Suganya Ramamoorthy | Computer Vision | Best Academic Researcher Award

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Dr. Suganya Ramamoorthy | Computer Vision | Best Academic Researcher Award

Dr. Suganya Ramamoorthy | Computer Vision | Associate Professor Senior at Vellore Institute of Technology Chennai | India

Dr. Suganya Ramamyoorthy is a distinguished academic and researcher, currently serving as an Associate Professor Senior at VIT University, Chennai. With a robust background in computer science and engineering, she has made significant contributions in the domains of medical image processing, big data analytics, computer vision, and engineering education. Her multidisciplinary research has bridged technological innovation with societal needs, particularly in healthcare diagnostics, intelligent transportation, and data privacy. Dr. Suganya is recognized for her active role in both teaching and mentoring, and she consistently integrates real-world applications into her academic and research endeavors. With over 700 citations and a growing h-index, her work continues to gain wide recognition in national and international research communities.

Academic Profile:

ORCID 

Scopus

Google Scholar

Education:

Dr. Suganya earned her doctoral degree in Computer Science, specializing in the areas of image processing and artificial intelligence applications. Her academic journey has been characterized by a commitment to advancing computational methods that solve real-world problems. Throughout her higher education, she focused on interdisciplinary research, blending core computer science concepts with domains like healthcare, biometric security, and environmental monitoring. Her educational foundation has been further enriched through ongoing professional certifications and research training that align with the evolving trends in AI, machine learning, and data engineering.

Experience:

In her academic career, Dr. Suganya has accumulated extensive experience in research, teaching, and academic leadership. At VIT University, she has contributed to curriculum development, student supervision, and project guidance at both undergraduate and postgraduate levels. She has also led and participated in multiple collaborative research initiatives, including those involving international institutions. Dr. Suganya is a frequent contributor to IEEE conferences, editorial boards, and global benchmarking challenges. Her participation in major biometric and vision-based competitions such as IJCB and AIM has strengthened her global visibility and collaborative network. Additionally, she actively engages in community outreach and knowledge dissemination through workshops, seminars, and academic panels.

Research Interests:

Dr. Suganya’s research interests span several high-impact areas, including big data analytics, deep learning in medical imaging, pattern recognition, and data privacy. Her work on computer-aided diagnostic systems has improved early detection mechanisms for diseases through dermoscopic and ultrasound image analysis. She has also developed AI models for obstacle detection in railway systems and semantic segmentation in aerial imagery. In the realm of data privacy, her research addresses pressing security concerns associated with large-scale data processing. She continues to explore cutting-edge technologies such as convolutional neural networks, feature extraction, and hybrid classification models, aiming to push the boundaries of applied AI research.

Awards:

Dr. Suganya has received multiple recognitions for her scholarly contributions and research excellence. Her work has been highlighted in international conferences and cited in respected scientific journals. Her involvement in benchmarking competitions and her contributions to high-impact projects reflect her dedication to both academic quality and societal relevance. Her strong academic record and innovative research approach make her a suitable nominee for the Best Academic Researcher Award, where her contributions are not only impactful in theory but also practical in application.

Selected Publications:

  • “An automated computer aided diagnosis of skin lesions detection and classification for dermoscopy images”
    Published: 2016
    Citations: 90

  • “Analyzing Big Data challenges and security issues in data privacy”
    Published: 2023
    Citations: 65

  • “AIM 2020: Scene relighting and illumination estimation challenge”
    Published: 2020
    Citations: 54

  • “Ssbc 2020: Sclera segmentation benchmarking competition in the mobile environment”
    Published: 2020
    Citations: 44

Conclusion:

Dr. Suganya Ramamyoorthy stands out as a dedicated researcher with a strong track record of scholarly output, international collaboration, and real-world impact. Her contributions to the fields of medical imaging, data privacy, and AI-driven systems underscore her commitment to addressing complex societal problems through innovative research. With a rapidly growing citation record and sustained involvement in collaborative projects, she has demonstrated leadership, vision, and academic excellence. Dr. Suganya’s expertise, coupled with her passion for mentorship and community engagement, positions her as a deserving candidate for the Best Researcher Award and a future leader in the global AI research landscape.

 

 

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.