associate Professor of computer science at the University of Paris 8, France; within the department of Computer Science and LIASD research Lab. Before joining the University of Paris 8, he was researcher at the French National Centre for Scientific Research (CNRS), France, and then he held a research fellow position at Northumbria University at Newcastle, U.K., within the department of Computer and Information Sciences. His research interests include: biomedical signal processing, image processing, biomedical engineering, brain-computer-interfaces, machine learning and biometrics. He has authored and co-authored more than 80 publications. He has served as a reviewer, TPC member, technical program committee chair, program chair, area chair, organizing committee member and steering committee member for many international conferences, and reviewed papers for several journals including IEEE Transactions, Elsevier, IET, Springer and MDPI. He serves as an Associate Editor for IEEE Access journal, Journal of Biomedical Research, Journal of Medical and Biological Engineering, CAAI Transactions on Intelligence Technology and Emerging Science Journal. He is also Editorial Board member for the journal of Applied Computing, Bioengineering, Informatics and BMC Biomedical Engineering. He is the organiser and chair of the International Workshop on Machine Learning for EEG Signal Processing, and the International Workshop on Recent Advances in Biometrics and its Applications. He serves, has served, as Guest Editor of special issues for Pattern Recognition Letters, Journal of Biomedical Research, Electronics, Computers and Bioengineering journals. Dr. Boubchir is a Senior Member of IEEE. He is also a member of IEEE SPS, IEEE EMBS, IEEE Computer Society, IEEE SMC Society, IEEE Biometrics Council, IARP and AFRIF.

Boubaker Daachi is full professor of computer science at the university of Paris 8. He received the B.S. degree in computer science from the University of Sétif, Algeria (1995), the M.S. degree in robotics from the University of Paris 6, France (1998), and the Ph.D. degree in robotics from the University of Versailles, France (2000). He was an Associate Professor of robotics and computer science at the university of Paris Est Créteil, from September 2003 to August 2014. He evolved as a Researcher at CNRS-AIST JRL, Tsukuba, Japan, from September 2014 to August 2015. His research interests include soft computing and BCI. Application fields are robotics, biometrics, pervasive and distributed systems. He has published more than 70 papers in scientific journals, books, and conference proceedings. He has been involved in the organizing committees of some national and international events.


Larbi Boubchir : larbi.boubchir [at] univ-paris8.fr

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