Christian Schachtner | Data Science | Research Excellence Award

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Prof. Dr. Christian Schachtner | Data Science | Research Excellence Award

Full Professor Digital Public Administration | Hochschule RheinMain | Germany

Prof. Dr. Christian Schachtner is a Professor of Administrative Digitalization whose work focuses on digital transformation, organizational change, smart government, public law, sustainability, and new learning in the public sector. His research has significantly contributed to understanding smart city strategies, chief digital officer (CDO) roles, agile governance, and data-based public management. He has authored and co-authored over 20 scholarly publications, including articles in Smart Cities, Verwaltung und Management, and international conference proceedings. His work has received 98 citations, with an h-index of 6 and an i10-index of 3, reflecting growing academic and practical impact. Through interdisciplinary and international collaborations, his research supports municipalities in designing resilient, citizen-centered, and digitally enabled governance systems, directly influencing public sector modernization and sustainable administrative innovation.

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Featured Publications


Smart government in local adoption

– ORAȘE INTELIGENTE ȘI DEZVOLTARE REGIONALĂ, 2021 . | Citations: 21.


New Work im öffentlichen Sektor?!

– Verwaltung und Management, 2019. | Citations: 10.


Handbuch Digitalisierung der Verwaltung

– utb, 2023. | Citations: 8.


Wise governance: Elements of the digital strategies of municipalities

– ORAȘE INTELIGENTE ȘI DEZVOLTARE REGIONALĂ, 2022. | Citations: 8.

Hossein Ghaffarian | Machine Learning | Editorial Board Member

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Dr. Hossein Ghaffarian | Machine Learning | Editorial Board Member 

Assistant Professor | Arak University | Iran

Dr. Hossein Ghaffarian is a distinguished researcher and faculty member in the Department of Computer Engineering at Arak University, Iran, recognized for his expertise in computer networks, intelligent transportation systems (ITS), data mining, and applied artificial intelligence. His academic contributions encompass both theoretical and applied dimensions of wired and wireless network architectures, network security, and quality of service optimization. Dr. Ghaffarian’s scholarly work demonstrates a strong interdisciplinary orientation, bridging computer systems architecture with real-world applications in vehicular ad hoc networks (VANETs), indoor localization, and cloud-based network solutions. He has served in multiple academic and professional capacities, including as IT and Product Manager at Sanaat Yar Afzar Iranian and consultant for Iran’s Ministry of Education and the Electrical Industry Data Committee (Tavanir). His innovative research has earned national recognition, including a Best Paper Award at the IEEE International Conference on Internet of Things and Applications. Dr. Ghaffarian has also contributed to key industrial and governmental projects, such as developing WAN solutions for electrical industries and designing cloud-based monitoring systems. His research achievements are further complemented by his active engagement in academic translation and technical education, with works such as Python Numpy for Beginners and Python Pandas for Beginners (Farsi editions). Dr. Hossein Ghaffarian’s academic impact is reflected in his international research visibility, with 82 citations by 81 documents, 21 publications, and an h-index of 4, underscoring his growing influence in computer engineering and artificial intelligence research.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Ghaffarian, H., Fathy, M., & Soryani, M. (2012). Vehicular ad hoc networks enabled traffic controller for removing traffic lights in isolated intersections based on integer linear programming. IET Intelligent Transport Systems, 6(2), 115–123. Citations: 52

  2. Farahani, B. J., Ghaffarian, H., & Fathy, M. (2009). A fuzzy based priority approach in mobile sensor network coverage. International Journal of Recent Trends in Engineering, 2(1), 138. Citations: 19

  3. Rashvand, H. F., & Chao, H. C. (2013). Dynamic ad hoc networks. Institution of Engineering and Technology. Citations: 18

  4. Parvin, H., Minaei-Bidgoli, B., & Ghaffarian, H. (2011). An innovative feature selection using fuzzy entropy. In International Symposium on Neural Networks (pp. 576–585). Citations: 16

  5. Keramatpour, A., Nikanjam, A., & Ghaffarian, H. (2017). Deployment of wireless intrusion detection systems to provide the most possible coverage in wireless sensor networks without infrastructures. Wireless Personal Communications, 96(3), 3965–3978. Citations: 15

Ahmed Hamza Osman Ahmed | Data Science | Best Researcher Award

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Prof. Dr. Ahmed Hamza Osman Ahmed | Data Science | Best Researcher Award

Professor of Computer Science | King Abdulaziz University | Saudi Arabia

Prof. Dr. Ahmed Hamza Osman Ahmed is a distinguished computer scientist and cybersecurity expert whose research bridges artificial intelligence, information security, and data privacy. With over 70 peer-reviewed publications in prestigious journals such as IEEE, Elsevier, and Springer, his scholarly impact is evidenced by 709 citations across 658 documents and an h-index of 14, underscoring his significant contributions to the field. His research encompasses AI-driven cybersecurity systems, intrusion detection, digital forensics, and blockchain-based data integrity, with several funded projects advancing intelligent threat prediction and misinformation detection. Prof. Ahmed has played a pivotal role in developing ABET-aligned curricula, integrating machine learning into cybersecurity education, and supervising more than 25 postgraduate theses in cybersecurity and data science. Internationally recognized for academic excellence, he has received awards such as the Gold Medal at PECIPTA 2011 and Best Postgraduate Student at Universiti Teknologi Malaysia. His extensive collaborations across Saudi Arabia, Malaysia, and Sudan reflect his commitment to fostering global research partnerships and advancing secure, AI-empowered digital ecosystems. Through his leadership in teaching, research, and academic service, Prof. Ahmed continues to contribute to shaping the future of cybersecurity and artificial intelligence with profound educational and societal impact.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Elssied, N. O. F., Ibrahim, O., & Osman, A. H. (2014). A novel feature selection based on one-way ANOVA F-test for e-mail spam classification. Research Journal of Applied Sciences, Engineering and Technology, 7(3), 625–638. Citations: 223

  2. Elhadi, A. A. E., Maarof, M. A., & Osman, A. H. (2012). Malware detection based on hybrid signature behaviour application programming interface call graph. American Journal of Applied Sciences, 9(3), 283–293. Citations: 137

  3. Osman, A. H., Salim, N., Binwahlan, M. S., Alteeb, R., & Abuobieda, A. (2012). An improved plagiarism detection scheme based on semantic role labeling. Applied Soft Computing, 12(5), 1493–1502. Citations: 128

  4. Osman, A. H., & Aljahdali, H. M. (2020). An effective ensemble boosting learning method for breast cancer virtual screening using neural network model. IEEE Access. https://doi.org/10.1109/ACCESS.2020.2976149 Citations: 93

  5. Abuobieda, A., Salim, N., Albaham, A. T., Osman, A. H., & Kumar, Y. J. (2012). Text summarization features selection method using pseudo genetic-based model. In Proceedings of the 2012 International Conference on Information Retrieval & Knowledge Management (pp. 84–89). Citations: 84