Lahcen Tamym | AI in Healthcare | Best Researcher Award

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Assoc. Prof. Dr. Lahcen Tamym | AI in Healthcare | Best Researcher Award

Associate Professor at Jean Monnet University, France

Lahcen Tamym is a dynamic academic professional and researcher in the field of computer science, currently serving as an Assistant Professor in Industrial Engineering and Healthcare Systems Engineering at Jean Monnet University, Saint-Étienne, within the LASPI Laboratory. His academic and research journey is rooted in Big Data and Data Science, with a particular focus on sustainable, resilient, and intelligent networked enterprises. With a passion for innovation at the intersection of emerging technologies and socio-environmental goals, Dr. Tamym has developed advanced frameworks for optimizing supply chains, improving life cycle sustainability, and enhancing decision-making using Big Data Analytics (BDA), Machine Learning (ML), Internet of Things (IoT), and Blockchain technologies. His multidisciplinary work continues to advance smart industrial systems aligned with the Sustainable Development Goals (SDGs).

Profile

Scopus

Education

Lahcen Tamym began his academic path with a Bachelor’s degree in Mathematical and Computer Sciences from Ibn Zohr University in Morocco, where he developed optimization models using CPLEX and MINOS. He then pursued a Master’s degree in Intelligent and Decision Support Systems at Sidi Mohamed Ben Abdellah University, where his work focused on deep learning for graph representation. He earned his Ph.D. in Computer Science from Aix-Marseille University, France, and Université Moulay Ismail, Morocco. His doctoral research specialized in Big Data Analytics for managing flexible, robust, and sustainable networked enterprises. The study emphasized machine learning, predictive analytics, and optimization in supply chains and sustainable value creation, forming the foundation for his continuing contributions to sustainable industrial development.

Experience

Dr. Tamym’s professional trajectory includes teaching and research across several institutions in France and Morocco. Before his current faculty position at Jean Monnet University, he served as a Temporary Teaching and Research Assistant (ATER) at Aix-Marseille University. During this time, he was involved in both instructional duties and cutting-edge research in computer science and interaction. His earlier involvement in collaborative research at Laboratoire d’Informatique et Systèmes (LIS) in France and Laboratoire d’Informatique et Applications (IA) in Morocco provided him with diverse academic exposure and the opportunity to build multidisciplinary solutions addressing real-world challenges in industrial and healthcare domains.

Research Interest

Dr. Tamym’s research revolves around the application of advanced data-driven methods to enhance sustainability, flexibility, and resilience in networked enterprises. His areas of interest include Big Data Analytics, IoT, Blockchain, Machine Learning, and Decision Support Systems. He is particularly focused on sustainable supply chain management, life-cycle assessment, risk analysis, and social sustainability evaluation. He has also explored blockchain-based security models for IoT, financial fraud detection systems using deep learning, and natural language processing in educational and healthcare systems. By integrating these technologies, he aims to create intelligent, transparent, and adaptive networks capable of responding to dynamic global and industrial demands.

Award

Although specific awards are not listed, Dr. Tamym’s consistent involvement in prestigious conferences and publication in reputable journals underlines his recognition within the academic community. His work has been well-received at international forums such as the International Conference on Ambient Systems, Networks and Technologies, and IFAC conferences, reflecting the impact and value of his contributions. His research aligns with global agendas for sustainable industry and digital transformation, enhancing his profile as a leading researcher in his domain.

Publication

Dr. Tamym has published widely in top-tier journals and conferences. Notable publications include:

  1. Big Data Analytics-based life cycle sustainability assessment for sustainable manufacturing enterprises evaluation, Journal of Big Data (2023), cited for contributions to sustainable manufacturing assessment.

  2. Big data analytics-based approach for robust, flexible and sustainable collaborative networked enterprises, Advanced Engineering Informatics (2023), cited for its novel integration of resilience in supply chains.

  3. A big data based architecture for collaborative networks: Supply chains mixed-network, Computer Communications (2021), contributing to architecture modeling for collaborative systems.

  4. A Big Data Analytics-Based Methodology For Social Sustainability Impacts Evaluation, Procedia Computer Science (2023), a case-based analysis on social sustainability metrics.

  5. How Can Big Data Analytics and Artificial Intelligence Improve Networked Enterprises’s Sustainability?, IEEE ACDSA Conference (2024), exploring AI’s role in sustainable enterprise development.

  6. Distributed Deep Learning-Based Model for Financial Fraud Detection in Supply Chain Networks, ICICT 2024, addressing cybersecurity challenges in digital supply chains.

  7. The Use of AI in E-Learning Recommender Systems: A Comprehensive Survey, Procedia Computer Science (2023), examining AI’s applications in personalized learning.

Conclusion

Lahcen Tamym stands at the forefront of interdisciplinary research, bridging data science and sustainable systems engineering. His academic contributions are rooted in practical application, ensuring that intelligent technologies directly impact the design and operation of industrial and healthcare systems. With a forward-looking vision aligned with Industry 5.0 principles and the SDGs, his research continues to influence the development of smart, ethical, and eco-efficient networks. Dr. Tamym’s commitment to fostering data-driven innovation across domains positions him as a transformative figure in the evolving landscape of sustainable and resilient enterprise systems.

Şifa Özsari | Image Processing | Best Researcher Award

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Dr. Şifa Özsari | Image Processing | Best Researcher Award

Res. Assist. | Ankara University | Turkey

Dr. Şifa Özsarı is an accomplished academic and researcher specializing in artificial intelligence (AI), machine learning, deep learning, image processing, and optimization. With a career dedicated to advancing cutting-edge technologies, Dr. Özsarı has made significant contributions to her field through groundbreaking research, impactful publications, and innovative problem-solving approaches. Currently affiliated with Ankara University, she has been recognized for her commitment to both scientific discovery and practical applications in AI-driven solutions.

Profile

Scopus

Education

Dr. Özsarı completed her academic training at prestigious institutions, building a strong foundation in engineering and computational sciences. Her educational journey was marked by excellence, with advanced degrees focusing on artificial intelligence and its interdisciplinary applications. Her academic pursuits equipped her with the knowledge and skills to address complex challenges in fields such as image processing, optimization algorithms, and medical diagnostics.

Experience

Dr. Özsarı has accumulated extensive professional experience in both academia and applied research. She has been involved in interdisciplinary projects that bridge AI with real-world applications, such as healthcare, environmental science, and engineering. Her expertise in deep learning and optimization has enabled her to contribute to projects like fungi classification, weather analysis, and temporomandibular joint disorder diagnostics. Throughout her career, she has mentored students, collaborated with international researchers, and participated in high-impact conferences.

Research Interests

Dr. Özsarı’s research interests lie at the intersection of artificial intelligence and its transformative potential across diverse domains. Her work focuses on developing advanced deep learning models, optimizing machine learning algorithms, and applying these technologies to image processing, medical diagnostics, and environmental monitoring. She is particularly passionate about leveraging AI to address pressing societal challenges, such as improving healthcare outcomes and advancing sustainable solutions.

Awards

Dr. Özsarı has been nominated for several awards that recognize her contributions to the field of artificial intelligence and machine learning. Her work has earned acclaim for its innovation, interdisciplinary approach, and potential for practical application. Specific details of awards and recognitions highlight her dedication to excellence and the impact of her research on both academia and industry.

Publications

Dr. Özsarı has an impressive portfolio of publications in esteemed journals, showcasing her expertise and contributions to AI and related fields. Selected publications include:

Deep Learning-Based Classification of Macrofungi: Comparative Analysis of Advanced Models for Accurate Fungi Identification (2024). Published in Sensors, vol. 24, no. 22, this paper explores fungi classification using deep learning, cited by several articles for its innovative methodologies.

A Comprehensive Review of Artificial Intelligence-Based Algorithms Regarding Temporomandibular Joint-Related Diseases (2023). Published in Diagnostics, vol. 13, no. 16, this review consolidates AI approaches for medical diagnostics, attracting citations for its thorough analysis.

Interpretation of Magnetic Resonance Images of Temporomandibular Joint Disorders by Using Deep Learning (2023). Published in IEEE Access, vol. 11, this study applies deep learning to medical imaging, widely recognized for its clinical significance.

Cloudy/Clear Weather Classification Using Deep Learning Techniques with Cloud Images (2022). Published in Computers and Electrical Engineering, vol. 102, this paper advances environmental monitoring with AI techniques.

Implementation of Meta-Heuristic Optimization Algorithms for Interview Problems in Land Consolidation: A Case Study in Konya/Turkey (2021). Published in Land Use Policy, vol. 108, this work integrates AI in land management.

Automatic Vertical Root Fracture Detection on Intraoral Periapical Radiographs with Artificial Intelligence-Based Image Enhancement (Date TBD). Published in Dental Traumatology, this ongoing work has drawn interest for its contributions to dental imaging.

USB-IDS-1 Dataset Feature Reduction with Genetic Algorithm (2024). Published in Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, vol. 66, this study enhances data efficiency using genetic algorithms.

Conclusion

Dr. Şifa Özsarı’s career exemplifies a dedication to advancing the frontiers of artificial intelligence. Through her interdisciplinary research, impactful publications, and contributions to real-world applications, she has established herself as a leading figure in her field. Her work not only addresses academic challenges but also provides innovative solutions to practical problems, making a meaningful impact across various industries. Dr. Özsarı’s ongoing research promises to continue shaping the future of AI and its applications.