Md Nagib Mahfuz Sunny | Health Informatics | Young Scientist Award

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Mr. Md Nagib Mahfuz Sunny | Health Informatics | Young Scientist Award

Healthcare Data Analyst & Researcher at Children’s Clinic of Michigan, United States

Md Nagib Mahfuz Sunny is an emerging researcher and healthcare data analyst with a strong focus on applying big data analytics, machine learning, and predictive modeling to address critical challenges in the healthcare sector. His academic background in computer science and information science, combined with his practical experience, has enabled him to contribute meaningfully to areas such as clinical decision support, disease diagnosis, fraud detection, and telemedicine. Sunny has authored numerous peer-reviewed publications in respected journals, showcasing his ability to bridge technology and healthcare effectively. His research emphasizes data-driven solutions aimed at improving patient outcomes and reducing healthcare costs. As an IEEE Senior Member, he demonstrates leadership and commitment to innovation in his field. With a forward-looking approach and interdisciplinary mindset, Sunny continues to explore impactful research directions that align with global health and technology trends, making him a promising figure in the realm of healthcare informatics and intelligent systems.

Professional Profile 

Google Scholar

Education

Md Nagib Mahfuz Sunny has a solid educational foundation that integrates both computer science and information science, equipping him with the technical and analytical skills necessary for advanced research in data-driven healthcare solutions. He earned his Master of Science in Information Science from Trine University in the United States, where he focused on data analytics and its applications in healthcare systems. Prior to that, he completed his Bachelor of Science in Computer Science and Technology from Jiangsu University of Science and Technology in China. His academic journey reflects a commitment to international exposure and interdisciplinary learning, which has played a critical role in shaping his understanding of global healthcare challenges and the role of advanced technology in addressing them. Sunny’s academic training has provided him with the theoretical knowledge and practical tools necessary to conduct innovative research at the intersection of artificial intelligence, machine learning, and healthcare informatics.

Experience

Md Nagib Mahfuz Sunny brings diverse and impactful experience as a healthcare data analyst and researcher, with a particular focus on the use of machine learning, predictive modeling, and big data analytics in medical contexts. His professional and academic experience spans developing intelligent systems for clinical decision-making, optimizing healthcare processes, and conducting extensive data-driven research. Sunny has worked on multidisciplinary projects involving IoT-based frameworks for disease detection, AI-powered solutions for prescription optimization, and machine learning techniques for cancer classification and fraud detection. His collaborative work with global research teams and healthcare professionals has contributed to practical innovations and published outcomes in well-regarded scientific journals. He is actively involved in designing research methodologies, data analysis pipelines, and predictive models tailored for real-world healthcare applications. His hands-on experience reflects a strong integration of technical expertise and domain-specific knowledge, positioning him to drive future innovations in health informatics and digital healthcare transformation.

Research Focus

Md Nagib Mahfuz Sunny’s research centers around the application of artificial intelligence, big data analytics, and machine learning in healthcare to enhance clinical decision-making, improve diagnostics, and reduce operational inefficiencies. His core focus areas include predictive healthcare analytics, public health informatics, AI for disease classification, fraud detection in medical systems, and IoT-based health monitoring. Through his published work, he has explored diverse topics such as diabetes diagnosis using intelligent systems, cancer stage classification based on biomarker data, and AI-enhanced drug substitution models aimed at reducing healthcare costs. He is particularly interested in integrating real-time data from healthcare environments with advanced computational models to generate actionable insights for physicians and public health professionals. Sunny’s research consistently emphasizes innovation, real-world applicability, and ethical use of data in healthcare. His contributions reflect a forward-thinking approach to solving modern medical challenges through computational intelligence and interdisciplinary collaboration.

Award and Honor

Md Nagib Mahfuz Sunny has earned recognition for his contributions to healthcare analytics and intelligent systems through multiple peer-reviewed publications and active involvement in professional communities. He holds the distinction of being an IEEE Senior Member, a title that reflects both his technical accomplishments and leadership within the engineering and technology community. His research has been published in esteemed journals and presented at international conferences, highlighting the relevance and impact of his work in the global academic landscape. The quality and applicability of his research, particularly in AI-driven healthcare solutions, have attracted attention from institutions and collaborators worldwide. His interdisciplinary and international academic journey has further contributed to his reputation as a knowledgeable and forward-thinking young scientist. As he continues to build on his work in healthcare data science, his achievements mark him as a strong candidate for future research awards and honors within the field of health informatics and artificial intelligence.

Publications Top Notes

  • Title: Optimizing Healthcare Outcomes through Data-Driven Predictive Modeling
    Authors: MNM Sunny, MBH Sakil, A Al Nahian, SW Ahmed, MN Shorif, J Atayeva
    Year: 2024
    Citations: 38

  • Title: Project Management and Visualization Techniques A Details Study
    Authors: MNM Sunny, MBH Sakil, A Al Nahian
    Year: 2024
    Citations: 23

  • Title: Neural Network-Powered License Plate Recognition System Design
    Authors: S Hasan, MNM Sunny, A Al Nahian, M Yasin
    Year: 2024
    Citations: 18

  • Title: Predictive Healthcare: An IoT-Based ANFIS Framework for Diabetes Diagnosis
    Authors: MNM Sunny, MBH Sakil, J Atayeva, ZS Munmun, MS Mollick, MO Faruq
    Year: 2024
    Citations: 4

  • Title: Telemedicine and Remote Healthcare: Bridging the Digital Divide
    Authors: MNM Sunny, U Sumaiya, MH Akter, F Kabir, ZS Munmun, B Nurani, M Amin
    Year: 2024
    Citations: 3

  • Title: Classification of Cancer Stages Using Machine Learning on Numerical Biomarker Data
    Authors: MNM Sunny, MM Amin, MH Akter, KMS Hossain, A Al Nahian, J Atayeva
    Year: 2024
    Citations: 3

  • Title: Numerical Analysis of Multivariate Data for Fraud Detection
    Authors: MNM Sunny, KMS Hossain, MM Amin, SN Sadmani
    Year: 2024
    Citations: 2

  • Title: Advance Obstacle Detection for Autonomous Vehicles Using Numerical Data from LIDAR and RADAR Sensor: A Machine Learning Approach
    Authors: R Akter, K Oyshee, MN Sunny, P Roy, F Ahammed, MF Refat
    Year: 2024
    Citations: 1

Conclusion

Md Nagib Mahfuz Sunny has established a commendable research profile with multiple impactful publications across emerging areas in healthcare analytics and machine learning. His work is gaining increasing recognition, as reflected by citation metrics, particularly in studies focusing on predictive modeling, IoT-based healthcare, and AI-powered diagnostics. The consistent authorship and interdisciplinary collaborations indicate his active engagement in advancing practical, data-driven solutions to real-world challenges. His growing citation count and contributions to reputable journals suggest a trajectory toward becoming a significant voice in the field. Overall, his research contributions are not only timely but also align well with the core values of innovation, applicability, and academic rigor—making him a deserving candidate for recognition through awards and further research opportunities.

Emanuele Raso | Medical Devices | Best Researcher Award

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Dr. Emanuele Raso | Medical Devices | Best Researcher Award

Research Fellow at University of Rome Tor Vergata, Italy

Emanuele Raso is a Research Fellow at the University of Rome Tor Vergata, specializing in cybersecurity within the Department of Electronic Engineering. He holds a Ph.D. in Computer Science, Control, and Geoinformation and focuses on applied cryptography, data privacy, open-source intelligence, and the use of artificial intelligence in the medical domain. His work is dedicated to developing secure data processing systems and privacy-preserving technologies, particularly for healthcare and critical digital infrastructure. Raso has contributed to several national and European research projects, including BPR4GDPR, I-NEST, Rome Technopole, and ISP5G+, and has published 16 Scopus-indexed journal articles. He serves as a guest editor for the MDPI Sensors journal’s special issue on cybersecurity in healthcare and is affiliated with CNIT’s National Laboratory of Network Assessment, Assurance, and Monitoring. His interdisciplinary research bridges engineering, cybersecurity, and healthcare, making significant strides in protecting sensitive data in increasingly digital health systems.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile 

Education

Emanuele Raso earned his Ph.D. in Computer Science, Control, and Geoinformation from the University of Rome Tor Vergata, where he also completed his earlier academic training. His doctoral work laid the foundation for his current research in cybersecurity, with a focus on secure and privacy-preserving technologies. Through his education, Raso developed a strong technical background in applied cryptography, artificial intelligence, and data privacy—areas critical to safeguarding modern digital infrastructures. His academic path demonstrates a consistent alignment with emerging technological challenges, particularly in the intersection of computing and healthcare. His education also reflects rigorous interdisciplinary training, incorporating both theoretical knowledge and practical implementation strategies in secure systems. This comprehensive academic preparation has enabled him to contribute effectively to national and European research initiatives, and to innovate in fields that bridge computer science and real-world societal applications, especially in the secure handling of sensitive health-related data.

Professional Experience

Emanuele Raso is currently a Research Fellow in the Department of Electronic Engineering at the University of Rome Tor Vergata. In this role, he has been actively involved in both academic and applied research focused on cybersecurity, with an emphasis on data privacy and secure computing environments. His professional experience includes participation in several high-profile European and national research projects such as BPR4GDPR, I-NEST, Rome Technopole, and ISP5G+. These projects have given him the opportunity to work on developing privacy-preserving technologies for healthcare and critical infrastructures. Although he does not yet have consultancy or industrial project experience, his academic roles have involved extensive research, collaboration, and knowledge dissemination. As a guest editor for MDPI Sensors, he contributes to the academic peer-review process, and he maintains active affiliations with professional research bodies like CNIT’s NAM LAB. His professional career reflects a growing influence in cybersecurity research with practical societal applications.

Research Interest

Emanuele Raso’s primary research interests lie in cybersecurity, particularly in applied cryptography, data privacy and confidentiality, open-source intelligence (OSINT), and the integration of artificial intelligence in the medical domain. His work is motivated by the growing need for secure digital environments, especially in critical sectors such as healthcare, where the protection of sensitive personal and clinical data is paramount. He is particularly focused on developing privacy-preserving technologies and secure data processing frameworks that ensure confidentiality without sacrificing functionality. His interdisciplinary approach bridges the gap between computer science and digital health, aiming to create systems that support compliance with regulations like GDPR while fostering innovation in medical data analysis. Raso is also interested in the ethical and social implications of AI-driven decision-making systems, especially in healthcare contexts. This forward-thinking research orientation enables him to address contemporary challenges at the nexus of cybersecurity, data science, and digital health infrastructure.

Award and Honor

While Emanuele Raso has not listed major individual awards or honors in his profile, his appointment as a Guest Editor for the Sensors journal’s special issue on “Cybersecurity in Healthcare and Medical Devices” is a notable academic distinction. This editorial role highlights his recognized expertise and growing reputation within the cybersecurity and health informatics research communities. Additionally, his active participation in prestigious European research projects such as BPR4GDPR and I-NEST reflects a high level of professional trust and recognition in his field. His affiliation with CNIT’s NAM LAB, a national network of telecommunications researchers, also signifies his integration into Italy’s leading research bodies. Though formal awards may yet be forthcoming in his career, these appointments and roles affirm the esteem in which he is held by colleagues and research institutions. They demonstrate his trajectory as a respected contributor in applied cybersecurity and health technology fields.

Conclusion

Emanuele Raso is an emerging expert in cybersecurity, with a strong academic background, active professional research engagements, and a focused interest in privacy-preserving technologies for healthcare and critical infrastructures. His work addresses timely and vital challenges in safeguarding sensitive information in an increasingly digital world, particularly at the intersection of artificial intelligence and health data management. Although his profile does not currently include industry collaborations or major awards, his contributions to high-level European projects and his editorial role underscore his growing impact in the field. With a solid foundation in computer science and a strong commitment to interdisciplinary innovation, Raso is well-positioned to make significant advancements in secure computing environments. His research is not only academically relevant but also societally impactful, with real-world applications in digital health systems. As his career progresses, he is likely to expand his influence further and become a key figure in shaping the future of cybersecurity in healthcare.

Publications Top Notes

  • Title: Privacy-aware architectures for NFC and RFID sensors in healthcare applications
    Authors: E. Raso, G.M. Bianco, L. Bracciale, G. Marrocco, C. Occhiuzzi, P. Loreti
    Year: 2022
    Citations: 16

  • Title: Privacy and transparency in blockchain-based smart grid operations
    Authors: P. Loreti, L. Bracciale, E. Raso, G. Bianchi, E.R. Sanseverino, P. Gallo
    Year: 2023
    Citations: 12

  • Title: UHF RFID and NFC point-of-care—Architecture, security, and implementation
    Authors: G.M. Bianco, E. Raso, L. Fiore, V. Mazzaracchio, L. Bracciale, F. Arduini, …
    Year: 2023
    Citations: 11

  • Title: An SDN-based traffic handover control procedure and SGD management logic for EHF satellite networks
    Authors: M.M. Aurizzi, T. Rossi, E. Raso, L. Funari, E. Cianca
    Year: 2021
    Citations: 10

  • Title: A privacy-preserving blockchain solution to support demand response in energy trading
    Authors: L. Bracciale, P. Loreti, E. Raso, G. Bianchi, P. Gallo, E.R. Sanseverino
    Year: 2022
    Citations: 8

  • Title: Anonymization and pseudonymization of FHIR resources for secondary use of healthcare data
    Authors: E. Raso, P. Loreti, M. Ravaziol, L. Bracciale
    Year: 2024
    Citations: 6

  • Title: ABEBox: A data driven access control for securing public cloud storage with efficient key revocation
    Authors: E. Raso, L. Bracciale, P. Loreti, G. Bianchi
    Year: 2021
    Citations: 6

  • Title: Performance evaluation of cryptographic schemes for blockchain security of smart grids
    Authors: E. Raso, L. Bracciale, P. Gallo, G. Bernardinetti, G. Bianchi, E.R. Sanseverino, …
    Year: 2022
    Citations: 4

  • Title: Privacy in blockchain-based smart grids
    Authors: L. Bracciale, E. Raso, P. Gallo, E.R. Sanseverino, G. Bianchi, P. Loreti
    Year: 2022
    Citations: 4

  • Title: GDPR compliance made easier: The BPR4GDPR project
    Authors: G. Lioudakis, E. Papagiannakopoulou, M. Koukovini, N. Dellas, …
    Year: 2021
    Citations: 4

  • Title: Toolate: cryptographic data access control for offline devices through efficient key rotation
    Authors: L. Bracciale, P. Loreti, E. Raso, G. Bianchi
    Year: 2021
    Citations: 4