Mebarka Allaoui | Machine Learning and AI Applications | Best Paper Award

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Dr. Mebarka Allaoui | Machine Learning and AI Applications | Best Paper Award

Bishop’s University | Canada

Dr. Mebarka Allaoui dedicated computer science researcher with a strong background in machine learning, manifold learning, and computer vision, this scholar holds a PhD in Computer Science focused on embedding techniques and their applications to visual data analysis. Their academic journey includes a master’s degree in industrial computer science and a bachelor’s degree in information systems, all completed with high distinction. Professionally, they have served as a Postdoctoral Fellow contributing to industry-funded research on anomaly detection, developing novel embedding, deep learning, and clustering methods to enhance the interpretability of latent representations and improve fraud detection in real-world financial datasets. Prior experience includes working as a computer engineer supporting system administration, software development, data analysis, and network configuration, alongside several teaching appointments delivering practical courses in software engineering, algorithmics, and web development. Their research contributions span dimensionality reduction, clustering, optimization, document analysis, and scientific information retrieval, with publications in reputable journals and conferences. Collaborative work further extends to studies on optimizers, object detection, and embedding initialization strategies. Recognized for high-quality academic performance and impactful research outputs, they continue to advance data-driven methodologies, aiming to bridge theoretical innovation with practical applications in intelligent systems and decision-support technologies.

Profile : Google Scholar

Featured Publications

Allaoui, M., Kherfi, M. L., & Cheriet, A. (2020). “Considerably improving clustering algorithms using UMAP dimensionality reduction technique” in International Conference on Image and Signal Processing, 317–325.

Drid, K., Allaoui, M., & Kherfi, M. L. (2020). “Object detector combination for increasing accuracy and detecting more overlapping objects” in International Conference on Image and Signal Processing, 290–296.

Allaoui, M., Belhaouari, S. B., Hedjam, R., Bouanane, K., & Kherfi, M. L. (2025). “t-SNE-PSO: Optimizing t-SNE using particle swarm optimization” in Expert Systems with Applications, 269, 126398.

Allaoui, M., Kherfi, M. L., Cheriet, A., & Bouchachia, A. (2024). “Unified embedding and clustering” in Expert Systems with Applications, 238, 121923.

Allaoui, M., Kherfi, M. L., & Cheriet, A. (2020). “International Conference on Image and Signal Processing” in Springer.

Abdelouahad Achmamad | Engineering | Best Researcher Award

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Dr. Abdelouahad Achmamad | Engineering | Best Researcher Award

Universite De Mans | France

Dr. Abde Louahad Achmamad is an embedded software engineer and researcher specializing in intelligent systems, AI algorithms, biomedical signal processing, and advanced embedded technologies for electrical, biomedical, and IoT applications. He holds a PhD in Electrical Engineering, complemented by master’s degrees in biomedical engineering and electrical/electronic engineering, supported by earlier qualifications in electromechanics and electronics. His professional experience spans biomedical R&D, embedded system design, AI-based medical diagnostics, MRI segmentation, IoT health monitoring, wearable sensor development, and security applications for STM32 microcontrollers. He has worked with leading institutions and companies across France and Morocco, including STMicroelectronics, Akkodis, Diabtech, Université de Rouen, ENSIAS, and multiple research laboratories. His scientific output includes 102 citations by 95 documents, 16 publications, and an h-index of 6, reflecting contributions in EMG-based diagnostics, phonoangiography, neuromuscular disorder detection, sensor fusion, and few-shot learning for medical imaging. He has also reviewed more than 200 scientific manuscripts for major journals from Springer, Elsevier, and MDPI, demonstrating recognized expertise in signal processing and embedded systems. His research interests include embedded AI, biomedical instrumentation, wearable sensors, IoT-based healthcare, security-focused embedded design, and intelligent diagnostic systems. Dr. Achmamad remains dedicated to advancing high-impact engineering solutions that enhance healthcare, sensing technologies, and intelligent embedded platforms.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Achmamad, A., & Jbari, A. (2020). A comparative study of wavelet families for electromyography signal classification based on discrete wavelet transform. Bulletin of Electrical Engineering and Informatics.

Achmamad, A., Belkhou, A., & Jbari, A. (2020). Fast automatic detection of amyotrophic lateral sclerosis disease based on Euclidean distance metric. In 2020 International Conference on Electrical and Information Technologies .

Belkhou, A., Achmamad, A., & Jbari, A. (2019). Classification and diagnosis of myopathy EMG signals using the continuous wavelet transform. In 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science .

Belkhou, A., Achmamad, A., & Jbari, A. (2019). Myopathy detection and classification based on the continuous wavelet transform. Journal of Communications Software and Systems.

Abdelouahad, A., Belkhou, A., Jbari, A., & Bellarbi, L. (2018). Time and frequency parameters of sEMG signal–force relationship. In 2018 International Conference on Optimization and Applications .

Decheng Li | Engineering | Best Researcher Award

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Mr. Decheng Li | Engineering | Best Researcher Award

Lanzhou University of Technology | China

Dr. Decheng Li is a dedicated scholar and researcher at the School of Automation and Electrical Engineering, Lanzhou University of Technology, China. He obtained his academic training in electrical engineering and automation, focusing on intelligent control systems, robotics, and power electronics. With extensive teaching and research experience, Dr. Li has contributed significantly to the advancement of automation technologies and intelligent systems applications in industrial environments. His research interests encompass intelligent control theory, optimization algorithms, renewable energy integration, and advanced signal processing techniques for control systems. Dr. Li has authored and co-authored numerous papers in leading international journals and conferences, reflecting his commitment to academic excellence and technological innovation. He has been involved in several national and provincial research projects, fostering collaboration between academia and industry. In recognition of his contributions, Dr. Li has received multiple academic awards and honors for his outstanding research and teaching performance. He continues to mentor graduate students and promote interdisciplinary research to solve real-world engineering challenges. Dr. Li remains committed to advancing automation and intelligent systems for sustainable industrial development and the future of smart technologies.

Profile: Orcid

Featured Publication

Liu, J., Li, D., & Chen, H. (2025). “Robust hybrid decentralized controller design for Voice Coil Actuator-Fast Steering Mirror system in high-precision optical measurements.

Qing Zhang | Innovation in Data Analysis | Best Researcher Award

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Prof. Qing Zhang | Innovation in Data Analysis | Best Researcher Award

Sun Yat-sen University, China

PUBLICATION PROFILE

Orcid

INNOVATOR IN DATA ANALYSIS: PROF. QING ZHANG – SUN YAT-SEN UNIVERSITY, CHINA 📊✨

📘 INTRODUCTION

Prof. Qing Zhang, a distinguished scholar from Sun Yat-sen University in China, is a visionary in the field of data analysis and innovation. Renowned for her methodical approach and pioneering techniques, she has significantly advanced the landscape of data-driven research in China and beyond. Her work represents the fusion of mathematical theory and real-world application, making her an influential figure in today’s digital and data-intensive era.

🎓 EARLY ACADEMIC PURSUITS

Prof. Zhang’s academic journey began with a passion for mathematics and computational science. Her foundational education, marked by excellence and curiosity, paved the way for advanced studies in statistical modeling and data interpretation. She pursued rigorous training at top institutions, developing a robust understanding of both theoretical and applied dimensions of data analysis.

🧑‍🏫 PROFESSIONAL ENDEAVORS

Upon joining Sun Yat-sen University, Prof. Zhang quickly emerged as a leading academic voice in the realms of data science and analytics. As a professor and mentor, she has guided numerous students and research teams, establishing a culture of innovation and critical thinking. Her teaching combines technical depth with practical relevance, inspiring the next generation of data analysts and scientists.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

Prof. Zhang’s research bridges the gap between algorithmic design and societal needs. Her focus areas include large-scale data mining, predictive analytics, machine learning algorithms, and interdisciplinary data applications. She has contributed to the development of novel methodologies for real-time data processing, high-dimensional statistics, and intelligent systems that address challenges in healthcare, finance, and smart cities.

🌍 IMPACT AND INFLUENCE

Prof. Zhang’s innovations have had wide-reaching effects, not just in academic circles but also in industrial collaborations and government-led data initiatives. Her models and frameworks have been implemented to enhance decision-making processes, improve public health monitoring systems, and support policy formulation with actionable insights. She remains a key contributor to the ongoing digital transformation in China.

📚 ACADEMIC CITATIONS AND PUBLICATIONS

A prolific author, Prof. Zhang has published over 100 peer-reviewed articles in high-impact international journals and conference proceedings. Her work is frequently cited in fields such as artificial intelligence, computational statistics, and systems engineering. She also serves as a reviewer and editorial board member for esteemed journals in data science, reflecting her status as a trusted authority in the field.

🏅 HONORS & AWARDS

Prof. Zhang has received numerous accolades in recognition of her scholarly excellence and innovative contributions. These include national awards for scientific progress, best paper awards from top-tier conferences, and prestigious research grants supporting frontier data science projects. Her leadership is also recognized through invited talks and keynote addresses at major international forums.

🧠 LEGACY AND FUTURE CONTRIBUTIONS

Prof. Zhang’s legacy is defined by her relentless pursuit of knowledge, mentorship, and a commitment to societal advancement through data. She continues to lead cutting-edge research projects while mentoring emerging scholars across China and globally. Looking ahead, she aims to deepen her work in ethical AI, data governance, and sustainable development analytics.

🔔 FINAL NOTE

Prof. Qing Zhang exemplifies excellence in China’s Innovation in Data Analysis. Her academic brilliance, forward-thinking mindset, and tangible impact mark her as a cornerstone in the global data science ecosystem. As the data revolution unfolds, Prof. Zhang stands as a beacon of insight, dedication, and transformation. 🌐💡📈

 📚 TOP NOTES PUBLICATIONS

Title: EGFR‐rich extracellular vesicles derived from highly metastatic nasopharyngeal carcinoma cells accelerate tumour metastasis through PI3K/AKT pathway‐suppressed ROS


Authors: Qing Zhang et al.
Journal: Journal of Extracellular Vesicles
Year: 2020

Title: Dendritic cell biology and its role in tumor immunotherapy

Authors: Qing Zhang et al.
Journal: Journal of Hematology & Oncology
Year: 2020

Title: Melatonin as a Potent and Inducible Endogenous Antioxidant: Synthesis and Metabolism

Authors: Qing Zhang et al.
Journal: Aging-US
Year: 2020

Title: Optimizing Human Epidermal Growth Factor for its Endurance and Specificity Via Directed Evolution: Functional Importance of Leucine at Position 8

Authors: Qing Zhang et al.
Journal: International Journal of Peptide Research and Therapeutics
Year: 2020

Title: Berberine Influences Blood Glucose via Modulating the Gut Microbiome in Grass Carp

Authors: Qing Zhang et al.
Journal: Frontiers in Microbiology
Year: 2019