Regner Sabillon  | Computer Science | Best Researcher Award

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Prof. Regner Sabillon | Computer Science | Best Researcher Award 

International University of La Rioja | Canada

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Early Academic Pursuits

Prof. Regner Sabillon embarked on a diverse and interdisciplinary academic journey rooted in aviation, computer science, and cybersecurity. He began his academic career with a Bachelor's degree in Computer Science from the Universidad de San Pedro Sula, Honduras. He later completed an MBA from the Universidad Politecnica de Madrid, Spain, with specializations in IT Systems Management and Business Administration. His academic thirst extended to include a Master of Science in Knowledge and Information Society from Universitat Oberta de Catalunya and further certifications from institutions like DeVry Institute of Technology and SAIT in Calgary. Currently, he is a Ph.D. candidate at the Universidad Internacional de La Rioja, Spain, focusing on cybersecurity audit, assurance, and awareness.

Professional Endeavors

Prof. Sabillon's extensive professional career spans over two decades in diverse IT and cybersecurity roles. From his early years as a military aviator to becoming a certified cybersecurity leader, his contributions include IT consulting, cybersecurity management, technical training, and educational leadership. He has held notable roles such as Cybersecurity Lead at SAIT, Bow Valley College, and Columbia College. He has also worked with organizations like Gran Tierra Energy, Tuscany LP, and the United Nations (UNDP) in international ICT consultancy roles. In academia, he currently serves as a lead professor at SAIT and instructor at various Canadian institutions including Athabasca University and Loyalist College.

Contributions and Research Focus

Prof. Sabillon's research spans critical areas of cybersecurity, including governance, digital forensics, cyber law, and cybersecurity awareness. His scholarly work focuses on developing practical models such as the CyberSecurity Audit Model (CSAM 2.0) and the Cybersecurity Awareness Training Model (CATRAM 2.0) aimed at improving organizational cybersecurity posture. He has published extensively in renowned journals and presented at international conferences such as IEEE SysCon, HCII, and CISTI. His current Ph.D. thesis delves into cybersecurity models for improving assurance and organizational resilience.

Accolades and Recognition

Prof. Sabillon has earned multiple prestigious awards including the Instructor Excellence Nominee (2024) at SAIT and the 2009 Outstanding Mentor Award from the Network Professional Association. His book on cybersecurity was ranked #1 by BookAuthority in several categories including Best New Cybersecurity Books. He also received the second-best research paper award at the INCISCOS 2017 conference. His extensive certifications, including C|CISO, CRISC, CGEIT, and ISO 27001 Lead Auditor, further establish his expertise and reputation.

Impact and Influence

Prof. Sabillon's work has significantly shaped the academic and professional landscape of cybersecurity in Canada and beyond. His curriculum development efforts at SAIT have influenced the structure of post-diploma cybersecurity programs, equipping the next generation of IT professionals with critical skills. Through his audit and awareness models, he has strengthened cybersecurity practices in academic and corporate institutions.

Legacy and Future Contributions

Prof. Sabillon continues to build a legacy of excellence in cybersecurity education and practice. With a deep commitment to knowledge sharing, training, and systems improvement, he is poised to contribute further to global cybersecurity standards and education reform. As he completes his Ph.D., his ongoing scholarly work and professional leadership promise lasting contributions to digital safety, governance, and risk management across sectors.

Publications

Cybersecurity Audit, Assurance and Awareness: Cybersecurity Models to Improve the Organizational Cybersecurity Posture
Author: Regner Sabillon
Journal: Unpublished Doctoral Dissertation
Year: 2025

Assessing the Effectiveness of Cyber Domain Controls When Conducting Cybersecurity Audits: Insights from Higher Education Institutions in Canada
Authors: Regner Sabillon, Juan Ramon Bermejo Higuera, Jeimy Cano, Javier Bermejo Higuera, Juan Antonio Sicilia Montalvo
Journal: Electronics
Year: 2024

Planning and Conducting Cybersecurity Audits to Assess the Effectiveness of Controls
Authors: Regner Sabillon, M. Barr
Conference Proceedings: IEEE International Systems Conference (SysCon), Montréal, Québec, Canada
Year: 2024

The Importance of Cybersecurity Awareness Training in the Aviation Industry for Early Detection of Cyberthreats and Vulnerabilities
Authors: Regner Sabillon, Juan Ramon Bermejo Higuera
Conference: HCI International 2023 – Late Breaking Papers
Year: 2023

The Importance of Cybersecurity Awareness Training in the Aviation Industry for Early Detection of Cyberthreats and Vulnerabilities
Author: Regner Sabillon
Conference: 25th International Conference on Human-Computer Interaction (HCII 2023)
Year: 2023

Conclusion

Prof. Regner Sabillon exemplifies academic and professional excellence in cybersecurity. His vast array of qualifications, scholarly contributions, and real-world applications reflect a unique blend of intellect and impact. With a focus on innovation, education, and strategic governance, Prof. Sabillon remains a transformative figure in the realm of computer science and cybersecurity.

Aman Bin Jantan | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Aman Bin Jantan | Computer Science | Best Researcher Award

Universiti Sains Malaysia | Malaysia

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Early Academic Pursuits 🎓

Assoc. Prof. Dr. Aman Bin Jantan's academic journey is rooted in a strong foundation in computer science. He earned his Bachelor’s degree (1993) and Master’s in Computer Science (AI) (1996) from Universiti Sains Malaysia (USM), where he laid the groundwork for his expertise in artificial intelligence and software engineering. His research on FrameLog Compiler Construction during his MSc reflected an early inclination toward programming languages and AI-driven system development. His PhD in Software Engineering (2002) from USM further solidified his prowess, focusing on the redefinition of expert system development languages—a groundbreaking contribution to the field.

Professional Endeavors 🏢

Dr. Aman has had an extensive career in both academia and industry. His professional journey began as a Research Officer at USM’s AI Lab in 1993, followed by roles as a Graduate Assistant and Lecturer. His passion for education saw him taking up lecturing positions at Stamford College, UiTM Shah Alam, and USM. Apart from academia, he ventured into the tech industry by establishing his own ICT business, offering software solutions, IT services, and computer training. Since 2002, he has been an integral part of USM’s School of Computer Sciences, where he now serves as an Associate Professor.

Contributions and Research Focus 🔬

Dr. Aman’s research spans across multiple domains, including:
Information Security – Intrusion Detection, Cyberwarfare, Encryption, Steganography, and Electronic Forensics.
Software Engineering – Fault Tolerance, Component-Based System Development, and Software Quality Assurance.
Artificial Intelligence – Machine Learning, Neuro-Fuzzy Systems, and Expert Systems.

His work on network security, intrusion detection, and machine learning-driven cybersecurity solutions has significantly impacted the field. His innovative Honeybee Intelligent Model for Network Zero-Day Attack Detection is a notable contribution that has been widely recognized.

Accolades and Recognition 🏆

Dr. Aman’s excellence in teaching and research has earned him multiple Excellent Service Awards (2007, 2011, 2020). His publications in high-impact journals, including those on financial crime prevention, AI-driven profiling, and cybersecurity measures, have established him as a thought leader in his domain.

Impact and Influence 🌍

As an academic and researcher, Dr. Aman has shaped the next generation of cybersecurity experts and software engineers. His workshops, mentorship, and leadership in the field of information security have influenced policy-making and corporate cybersecurity strategies. His Security and Forensic Research Group Laboratory at USM is a hub for cutting-edge research in cyber defense technologies.

Legacy and Future Contributions 🚀

Dr. Aman’s contributions to artificial intelligence, cybersecurity, and software engineering will continue to shape the landscape of digital security and computing. His commitment to advancing cybersecurity education and research ensures that future professionals will be well-equipped to tackle emerging threats in an increasingly digital world. With a strong portfolio of research, industry collaborations, and mentorship, Dr. Aman remains a driving force in the evolution of AI-driven security solutions. His future work is expected to redefine the intersection of AI and cybersecurity, making digital systems safer and more resilient.

Publications

  • 📄 Enhancing Neighborhood-Based Co-Clustering Contrastive Learning for Multi-Entity Recommendation

    • Authors: J. Liao, Juan; A.B. Jantan, Aman Bin; Z. Liu, Zhe

    • Journal: Engineering Applications of Artificial Intelligence

    • Year: 2025

  • 📄 Digital Forensic Investigation on Social Media Platforms: A Survey on Emerging Machine Learning Approaches

    • Authors: A.A. Kazaure, Abdullahi Aminu; A.B. Jantan, Aman Bin; M.N. Yusoff, Mohd Najwadi

    • Journal: Journal of Information Science Theory and Practice

    • Year: 2024

  • 📄 Digital Forensics Investigation Approaches in Mitigating Cybercrimes: A Review

    • Authors: A.A. Kazaure, Abdullahi Aminu; A.B. Jantan, Aman Bin; M.N. Yusoff, Mohd Najwadi

    • Journal: Journal of Information Science Theory and Practice

    • Year: 2023

  • 📄 A Machine Learning Classification Approach to Detect TLS-Based Malware Using Entropy-Based Flow Set Features (Open Access)

    • Authors: K. Keshkeh, Kinan; A.B. Jantan, Aman Bin; K. Alieyan, Kamal

    • Journal: Journal of Information and Communication Technology

    • Year: 2022

  • 📄 Multi-Behavior RFM Model Based on Improved SOM Neural Network Algorithm for Customer Segmentation (Open Access)

    • Authors: J. Liao, Juan; A.B. Jantan, Aman Bin; Y. Ruan, Yunfei; C. Zhou, Changmin

    • Journal: IEEE Access

    • Year: 2022