Mariam Ben Hassen | Computer Science | Editorial Board Member

Published on by Award and Honors

Assist. Prof. Dr. Mariam Ben Hassen | Computer Science | Editorial Board Member

Assist. Prof. Dr. Mariam Ben Hassen | University of Sfax | Tunisia

Dr. Mariam Ben Hassen is a computer science scholar recognized for her contributions to knowledge management, business process modeling, ontology engineering, and decision support. Her work bridges theoretical innovation with practical frameworks for designing and specifying complex enterprise information systems, emphasizing multi-dimensional modeling, intelligent systems, and extending BPMN through ontological structures. Her research develops conceptual and ontological frameworks to model sensitive business processes, enhance enterprise information systems, and support knowledge-driven decision-making. She has extensive experience in academic teaching, research supervision, and project leadership, producing impactful publications in high-ranking journals and international conferences. Her scholarship integrates knowledge representation with organizational processes, advancing modern perspectives in information systems engineering and providing valuable tools for intelligent, data-informed enterprise management.

Profile : Google Scholar 

Featured Publications 

Conceptual Analysis of Sensitive Business Processes. (2023). Business Process Management Journal. Cited by: N/A.

 

Zhen Yang | Computer Science | Best Researcher Award

Published on by Award and Honors

Assist. Prof. Dr. Zhen Yang | Computer Science | Best Researcher Award

Deputy Director | Jiangxi Science and Technology Normal University | China

Dr. Zhen Yang is an accomplished Associate Professor at the Jiangxi Provincial Key Laboratory of Advanced Electronic Materials and Devices, Jiangxi Science and Technology Normal University, China, with a strong background in automation and control engineering. He earned his B.S. in Automation from Changchun Institute of Technology, his M.S. in Control Theory and Control Engineering from Qingdao University of Science & Technology, and his Ph.D. in Control Science and Engineering from Shanghai Jiao Tong University, where he focused on integrating computational intelligence with control systems. Dr. Yang’s research bridges theory and practice in computer vision, machine learning, and remote sensing, with applications in crop disease and pest recognition, remote sensing image classification, and precision agriculture. He has led numerous research projects, supervised graduate students, and collaborated with academic and industry partners to develop intelligent monitoring systems and data-driven agricultural solutions. Recognized for his scholarly contributions, innovative mindset, and practical impact, Dr. Yang has received awards for his research excellence and technological innovations. His work exemplifies the integration of advanced algorithms with real-world applications, addressing environmental monitoring, sustainable agriculture, and intelligent system design, establishing him as a leading figure in his field.

Profile : ORCID 

Featured Publications

Yang, Z., et al. (2021). Deep learning for crop disease recognition in remote sensing images. IEEE Transactions on Geoscience and Remote Sensing. (Cited by 45)

Yang, Z., et al. (2020). Intelligent pest detection using convolutional neural networks. Computers and Electronics in Agriculture. (Cited by 38)

Yang, Z., et al. (2019). Remote sensing image classification with machine learning techniques. Remote Sensing. (Cited by 52)