Larbi Boubchir | Deep Anomaly Detection in Blockchain | Best Scholar Award

Prof. Larbi Boubchir | Deep Anomaly Detection in Blockchain | Best Scholar Award 

Professor | University of Paris 8 | France

Based on the detailed profile of Prof. Dr. Larbi Boubchir, here is an analysis of his suitability for the Research for Best Scholar Award, focusing on his strengths, areas for improvement, and a concluding assessment.

Strengths

  1. Extensive Research Contributions: Prof. Boubchir has authored and co-authored over 100 publications, which highlights his prolific output and active engagement in research. His work spans a broad range of topics including artificial intelligence, biometrics, biomedical signal processing, and image processing, demonstrating significant expertise across multiple domains.
  2. Leadership and Organizational Roles: He holds several prominent positions, such as Full Professor, Deputy Director of LIASD, and Head of multiple Master’s programs. His roles in organizing and chairing international workshops and conferences further illustrate his leadership and influence in the academic community.
  3. Recognition and Awards: His achievements include being recognized as an Outstanding Associate Editor by IEEE Access, receiving Best Paper and Best Poster awards, and contributing to notable international research projects. These accolades reflect the high quality and impact of his research.
  4. Diverse Teaching Experience: Prof. Boubchir has a robust teaching background, covering various levels and subjects in computer science, signal and image processing, and artificial intelligence. His pedagogical responsibilities and contributions to curriculum development at several institutions underscore his commitment to education.
  5. Multidisciplinary Research: His work in areas like biometric recognition, biomedical signal processing, and artificial intelligence for cybersecurity highlights his interdisciplinary approach and innovative contributions to multiple fields.

Areas for Improvement

  1. Interdisciplinary Collaboration: While Prof. Boubchir’s research is broad, further collaboration with researchers from different disciplines could enhance the application and impact of his work. For example, integrating perspectives from cognitive sciences or behavioral studies might enrich his research in biometrics and artificial intelligence.
  2. Involvement in Emerging Technologies: Although his research is cutting-edge, staying abreast of emerging technologies such as quantum computing or new AI paradigms could provide additional opportunities for groundbreaking research and keep his work at the forefront of technological advancements.
  3. Increased Focus on Applied Research: While his theoretical and methodological contributions are significant, emphasizing applied research that directly addresses real-world problems and demonstrates practical outcomes could enhance the societal impact of his work.

Short Biography

Prof. Dr. Larbi Boubchir is a distinguished Full Professor of Computer Science at the University of Paris 8, France. With a notable career spanning several institutions, including CNRS and Northumbria University, he has made significant contributions to the fields of artificial intelligence, biometrics, and biomedical signal processing. His role as Deputy Director of the LIASD laboratory and Head of multiple Master’s programs underscores his leadership and influence in both research and education. Prof. Boubchir’s extensive experience in organizing international workshops and conferences further highlights his active engagement with the global academic community.

Profile

ORCID

Education

Prof. Boubchir earned his PhD in Signal and Image Processing from the University of Caen-Basse Normandie in 2007, following a Master of Advanced Studies in Computer Science from Polytech’Tours, University of François-Rabelais, Tours, in 2002. In 2019, he completed his Habilitation à Diriger des Recherches (HDR) at the University of Paris 8, which qualifies him to supervise doctoral research in Computer Science.

Experience

Prof. Boubchir has held numerous academic positions throughout his career. He has been a Full Professor at the University of Paris 8 since 2021, where he also serves as Deputy Director of the LIASD research lab and heads several Master’s programs. Prior to this, he was an Associate Professor at the same institution and held research fellowships at Northumbria University, CNRS, and Qatar University. His diverse teaching experience spans institutions in France, the UK, and Qatar, and includes a range of subjects from computer programming to artificial intelligence.

Research Interests

Prof. Boubchir’s research interests encompass biometrics, artificial intelligence, biomedical signal processing, and image processing. His work involves developing algorithms for biometric recognition, feature engineering, and deep learning applications in biomedical data analysis. He is particularly focused on applications such as biometric authentication, epilepsy detection, and brain-computer interfaces. His interdisciplinary approach combines advanced machine learning techniques with practical applications in security and healthcare.

Awards

Prof. Boubchir has received several prestigious awards, including IEEE Access Outstanding Associate Editor honors (2020, 2021, 2023) and the Best Paper award at the 39th International Conference on Telecommunications and Signal Processing (2016). He also won the Best Poster Award at the 9th International Conference on Software Defined Systems (2022) and achieved recognition for his top papers at IEEE conferences.

Publications

Here are some of Prof. Boubchir’s notable publications:

A Review on Deep Anomaly Detection in Blockchain (2024), Blockchain: Research and Applications.

Enhancing 2D-3D Facial Recognition Accuracy of Truncated-Hidden Faces Using Fused Multi-Model Biometric Deep Features (2024), Multimedia Tools and Applications.

Deep Speech Recognition System Based on AutoEncoder-GAN for Biometric Access Control (2023), International Journal of Advanced Computer Science and Applications (IJACSA).

Efficient Multiplier-Less Parametric Integer Approximate Transform Based on 16-Points DCT for Image Compression (2022), Multimedia Tools and Applications.

Lossy Image Compression Based on Efficient Multiplier-Less 8-Points DCT (2022), Multimedia Systems.

EEG Signal Feature Extraction and Classification for Epilepsy Detection (2022), Informatica.

Detecting African Hoofed Animals in Aerial Imagery Using Convolutional Neural Network (2021), IAES International Journal of Robotics and Automation.

Palm Vein Recognition Based on Competitive Coding Scheme Using Multi-Scale Local Binary Pattern with Ant Colony Optimization (2020), Pattern Recognition Letters.

A Novel and Efficient 8-Point DCT Approximation for Image Compression (2020), Multimedia Tools and Applications.

EEG Epileptic Seizure Detection and Classification Based on Dual-Tree Complex Wavelet Transform and Machine Learning Algorithms (2020), Journal of Biomedical Research.

Conclusion

Prof. Dr. Larbi Boubchir is highly suitable for the Research for Best Scholar Award. His impressive research portfolio, leadership roles, teaching contributions, and recognition from the academic community illustrate his exceptional qualifications. His diverse expertise and significant impact in fields such as artificial intelligence, biometrics, and biomedical signal processing make him a strong candidate for this award. To further strengthen his profile, focusing on interdisciplinary collaborations, emerging technologies, and applied research could provide additional avenues for innovation and impact. Overall, Prof. Boubchir’s accomplishments and contributions make him a distinguished candidate deserving of recognition.

Sajad Zandi | Distributed Network | Best Researcher Award

Mr. Sajad Zandi | Distributed Network | Best Researcher Award

Mr. Sajad Zandi ,University of technology Sydney, Australia

Sajad Zandi is affiliated with the University of Technology Sydney in Australia. He specializes in [mention his field or area of expertise, if known]. With a background in [mention any relevant educational or professional background], Mr. Zandi contributes to [mention any notable contributions or areas of focus]. His research interes

Profile

Scopus

Education:

Master of Electrical Engineering – Telecommunication,Malayer University, Hamadan, Iran,Sep. 2014 – Sep. 2017,GPA: 17.33 out of 20,Bachelor of Telecommunication Engineering (Transmission),Safahan Institute of Higher Education, Esfahan, Iran,Sep. 2009 – Jul. 2011,GPA: 16.76 out of 20,Associate of Telecommunication – Data Communication,Hormozgan University, Hormozgan, Iran,Jan. 2007 – Sep. 2009,GPA: 16.30 out of 20

Experience:

Researcher, R&D Department,SINA Innovative Communications System Company, Tehran, Iran,Dec. 2021 – Present,Technical Project Manager,Nokia-OM International Company, Tehran, Iran,Nov. 2017 – Dec. 2019,Researcher,Nabius International Institution, Esfahan, Iran,Jul. 2011 – Sep. 2014

Research Focus:

Your recent research collaborations are primarily focused on:,Diffusion algorithms in signal processing,Adaptive filters for sparse system identification over distributed networks,Demand-side management algorithms,Robust algorithms for impulsive noise environments

Skills:

Operating Systems: Proficient in Microsoft Windows and Linux,Programming Languages: C, C++, Java, Matlab, R, Python,Scientific Software: LabVIEW,Signal Processing: Deep learning, machine learning, computer vision,Other Skills: Technical project management, wireless network administration

Awards:

  • Reviewing Journal of Signal Processing Award (Mar. 2023)
  • TOEFL iBT (home edition): Overall score 102 (Dec. 2021)

 publications:

    • You have several publications in reputable journals, including IEEE Transactions and Springer journals, focusing on various aspects of signal processing, adaptive filters, and demand-side management algorithms.

    References:

    • Dr. Mehdi Korki
      • Senior Researcher, School of Science, Swinburne University of Technology, Australia
      • Email: mkorki@swin.edu.au
    • Dr. Vahideh Montazeri
      • Assistant Professor, Department of Artificial Intelligence, Smart University of Medical Sciences, Tehran, Iran