Aman Bin Jantan | Computer Science | Best Researcher Award

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

Universiti Sains Malaysia | Malaysia

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Early Academic Pursuits ๐ŸŽ“

Assoc. Prof. Dr. Aman Bin Jantan's academic journey is rooted in a strong foundation in computer science. He earned his Bachelorโ€™s degree (1993) and Masterโ€™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 languagesโ€”a groundbreaking contribution to the field.

Professional Endeavors ๐Ÿข

Dr. Aman has had an extensive career in both academia and industry. His professional journey began as a Research Officer at USMโ€™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 USMโ€™s School of Computer Sciences, where he now serves as an Associate Professor.

Contributions and Research Focus ๐Ÿ”ฌ

Dr. Amanโ€™s research spans across multiple domains, including:
Information Security โ€“ Intrusion Detection, Cyberwarfare, Encryption, Steganography, and Electronic Forensics.
Software Engineering โ€“ Fault Tolerance, Component-Based System Development, and Software Quality Assurance.
Artificial Intelligence โ€“ 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 ๐Ÿ†

Dr. Amanโ€™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 ๐ŸŒ

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 ๐Ÿš€

Dr. Amanโ€™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


  • ๐Ÿ“„ 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


  • ๐Ÿ“„ 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


  • ๐Ÿ“„ 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


  • ๐Ÿ“„ 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


  • ๐Ÿ“„ 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


 

Qiuping Li | Mathematics | Best Researcher Award

Dr. Qiuping Li | Mathematics | Best Researcher Award

Gansu University of Political Science and Law | China

Author Profile

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Early Academic Pursuits ๐ŸŽ“

Dr. Qiuping Li embarked on his academic journey with a Bachelor of Science in Information and Computational Science from Jilin University, where he developed a strong foundation in mathematical modeling and computational analysis. His passion for theoretical mathematics led him to pursue a Ph.D. in Applied Mathematics at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences in Beijing. During this time, he honed his expertise in graph theory, delving into its complex structures and applications.

Professional Endeavors ๐Ÿ›๏ธ

As a dedicated academic, Dr. Li has held key positions in prestigious institutions. He served as a lecturer at the School of Computer Science and Technology at Hengyang Normal University from 2018 to 2024, where he mentored aspiring mathematicians and contributed significantly to research in graph theory and cryptography. In 2025, he transitioned to the School of Cyber Security at Gansu University of Political Science and Law, focusing on integrating graph theory with network security, reinforcing his role as a leading researcher in these domains.

Contributions and Research Focus ๐Ÿ”ฌ

Dr. Li's research spans several critical areas, including graph theory, network security, and cryptographic algorithms. His work on graph energy, order-energetic graphs, and lightweight cryptography has provided valuable insights into mathematical structures and their real-world applications. His contributions to the field are reflected in multiple SCI-indexed publications, including his studies on infinite classes of L-borderenergetic graphs and graph energy changes due to edge deletion. His research has enhanced the understanding of structural properties in computational chemistry and network systems.

Accolades and Recognition ๐Ÿ†

Dr. Liโ€™s groundbreaking research has earned him recognition in the academic community. His publications in prestigious journals such as MATCH Communications in Mathematical and Computer Chemistry have been widely cited and referenced by fellow researchers. His expertise in cryptography has also led to the development of novel block cipher algorithms, with several patents granted for innovative encryption methodologies. His contributions to lightweight block ciphers have positioned him as a thought leader in secure communication technologies.

Impact and Influence ๐ŸŒ

Beyond academia, Dr. Liโ€™s research has profound implications for cybersecurity and mathematical modeling. His advancements in graph theory contribute to network security by optimizing encryption methods, ensuring more robust data protection. His patented cryptographic algorithms offer practical solutions for secure digital communication, addressing modern challenges in information security. Through his teachings and mentorship, he continues to inspire the next generation of researchers, fostering a new wave of innovation in applied mathematics and cryptography.

Legacy and Future Contributions ๐Ÿ”ฎ

Dr. Qiuping Liโ€™s legacy is defined by his relentless pursuit of knowledge and his commitment to advancing mathematical research. His work in graph theory and cryptography will continue to influence academic discourse and practical applications in cybersecurity. As he progresses in his career, he is poised to further bridge the gap between theoretical mathematics and real-world problem-solving, paving the way for new breakthroughs in secure systems and network analysis. His dedication to research and education ensures that his contributions will leave a lasting imprint on both academia and industry.

Publications


  • ๐Ÿ“„ A New Family of Multipartition Graph Operations and Its Applications in Constructing Several Special Graphs

    • Authors: Qiuping Li, Liangwen Tang, Qingyun Liu, Mugang Lin

    • Journal: Symmetry

    • Year: 2025


  • ๐Ÿ“„ Infinite Numbers of Infinite Classes of L-Borderenergetic Graphs

    • Authors: Qiuping Li, Liangwen Tang

    • Journal: MATCH Communications in Mathematical and Computer Chemistry

    • Year: 2023


  • ๐Ÿ“„ Construction of Order-Energetic Graphs

    • Authors: Qiuping Li, Liangwen Tang, Qingyun Liu, Mugang Lin

    • Journal: MATCH Communications in Mathematical and Computer Chemistry

    • Year: 2024


  • ๐Ÿ“„ Graph Energy Change on Edge Deletion

    • Authors: Liangwen Tang, Mugang Lin, Qiuping Li

    • Journal: MATCH Communications in Mathematical and Computer Chemistry

    • Year: 2023


  • ๐Ÿ“„ Lightweight Block Ciphers

    • Authors: Li Lang, Li Qiuping

    • Publisher: Huazhong University of Science and Technology Press

    • Year: 2020