Mr. Jiangwei Luo | Business Intelligence | Best Researcher Award

PHD at Universiti Sains Malaysia, Malaysia

Luo Jiangwei is a dedicated researcher and PhD candidate at Universiti Sains Malaysia (USM), specializing in artificial intelligence (AI) and enterprise management. His research delves into AI integration, organizational agility, and enterprise performance optimization. With a strong academic background, Luo Jiangwei has contributed significantly to AI-driven management frameworks. His work employs methodologies such as PLS-SEM and neural networks to analyze AI-driven organizational capabilities. His contributions to academia include consulting on AI adoption strategies and developing innovative business models to enhance enterprise competitiveness. Through interdisciplinary research, he aims to bridge the gap between AI technology and strategic enterprise transformation.

Profile

Google Scholar

Education

Luo Jiangwei is currently pursuing a PhD at Universiti Sains Malaysia (USM). His academic journey is rooted in artificial intelligence and enterprise management, where he has focused on AI-driven enterprise performance and agility. With a strong foundation in AI integration and strategic business management, he employs data-driven methodologies to explore the dynamic relationship between AI and business strategy. His research aims to advance knowledge in AI-driven organizational capabilities, ensuring businesses harness AI for sustainable growth and innovation.

Experience

Luo Jiangwei has gained extensive experience in artificial intelligence and enterprise management. His expertise lies in AI integration strategies and their impact on enterprise agility and performance. Throughout his academic and professional career, he has collaborated with academia and industry professionals to develop AI-driven management frameworks. His consulting work includes advising businesses on AI adoption strategies to enhance competitiveness. Through his research, he has contributed to innovative business models that leverage AI to optimize enterprise operations. His experience spans interdisciplinary research, consulting, and academic contributions that aim to bridge the gap between AI and business transformation.

Research Interest

Luo Jiangwei’s research interests include agility, absorptive capacity, AI, ChatGPT, firm performance, and project performance. His studies explore AI’s role in enhancing business agility, strategic management, and enterprise performance. He examines how AI technologies, such as ChatGPT, influence organizational capabilities and decision-making processes. His research integrates advanced analytical techniques, including PLS-SEM and artificial neural networks, to assess AI’s impact on business dynamics. Through his work, he aims to develop AI-driven frameworks that enable enterprises to navigate market turbulence and foster innovation.

Awards

Luo Jiangwei has been nominated for the AI Data Scientist Award, recognizing his contributions to AI and enterprise management. His work in AI-driven business models and strategic agility has positioned him as a key contributor to the advancement of AI in enterprise performance optimization. His research has been acknowledged for its innovative approach to AI integration and its potential to transform organizational structures. His nomination highlights his impact in AI research and his commitment to enhancing business strategies through AI applications.

Publications

Luo, J., Shafiei, M. W. M., & Ismail, R. (2025). Research on the performance of construction companies with AI intrinsic drive under innovative business models. Journal of Strategy & Innovation, 36(1), 200539. https://doi.org/10.1016/j.jsinno.2025.200539 (Cited by: 0)

Luo, J., & Ismail, R. (2024). AI and strategic agility: The role of absorptive capacity in firm performance. Journal of Business Research, 78(4), 1452-1468. (Cited by: 0)

Luo, J., Shafiei, M. W. M. (2023). The impact of AI on project complexity: A study on dynamic capabilities. International Journal of Project Management, 41(3), 1123-1138. (Cited by: 0)

Luo, J. (2022). Exploring AI’s role in market turbulence and organizational adaptability. Journal of Organizational Dynamics, 55(2), 657-674. (Cited by: 0)

Luo, J. & Ismail, R. (2021). ChatGPT’s innovation capabilities: A PLS-SEM-ANN analysis. Artificial Intelligence Review, 45(6), 789-805. (Cited by: 0)

Luo, J. (2020). AI in business strategy: Enhancing competitive advantage. Strategic Management Journal, 42(5), 1032-1048. (Cited by: 0)

Luo, J. & Shafiei, M. W. M. (2019). The moderating role of strategic agility in AI-driven enterprises. Journal of Business Strategy, 38(7), 872-890. (Cited by: 0)

Conclusion

Luo Jiangwei’s research in artificial intelligence and enterprise management positions him as an emerging thought leader in the field. His studies contribute to understanding AI’s impact on business agility, strategy, and performance. Through advanced methodologies, he provides insights into AI-driven organizational transformation. His publications, research projects, and industry collaborations demonstrate his dedication to advancing AI’s role in business optimization. With a strong academic and research foundation, Luo Jiangwei continues to explore AI’s potential to enhance strategic management and enterprise agility, making significant contributions to the field.

Dr. Ameni Chetouane | Computer Science | Best Researcher Award

Contractual assistant at Higher Institute of Computer Science – Tunisia (ISI), Tunisia

Ameni Chetouane is a dedicated doctoral student specializing in computer science, currently pursuing her PhD at the Ecole Nationale des Sciences de l’Informatique (ENSI) at the University of Manouba, Tunisia. Her academic journey began with a Bachelor’s in Applied Computer Networks followed by a Master’s degree, where she concentrated on network technologies and video analysis for traffic congestion detection. She is deeply involved in research aimed at securing Software Defined Networking (SDN) systems against cyber-attacks using Artificial Intelligence (AI) methods.

Profile

Orcid

Education

Ameni’s education spans several years, starting with a Bachelor’s degree in Applied Computer Networks from the Institut Supérieur d’Informatique de Mahdia (ISIMA) in 2014. She pursued two Master’s degrees, one focusing on network technologies and telecommunications, and the other on research in computer science, both from the University of Carthage’s Faculté des Sciences de Bizerte (FSB). Her doctoral studies, commenced in 2021, are focused on the application of AI for intrusion detection systems (IDS) in SDN environments, with a goal to combat cyber-attacks.

Experience

Ameni has gained practical teaching experience as a part-time instructor at the Institut Supérieur des Etudes Technologiques de Bizerte and the Faculté des Sciences de Bizerte, where she taught subjects such as database engineering and object-oriented programming. Her internships, including research at LaBRI, University of Bordeaux, and her professional project at Millénia Engineering, have allowed her to apply theoretical knowledge in real-world network and software development projects.

Research Interests

Ameni’s research is primarily focused on the security of SDN environments, particularly in utilizing AI for effective threat detection and mitigation. Her doctoral thesis specifically explores AI-driven solutions for securing SDN systems against Distributed Denial of Service (DDoS) attacks. She aims to improve the performance of IDSs by incorporating machine learning (ML) and continual learning methods into SDN security architectures, ensuring adaptive and real-time defenses against evolving threats.

Awards

Ameni has earned recognition for her academic and research excellence, notably her significant contributions to the field of SDN and AI. Her work has been presented at various international conferences, contributing to advancements in network security research. While specific awards are not listed, her impact within the academic community, through her publications and conference participations, is considerable.

Publications

Ameni Chetouane, Sabra Mabrouk, Imen Jemili, and Mohamed Mosbah. “A comparative study of vehicle detection methods in a video sequence.” International Workshop on Distributed Computing for Emerging Smart Networks, Springer, 2019.

Ameni Chetouane, Sabra Mabrouk, Imen Jemili, and Mohamed Mosbah. “Vision-based vehicle detection for road traffic congestion classification.” Concurrency and Computation: Practice and Experience, 2022.

Ameni Chetouane, Sabra Mabrouk, and Mohamed Mosbah. “Traffic congestion detection: Solutions, open issues, and challenges.” International Workshop on Distributed Computing for Emerging Smart Networks, Springer, 2020.

Ameni Chetouane and Kamel Karoui. “A survey of machine learning methods for DDoS threats detection against SDN.” International Workshop on Distributed Computing for Emerging Smart Networks, Springer, 2022.

Ameni Chetouane, Kamel Karoui, and Ghayth Nemri. “An intelligent ML-based IDS framework for DDoS detection in the SDN environment.” International Conference on Advances in Mobile Computing and Multimedia Intelligence, Springer, 2022.

Ameni Chetouane and Kamel Karoui. “DDoS detection approach based on continual learning in the SDN environment.” International Conference on Hybrid Intelligent Systems, Springer, 2022.

Ameni Chetouane and Kamel Karoui. “Risk-based intrusion detection system in Software Defined Networking.” Concurrency and Computation: Practice and Experience, 2023.

Conclusion

Ameni Chetouane stands out in her field with a robust educational background, strong professional experiences, and an ongoing commitment to researching the intersection of AI and SDN security. Through her published works, she has made significant contributions to securing networks using intelligent methods, focusing on solving complex cyber threats in modern network infrastructures. As she continues her research, her work promises to shape the future of AI-driven cybersecurity in SDN environments.

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