Akram Bennour | Biometrics | Outstanding Scientist Award

Dr. Akram Bennour | Biometrics | Outstanding Scientist Award

Echahid cheikh Larbi Tebessi University, Algeria

👨‍🎓Professional Profile

🏫 Current Position and Academic Leadership

Dr. Akram Bennour has been an Associate Professor in the Computer Science Department at the University of Tebessa, Algeria, since 2009. Throughout his tenure, he has led several academic and research initiatives, significantly shaping the university’s research output. Notably, he has served as the Vice-Rector in charge of Scientific Research and International Cooperation (2012-2014) and Deputy Vice-Rector for higher education and continuing education (2019). Additionally, he holds leadership roles in various committees, including scientific and disciplinary bodies, reflecting his influence within the academic governance structure of the university.

📚 Early Academic Pursuits and Education

Dr. Bennour’s academic journey began with his Bachelor’s degree in Computer Science (2004) from the University of Mantouri, Constantine. He then completed a Magistere in Computer Science at the University of Tebessa in 2009, followed by a Doctorate in Computer Science from the University of Annaba in 2015. His commitment to advanced research led him to earn his Habilitation degree in 2019 from the University of Oum-el-Bouaghi, Algeria, marking a pivotal moment in his academic career.

🔍 Contributions and Research Focus

Dr. Bennour’s research spans across multiple areas, emphasizing nature-inspired metaheuristics, evolutionary computation, machine learning, artificial intelligence, and pattern recognition. His work delves deeply into image processing, especially in the contexts of satellite imagery, handwriting, and medical imaging. His contributions have significantly impacted AI and computational methods applied to medical diagnostics, such as his recent focus on early detection of neural diseases through handwriting analysis (2022-2025) and pulmonary disease diagnosis (2023-2026).

He has been actively involved in various research projects, including:

  • Multi-Temporal Analysis of Images and Data Processing (2010-2013)
  • Knowledge Extraction and Analysis (2013-2016)
  • Data Protection within Electronic Administration (2020-2023)

🌍 Professional Endeavors and Global Impact

Dr. Bennour’s influence extends beyond academia. He serves as an editorial leader and guest editor for several prestigious journals, including Springer’s Pattern Recognition Letters and SNCS Special Issues, focusing on machine learning and pattern recognition. His editorial leadership has contributed to advancing research in these fields and providing a platform for global research collaborations.

Additionally, he plays an instrumental role in organizing international conferences, such as the Springer International Conference on Intelligent Systems and Pattern Recognition (ISPR), where he has served as General Chair multiple times. These roles underscore his commitment to fostering global research dialogues and knowledge exchange.

📖 Teaching Experience and Mentorship

Dr. Bennour has an extensive teaching portfolio, reflecting his dedication to educating the next generation of computer scientists. His teaching spans various critical topics, including:

  • Artificial Intelligence
  • Computer Vision
  • Data Structures and Algorithms
  • Operating Systems and Security

He has taught both undergraduate and graduate courses since 2009, with his courses focusing on hands-on programming languages (e.g., Python, C++, MATLAB) and technical areas such as machine learning, image processing, and network security. His passion for teaching is evident in his role as Head of Master’s and Bachelor’s programs at the University of Tebessa, where he has shaped the curriculum to align with current industry needs.

⚙️ Technical Skills and Expertise

Dr. Bennour is highly skilled in a range of technical areas, including:

  • Programming Languages: SQL Server, MATLAB, Python, C++, PHP/MySQL, Pascal
  • AI & Machine Learning: Expertise in pattern recognition, image analysis, and biometrics
  • System Administration: Proficient in Windows, Unix, and VMware environments
  • Data Protection & Security: Advanced skills in backup systems, Exchange servers, and Active Directory management

His interdisciplinary expertise positions him as an authority in combining AI technologies with practical applications, especially in medical diagnostics and cybersecurity.

🌟 Legacy and Future Contributions

Dr. Bennour’s contributions to both academia and industry are profound, particularly in the application of AI for real-world problems. His research continues to shape the landscape of intelligent systems, and his leadership in international conferences and journals ensures that his influence remains global. As he continues his work on early disease detection and advanced AI applications, his future contributions are likely to have significant societal impacts, particularly in healthcare and medical technology.

📈 Academic Influence and Citations

Dr. Bennour’s extensive body of research has contributed to the growing body of literature in his fields of expertise. Through his publications and editorial roles, he has advanced the academic discourse surrounding AI, machine learning, image processing, and pattern recognition. His work on pattern recognition, especially in medical contexts, is frequently cited and serves as a foundation for other scholars in related fields.

🌐 Professional Memberships and Global Networks

Dr. Bennour is an active member of several international academic communities. His roles as General Chair for the ISPR conferences and his participation in organizing multiple international conferences demonstrate his commitment to fostering global collaboration and advancing research in intelligent systems and pattern recognition. His editorial work further solidifies his position as a key figure in the academic and research community.

📖Top Noted Publications

Channel and Spatial Attention in Chest X-Ray Radiographs: Advancing Person Identification and Verification with Self-Residual Attention Network
    • Authors: H. Farah, A. Bennour, N. A. Kurdi, S. Hammami, M. Al-Sarem
    • Journal: Diagnostics
    • Year: 2024
An innovative framework to securely transfer data through the Internet of Things using advanced generative adversarial networks
    • Authors: A. Bennour, M. Elhoseny, B. D. Veerasamy, R. Bhatt, A. Agrawal, P. K. Shukla, et al.
    • Journal: Journal of High Speed Networks
    • Year: 2024
Unveiling Parkinson’s: Handwriting Symptoms with Explainable and Interpretable CNN Model
    • Authors: A. Zemmar, A. Bennour, M. Tahar, F. Ghabban, M. Al-Sarem
    • Journal: International Journal of Pattern Recognition and Artificial Intelligence
    • Year: 2024
Park-Net: A Deep Model for Early Detection of Parkinson’s Disease Through Automatic Analysis of Handwriting
    • Authors: A. Bennour, T. Mekhaznia
    • Journal: SN Computer Science
    • Year: 2024
Beyond Traditional Biometrics: Harnessing Chest X-Ray Features for Robust Person Identification
  • Authors: F. Hazem, B. Akram, T. Mekhaznia, F. Ghabban, A. Alsaeedi, B. Goyal
  • Journal: Acta Informatica Pragensia
  • Year: 2024

Jing An | Artificial Intelligence | Best Researcher Award

Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

👨‍🎓Professional Profile

Scopus Profile

👨‍🏫 Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

🎓 Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Master’s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

💼 Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships 🚀.

📚 Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

🔧 Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

🧑‍🏫 Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

🔍 Research Interests

Dr. An’s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

📖Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020