Prof. Larbi Boubchir, University of Paris 8, France
Prof. Larbi Boubchir appears to be a strong candidate for the “Research for Best Researcher Award” based on several key factors:
Publication profile
Academic and Professional Achievements
Prof. Boubchir is a Full Professor of Computer Science at the University of Paris 8, France, where he has held multiple significant roles, including Deputy Director of the LIASD laboratory and Head of the IUSD research group. His academic background includes a Ph.D. in Signal and Image Processing and an HDR degree in Computer Science, showcasing a solid foundation in his field.
Research Expertise
His research interests are diverse and highly relevant, covering artificial intelligence, biometrics, biomedical signal processing, and image processing. His expertise in advanced areas such as machine learning, deep learning, and feature engineering, coupled with practical applications in biometric security and health-related fields, highlights his significant contributions to cutting-edge technology.
PublicationĀ
- Analytical form for a Bayesian wavelet estimator of images using the Bessel K form densities š – Cited by 155, 2005
- Faceāiris multimodal biometric identification system šµļøāāļø – Cited by 104, 2020
- Multi-spectral palmprint recognition based on oriented multiscale log-Gabor filters ā – Cited by 89, 2016
- Multivariate statistical modeling of images with the curvelet transform š – Cited by 79, 2005
- A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with ā¦ ā±ļø – Cited by 74, 2012
- A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate Ī±-stable prior š – Cited by 64, 2006
- Wavelet Denoising Based on the MAP Estimation Using the BKF Prior With Application to Images and EEG Signals š§ – Cited by 57, 2013
- EEG epileptic seizure detection and classification based on dual-tree complex wavelet transform and machine learning algorithms ā” – Cited by 50, 2020
- A review of feature extraction for EEG epileptic seizure detection and classification š¬ – Cited by 49, 2017
- Epileptic seizure prediction based on EEG spikes detection of ictal-preictal states š – Cited by 45, 2020
- Robust model-free gait recognition by statistical dependency feature selection and globality-locality preserving projections š¶āāļø – Cited by 39, 2016
- Human gait recognition based on Haralick features š¶āāļø – Cited by 38, 2017
- Faceāiris multi-modal biometric system using multi-resolution Log-Gabor filter with spectral regression kernel discriminant analysis šø – Cited by 37, 2018
- Palm vein recognition based on competitive coding scheme using multi-scale local binary pattern with ant colony optimization šļø – Cited by 36, 2020
- Human gait recognition using GEI-based local multi-scale feature descriptors šŗ – Cited by 36, 2019
Awards and Recognition
He has received several prestigious awards, including IEEE Access Outstanding Associate Editor accolades and Best Paper awards at international conferences. These honors reflect his high impact and recognition in the research community.
Leadership and Teaching
In addition to his research, Prof. Boubchir has made substantial contributions to education as the head of Masterās programs in Cyber Security, Data Science, and Big Data. His leadership in these programs demonstrates his commitment to advancing knowledge and mentoring future professionals.
Conclusion
Prof. Boubchirās extensive research contributions, leadership roles, and accolades make him a highly suitable candidate for the Research for Best Researcher Award.