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.

Wisal Zafar | AI in Healthcare | Data Scientist of the Year Award

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Mr. Wisal Zafar | AI in Healthcare | Data Scientist of the Year Award

Lecturer at Cecos University of IT and Emerging Sciences, Pakistan

Wisal Zafar is a dynamic academic and research-oriented professional whose expertise lies at the intersection of data science, artificial intelligence, and deep learning. With a strong foundation in software engineering, he has progressively transitioned into data-centric domains where he now actively contributes as a lecturer, researcher, and data scientist. His work integrates modern machine learning techniques and neural networks to tackle real-world problems ranging from healthcare to education. His career is marked by a drive to foster innovation through technology, an unwavering commitment to academic excellence, and a passion for nurturing student potential in both undergraduate and postgraduate settings.

Profile

Scopus

Education

Wisal’s academic journey began with a Bachelor of Science in Software Engineering from Iqra National University, Peshawar, completed in 2020 with a commendable CGPA of 3.47/4.00. Building on this strong foundation, he pursued a Master of Science in Software Engineering at the same university, expected to be completed by mid-2024, where he currently holds a CGPA of 3.50/4.00. His academic record reflects a consistent pursuit of knowledge and skill advancement in software technologies, deep learning, and data analysis. Prior to his university education, he completed his Intermediate from Capital Degree College and matriculation from The Jamrud Model High School with notable academic performances.

Experience

Professionally, Wisal has held several key positions in academia and data processing. He is currently serving as a Lecturer at CECOS University of IT and Emerging Sciences, Peshawar, where he imparts advanced-level knowledge in Artificial Intelligence, Data Science, and Machine Learning. Before this, he contributed significantly to Iqra National University both as a Lecturer and as an EDP Officer, where he oversaw electronic data processing and optimized data accessibility across research and academic projects. His roles have consistently involved not only teaching but also mentorship, particularly in guiding final-year students through research and development of innovative software solutions. His earlier professional engagements also include roles as a Junior Web Developer and teaching positions, showcasing a diverse skill set in both educational and technical domains.

Research Interests

Wisal’s research interests are rooted in the application of artificial intelligence and machine learning to critical societal challenges. His work spans brain tumor detection, plant disease classification, emotion recognition in educational settings, and mental health analysis using social media data. He is particularly intrigued by hybrid deep learning architectures, transformer-based models, and neural networks. He consistently integrates image processing techniques and NLP tools to build intelligent, data-driven solutions. His recent focus includes real-time decision support systems, content-based image retrieval, and multi-scale classification, which have promising implications for both healthcare and education systems.

Awards

In recognition of his exceptional contribution to the academic and technical environment, Wisal was honored with the “Best Employee of the Year 2023” award at Iqra National University. This accolade acknowledges his consistent performance, innovative approach to teaching and research, and his ability to blend administrative responsibilities with cutting-edge academic delivery. His recognition serves as a testament to his dedication, collaborative spirit, and leadership potential in the academic research community.

Publications

Wisal has made significant scholarly contributions, with several research publications in high-impact international journals. His paper “Enhanced TumorNet: Leveraging YOLOv8s and U-Net for Superior Brain Tumor Detection and Segmentation Utilizing MRI Scans” was published in Results in Engineering (2024) and is cited for its innovative approach to medical imaging using hybrid models. Another influential work, “Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed”, appeared in MDPI-Healthcare (2023) and explores diagnostic modeling using AI techniques. His third publication, “A Survey on Big Data Analytics (BDA) Implementation and Practices in Medical Libraries of Punjab”, published in the Journal of Computing & Biomedical Informatics (2023), provides insights into the integration of BDA in healthcare information systems. These publications highlight his range—from healthcare diagnostics to knowledge systems—and his adaptability in multiple AI-driven domains.

Conclusion

Wisal Zafar stands out as a highly motivated data scientist and academician with a clear vision for the future of AI and its applications. Through his diverse academic background, hands-on teaching experience, impactful research, and recognized contributions to institutional growth, he exemplifies the qualities of an innovative thinker and dedicated professional. His continued exploration of deep learning and intelligent systems is not only enriching the academic field but also paving the way for practical solutions to societal challenges. With a growing portfolio of research and a keen eye for technological advancements, Wisal is well-poised to make long-term contributions to AI-based research and higher education. His career trajectory illustrates a seamless blend of academic rigor, technical skill, and research excellence.

yang Li | AI in Healthcare | Best Researcher Award

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Prof. yang Li | AI in Healthcare | Best Researcher Award

Chief physician at First Hospital of Shanxi Medical University, China

Dr. Yang Li is a distinguished Chief Neurologist at the First Hospital of Shanxi Medical University, with over three decades of experience in cognitive disorder research and clinical practice. He holds a Doctor of Medicine (M.D.) degree and serves as a doctoral advisor. As the head of the Core Advanced Cognitive Center, he has played a pivotal role in advancing cognitive health initiatives in China. His contributions include the establishment of Shanxi Province’s first memory clinic in 2009, which received national recognition in subsequent years. Dr. Li has spearheaded multiple projects focused on Alzheimer’s disease (AD) and Parkinson’s disease (PD), significantly enhancing early detection and patient care strategies. Recognized for his exceptional contributions, he has been awarded the Second Prize of the Shanxi Provincial Science and Technology Progress Award and was selected as a leading talent under the “San Jin Talents” Support Program.

Profile

Scopus

Education

Dr. Yang Li obtained his Doctor of Medicine (M.D.) degree, equipping him with the expertise necessary for his extensive work in neurology and cognitive disorders. As a dedicated academic, he has mentored numerous doctoral candidates, guiding them in clinical research. His academic journey reflects a strong commitment to advancing neurological science, particularly in memory and cognitive function research. His efforts have contributed significantly to the development of national health policies and innovative diagnostic techniques for neurodegenerative disorders.

Experience

With more than 30 years in the field, Dr. Li has played a transformative role in neurology, specializing in cognitive disorders. His leadership at the First Hospital of Shanxi Medical University has resulted in numerous breakthroughs in early detection and treatment methodologies for conditions such as Alzheimer’s and Parkinson’s disease. Dr. Li has also been instrumental in establishing national training programs, including the Cognitive Specialty Capacity Building Project initiated by the National Health Commission. His expertise extends beyond clinical practice to impactful policy formulation and implementation. His work in digital screening tools and community-based healthcare projects underscores his innovative approach to neurological health.

Research Interests

Dr. Li’s research is primarily centered on cognitive disorders, particularly Alzheimer’s disease and other neurodegenerative conditions. He has pioneered advancements in early screening tools and interventions, integrating digital diagnostics such as neuroimaging assessments, PET-CT scans, and gait analysis. His recent initiatives focus on community-based screening, aiming to develop scalable and efficient methods for detecting mild cognitive impairment (MCI) and dementia in aging populations. His work contributes significantly to global research in cognitive health, emphasizing preventive strategies and innovative therapeutic approaches.

Awards

Dr. Li’s contributions to cognitive neurology have earned him numerous accolades. He was honored with the Second Prize of the Shanxi Provincial Science and Technology Progress Award in recognition of his pioneering research in neurodegenerative disorders. In 2018, he was selected as a leading talent under the “San Jin Talents” Support Program. His memory clinic, established in 2009, was recognized as a “National Outstanding Memory Clinic” in both 2013 and 2014. His dedication to advancing early screening and intervention methods for cognitive impairments has positioned him as a key figure in neurological research and healthcare innovation.

Publications

Dr. Li has contributed extensively to the scientific community with high-impact publications in leading journals. Some of his notable works include:

Qin Y, Han H, Li Y, et al. (2023). “Estimating Bidirectional Transitions and Identifying Predictors of Mild Cognitive Impairment.” Neurology, 100(3), e297-e307. [Cited by 120 articles].

Jia J, Zhao T, Liu Z, et al. (2023). “Association between Healthy Lifestyle and Memory Decline in Older Adults: 10-Year Prospective Cohort Study.” BMJ, 380, e072691. [Cited by 95 articles].

Wu H, Ren Z, Gan J, et al. (2022). “Blood Pressure Control and Risk of Post-Stroke Dementia.” Front Neurol, 13, 1069667. [Cited by 87 articles].

Zhang X, Lv L, Min G, Wang Q, Zhao Y, Li Y. (2021). “Complex Figure Test and Its Clinical Application in Neuropsychiatric Disorders.” Front Neurol, 12, 680474. [Cited by 78 articles].

Xu SY, Song MM, Liu DY, et al. (2024). “Contrast-Induced Encephalopathy with Elevated Cerebrospinal Fluid Protein.” Br J Neurosurg, 38(4), 963-967. [Cited by 56 articles].

Wang F, Fei M, Hu WZ, et al. (2022). “Prevalence of Constipation in Elderly and Its Association with Dementia.” Front Neurosci, 15, 821654. [Cited by 102 articles].

Xing Y, Zhu Z, Du Y, et al. (2020). “COG-REAGENT: Cognitive Training in Amnestic Mild Cognitive Impairment.” J Alzheimers Dis, 75(3), 779-787. [Cited by 112 articles].

Conclusion

Dr. Yang Li has made remarkable contributions to cognitive neurology through his pioneering research, clinical expertise, and commitment to early detection of neurodegenerative disorders. His leadership in community-based screening projects and digital health interventions has significantly advanced the field of cognitive disorders. With numerous prestigious awards, high-impact publications, and dedicated mentorship, Dr. Li continues to shape the landscape of Alzheimer’s and dementia research. His work not only enhances diagnostic methodologies but also fosters preventive healthcare strategies, making a lasting impact on the global fight against cognitive decline.