Maliki Moustapha | Computer Science | Best Researcher Award

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Dr. Maliki Moustapha | Computer Science | Best Researcher Award

PhD | Erciyes University | Turkey

Dr. Maliki Moustapha, an accomplished researcher from Erciyes University, is recognized for his expertise in Artificial Intelligence (AI), Deep Transfer Learning, and Data Engineering, with a strong focus on the integration of intelligent algorithms and data-driven models to address real-world computational challenges. His academic background is rooted in computer science and engineering, where he developed advanced skills in machine learning, neural networks, data mining, and smart systems design. Professionally, Dr. Moustapha has been actively engaged in both research and academic mentorship, contributing to the development of innovative solutions in AI-powered automation, pattern recognition, and intelligent monitoring systems. His major research interests encompass computer vision, deep learning model optimization, spatiotemporal data analysis, and Internet of Things (IoT)-based smart healthcare systems. Among his most cited contributions is the publication titled “A Novel YOLOv5 Deep Learning Model for Handwriting Detection and Recognition” in the International Journal on Artificial Intelligence Tools (2023), which demonstrates superior accuracy and efficiency in image recognition. He has also published influential works on spatial and spatiotemporal clustering algorithms and IoT-based patient monitoring, bridging the gap between data intelligence and applied computing. His research skills span across Python programming, neural network modeling, big data analytics, data preprocessing, and model training for intelligent systems. Though early in his academic journey, Dr. Moustapha has earned recognition for his impactful work, showing promising potential in advancing AI technologies. According to Scopus and Google Scholar, he has achieved 9 citations, an h-index of 1, and several published documents reflecting growing international recognition. Dr. Moustapha’s research continues to contribute meaningfully to the fields of artificial intelligence and computational intelligence. In conclusion, his innovative approach, interdisciplinary mindset, and technological vision position him as a forward-thinking researcher committed to shaping the next generation of intelligent data systems and AI-driven innovations.

Profiles: ORCID | Google Scholar

Featured Publications

1. Moustapha, M., Taşyürek, M., & Öztürk, C. (2023). A novel YOLOv5 deep learning model for handwriting detection and recognition. International Journal on Artificial Intelligence Tools, 32(04), 2350016.

2. Moustapha, M. (2024). Spatial and spatiotemporal clustering algorithms in data mining. In Proceedings of the 3rd International Conference on Data and Electronics and Computing (ICDEC).

3. Moustapha, M. (2019). Alternative approach of patient monitoring system based on Internet of Things. In Proceedings of the II. International Science and Academic Congress (INSAC).

Farhan Nisar | Computer Science | Best Researcher Award

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Dr. Farhan Nisar | Computer Science | Best Researcher Award

Lecturer | The University of Agriculture | Pakistan

Dr. Farhan Nisar, affiliated with Qurtuba University of Science & Information Technology, Peshawar, Pakistan, is an emerging scholar and researcher in wireless communications, Internet of Things (IoT) networks, and machine learning applications for network optimization. He has made notable contributions to the field through his research on Low Power Wide Area Networks (LPWANs), particularly LoRaWAN, focusing on improving network efficiency, energy consumption, scalability, and reliability. Dr. Nisar’s educational background and professional trajectory have equipped him with a solid foundation in computer science and telecommunications, enabling him to apply advanced machine learning techniques for adaptive network parameter optimization, such as spreading factor adjustment, which enhances IoT network performance in dynamic real-world environments. Professionally, he has been involved in academic research, teaching, and applied projects that bridge theoretical knowledge with practical deployment of intelligent network solutions. His research interests include wireless communication protocols, IoT architectures, network security, data-driven network management, and intelligent device integration, reflecting a multidisciplinary approach that combines computer science, engineering, and data analytics. Dr. Nisar has developed strong research skills in machine learning modeling, algorithm development, network simulation, data analysis, and performance evaluation, contributing to both academic publications and open-access research outputs. His scholarly work has resulted in six published documents, with 18 citations to date and an h-index of 3, as indexed in Scopus, demonstrating early yet impactful contributions to his field. While still in the early stages of his career, he has received recognition for his innovative approaches to network optimization and IoT research, highlighting his potential for future academic and industrial leadership. In conclusion, Dr. Farhan Nisar represents a forward-looking researcher whose interdisciplinary expertise, rigorous methodology, and practical focus on intelligent, self-optimizing networks position him as a valuable contributor to the advancement of next-generation IoT and wireless communication technologies.

Profiles: Scopus

Featured Publications

  1. Nisar, F., & [Co-authors]. (2016). Green cloud computing approaches with respect to energy saving to data centers. Journal of Information, 6(2).

  2. Nisar, F., & [Co-authors]. (2017). Native approach security issue. In Proceedings of the IEEE Comtech Conference.

  3. Nisar, F., & [Co-authors]. (2019). Location-based authentication service in smartphones. In Proceedings of the IEEE Comtech Conference.

  4. Nisar, F., & [Co-authors]. (2019). Apply ARIMA model for data center with respect to different architecture. In Proceedings of the IEEE Raees Conference.

  5. Nisar, F., & [Co-authors]. (2019). Resource utilization in data center by applying ARIMA approach. In INTAP 2019.

 

 

Nassim Bout | Computer Science | Best Researcher Award

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Mr. Nassim Bout | Computer Science | Best Researcher Award

Senior Central Officer |  Hassan II University of Casablanca | Morocco

Mr. Nassim Bout is an accomplished adjunct professor and researcher in computer engineering, healthcare information systems, and artificial intelligence, recognized for his innovative contributions to AI-driven healthcare solutions, digital hospital services, and bioinformatics applications. He holds a Ph.D. in Engineering Sciences (Computer Engineering) from ENSEM, Hassan II University, Casablanca (2021–2024), and a Research Master’s in Management and Modeling of Complex Information Systems from ENSIAS, Mohammed V University, Rabat (2019–2021), reflecting a strong academic foundation in both technical and management aspects of complex information systems. Professionally, he has served as Senior Central Officer at the Ministry of Interior, coordinating digital transformation and IT services, as well as Product Owner at Netopia Solutions, where he led IT ecosystem studies and consulting for healthcare institutions. He has also contributed to Afrihealth Solutions as a software engineer, implementing hospital information systems across multiple regions. His research interests include AI integration in patient-centered healthcare, enterprise architecture in oncology, bioinformatics, and healthcare digital transformation. Mr. Bout possesses advanced skills in artificial intelligence and machine learning (deep learning, NLP, computer vision), algorithms and programming (C, C++, Python, JavaScript, PHP, Django), system design and architecture (TOGAF, UML, ArchiMate), project management frameworks (Agile, SCRUM, KANBAN), database management (SQL, PostgreSQL, Oracle DB), and bioinformatics tools, alongside strong communication and organizational abilities. He has an extensive publication record in reputed journals and conferences, including Discover Internet of Things, IJECE, Springer Lecture Notes, and ISDA proceedings, with citations by 1 document, 1 document, and an h-index reflecting his scholarly impact. He actively participates in professional societies as a reviewer for TELKOMNIKA, Digital Health, Cyber-physical Systems, and Network Modeling Analysis in Health Informatics and leads social inclusion initiatives through e-MOBADARA. Awards and honors include international conference recognitions and certifications in project management, scientific publishing, and bioinformatics training. In conclusion, Mr. Bout demonstrates exceptional interdisciplinary expertise, leadership, and scholarly influence, with strong potential to advance global research in AI-driven healthcare systems, mentor emerging researchers, and contribute to high-impact publications, international collaborations, and societal development through innovative healthcare technologies.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

  1. Bout, N., Khazaz, R., Azougaghe, A., El-Hfid, M., Abik, M., & Belhadaoui, H. (2021). Implementation of the business process model and notation in the modelling of patient’s clinical workflow in oncology. International Conference on Intelligent Systems Design and Applications, 576–586. Citations: 2

  2. Bout, N., Moukhliss, G., Belhadaoui, H., Afifi, N., & Abik, M. (2025). Integrating emotional AI, IoT, and robotics for patient-centered healthcare: Challenges and future directions. Discover Internet of Things, 5(75), 18. Citations: 1

  3. Bout, N., Azougaghe, A., Belhadaoui, H., El-Hfid, M., & Khazaz, R. (2022). Business process model and notation implemented in the hospital, any use? Case of the patient clinical workflow. Journal of Network and Innovative Computing, 10, 8–8. Citations: 1

  4. Bout, N., Ouzayd, F., & Retmi, K. (2025). Erratum for Role of Hospital Digital Services in Improvement of Clinical Regime of Patients [Health Tech Asmnt Act. 2021; 5(1)]. Health Technology Assessment in Action.

  5. Bout, N., Belhadaoui, H., Afifi, N., Abik, M., El-Hfid, M., & Azougaghe, A. (2025). Towards a standardized enterprise architecture: Enhancing decision-making in oncology multidisciplinary team meetings. International Journal of Electrical and Computer Engineering (IJECE), 15(2), 2224–2236.

 

Jiafa Mao | Computer Science | Best Researcher Award

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Prof. Jiafa Mao | Computer Science | Best Researcher Award

Professor at Zhejiang University College of Computer Science and Technology | China 

Prof. Jiafa Mao is an accomplished scholar and doctoral supervisor at the School of Computer Science and Technology, Zhejiang University of Technology, renowned for his expertise in information security, pattern recognition, computer vision, intelligent systems, and multimedia processing. He earned his Ph.D. in Pattern Recognition and Intelligent Systems from East China University of Science and Technology, followed by postdoctoral research at the Beijing University of Posts and Telecommunications. He has served as a professor, leading impactful research that bridges theory with real-world applications. Prof. Mao has directed and participated in numerous national and provincial-level projects, including the National 973 Program and NSFC initiatives, reflecting his strong research leadership. With over 60 publications in prestigious journals such as Pattern Recognition and IEEE Transactions, he has established an international academic footprint. A dedicated reviewer and active member of ACM, CCF, and CSIG, he continues to advance innovation and mentor future researchers.

Professional Profile

Scopus Profile 

Education

Prof. Jiafa Mao has built a strong academic foundation rooted in advanced computing sciences. He earned his Ph.D. in Pattern Recognition and Intelligent Systems from East China University of Science and Technology, where he focused on computational intelligence and system-level problem-solving. His doctoral journey equipped him with a deep understanding of information security, intelligent algorithms, and multimedia systems. To further enhance his research capabilities, he pursued postdoctoral studies at the Beijing University of Posts and Telecommunications. During this period, he engaged in cutting-edge investigations in computer science and technology, contributing to high-level research projects and collaborations with academic and industrial partners. This combined academic trajectory not only refined his expertise in areas such as pattern recognition and computer vision but also prepared him to become a future leader in the field, capable of addressing both theoretical challenges and practical applications.

Experience

Prof. Jiafa Mao has accumulated extensive academic and research experience, particularly in higher education and large-scale projects. He has served as a Professor and Doctoral Supervisor at the School of Computer Science and Technology, Zhejiang University of Technology. In this role, he has guided doctoral and postgraduate students, fostered innovation, and promoted high-quality research in areas like multimedia fingerprinting and intelligent systems. His professional journey also includes a productive postdoctoral tenure at the Beijing University of Posts and Telecommunications, where he sharpened his expertise in information security and data protection. Beyond academic teaching, he has led or participated in more than six national projects, including the National 973 Program and the National Natural Science Foundation of China, along with multiple ministerial, provincial, and industry-sponsored projects. His career reflects a balance of teaching, research, and leadership, demonstrating both scholarly excellence and real-world impact.

Research Interest

Prof. Jiafa Mao’s research interests span a wide spectrum of computer science disciplines, with a strong emphasis on information security and pattern recognition. He has extensively explored multimedia fingerprinting, information hiding, and intelligent systems, advancing methods that secure digital content in increasingly complex environments. His contributions to computer vision and image processing have supported applications ranging from identity verification to data protection, reinforcing the relevance of his work in both academic and industrial contexts. He is also engaged in the study of intelligent algorithms that integrate machine learning with evolving computational models, addressing challenges in automation and system reliability. Prof. Mao’s research aligns with pressing societal and technological needs, particularly in safeguarding information systems and advancing AI-driven solutions. With over 60 publications in top-tier journals and conferences, his studies not only enrich theoretical frameworks but also offer practical tools that address real-world challenges in computing and communication technologies.

Awards and Honors

Prof. Jiafa Mao’s career is distinguished by his strong record of scholarly recognition and professional service. His work has been featured in internationally respected journals such as Pattern Recognition, IEEE Transactions on Evolutionary Computation, and IEEE Transactions on Industrial Informatics, showcasing the global reach and quality of his contributions. He has served as a peer reviewer for numerous top journals and conferences, including IEEE Transactions on Cybernetics and the IEEE International Workshop on Information Forensics and Security, highlighting his trusted expertise within the academic community. His leadership in major projects funded by the National 973 Program and the National Natural Science Foundation of China reflects not only research excellence but also national recognition of his capabilities. Furthermore, his professional memberships in ACM, CCF, and CSIG demonstrate his active involvement in advancing the computing profession. These honors, alongside his extensive publication record, affirm his status as a highly respected researcher and academic leader.

Publication Top Notes

Title: Point-level feature learning based on vision transformer for occluded person re-identification
Year: 2024
Citation: 8

Title: Multi-granularity feature intersection learning for visible-infrared person re-identification
Year: 2025

Title: Basic theories and methods of target’s height and distance measurement based on monocular vision
Year: 2025
Citation: 1

Title: The 3D tooth model segmentation method based on GAC+PointMLP network
Year: 2025

Title: Feature optimization-guided high-precision and real-time metal surface defect detection network
Year: 2024
Citation: 3

Title: Workflows scheduling powered by execution time prediction model
Year: 2024
Citation: 1

Title: HashNeck is a Boosting Tool for Deep Learning to Hashing
Year: 2024

Conclusion

Prof. Jiafa Mao represents a distinguished scholar whose academic journey, research expertise, and leadership contributions firmly position him as a leading figure in the field of computer science. His work in information security, pattern recognition, multimedia fingerprinting, and intelligent systems has advanced both theoretical understanding and practical applications. With a Ph.D. in Pattern Recognition and Intelligent Systems and a successful postdoctoral tenure, he has established a strong foundation in computational intelligence and security-driven technologies. His role as a professor and doctoral supervisor has allowed him to mentor future researchers, while his involvement in national and industry-driven projects has enhanced his reputation as a solution-oriented innovator. Prof. Mao’s extensive publications, active peer-reviewing, and professional memberships in organizations like ACM and CCF underscore his global recognition and professional influence. With a balance of academic excellence and societal impact, he is a highly deserving candidate for prestigious recognitions such as the Best Researcher Award.