Zaynab BOUJELB | Engineering | Best Researcher Award

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Dr. Zaynab BOUJELB | Engineering | Best Researcher Award

Doctor in Biomedical Engineering at Ibn Tofail University, Morocco

Boujelb Zaynab is a Moroccan biomedical engineer and researcher specializing in medical imaging, hospital equipment management, and artificial intelligence applications in healthcare. With a strong academic background in biomedical engineering, radiology, physics, and artificial intelligence, she has developed expertise in medical instrumentation, radioprotection, and healthcare technology management. She is actively involved in teaching, research, and professional engagements in both public and private institutions. Her work spans hospital infrastructure, quality control, and advanced imaging techniques. She has contributed to various academic projects, including the development of AI-based detection systems and healthcare management applications. Fluent in Arabic, French, and English, she collaborates on research and academic initiatives, making significant contributions to the biomedical field.

Professional Profile

Education

Boujelb Zaynab is currently pursuing a Ph.D. in Biomedical Engineering, Physics, and Artificial Intelligence at Ibn Tofail University, Kenitra (2021-2025). She holds an Engineering degree in Biomedical Engineering with a specialization in Hospital Instrumentation from ENSAM, Rabat (2017-2020). She also earned a Bachelor’s degree in Radiology from the Higher Institute of Nursing and Health Techniques, Rabat (2014-2017), and another Bachelor’s degree in Physics and Computer Science from the Faculty of Sciences, Rabat (2010-2014). Her multidisciplinary educational background has enabled her to develop a deep understanding of biomedical sciences, imaging techniques, and healthcare technology, equipping her with the skills necessary for academic research and professional practice.

Professional Experience

Boujelb Zaynab has extensive professional experience in academia, research, and biomedical engineering. She is currently a faculty member at the Higher Institute of Nursing and Health Techniques in Rabat, responsible for diploma equivalence evaluations, international cooperation, and teaching courses in quality management and medical maintenance. She also serves as a biomedical engineer at the Directorate of Equipment and Maintenance, where she is involved in hospital equipment acquisition, project management, and quality control. Additionally, she has worked at Mohammed VI University of Health Sciences as a lecturer in advanced medical imaging techniques. Her experience includes supervising student research projects, overseeing hospital equipment installations, and participating in public health initiatives. She has also contributed to healthcare policy discussions and procurement processes, enhancing hospital infrastructure.

Research Interests

Boujelb Zaynab’s research interests lie at the intersection of biomedical engineering, artificial intelligence, and medical imaging. She focuses on developing AI-based detection systems for radiology and imaging applications, enhancing hospital equipment management through automation, and improving radioprotection techniques. Her academic projects have included real-time motion detection in radiology, AI-assisted tumor measurement, fall detection systems for elderly care, and healthcare management applications. She is particularly interested in the integration of machine learning with imaging modalities such as MRI and CT scans to improve diagnostic accuracy and patient safety. Additionally, she explores quality control measures in healthcare infrastructure and the optimization of biomedical equipment to enhance hospital efficiency.

Research Skills

Boujelb Zaynab possesses strong technical and analytical skills in biomedical engineering and healthcare technology. She is proficient in medical imaging techniques, radioprotection, signal processing, and automated biomedical systems. Her expertise includes electronic circuit design, machine learning for medical diagnostics, and computerized maintenance management systems (CMMS). She is skilled in programming languages such as MATLAB, LabVIEW, and Java, which she applies in medical data analysis and AI-based healthcare solutions. Additionally, she has experience in project management, feasibility studies, and quality control of hospital equipment. Her ability to integrate theoretical knowledge with practical applications allows her to conduct impactful research and implement innovative healthcare solutions.

Awards and Honors

Although specific awards and honors are not mentioned in her profile, Boujelb Zaynab has demonstrated academic excellence through her contributions to biomedical research and engineering. She has actively participated in national conferences and collaborated on innovative healthcare projects. Her role in supervising student research and developing hospital equipment management solutions highlights her contributions to the field. She has also played a key role in institutional and governmental healthcare initiatives, which reflect her expertise and commitment to advancing biomedical science and technology. Recognition in academic circles and her involvement in significant projects suggest that she has the potential to achieve further accolades in the future.

Conclusion

Boujelb Zaynab is a dedicated biomedical engineer and researcher with expertise in medical imaging, hospital equipment management, and artificial intelligence applications in healthcare. Her multidisciplinary background, research contributions, and teaching experience make her a valuable asset to the field. While she has demonstrated significant professional and academic achievements, further publications in high-impact journals, international collaborations, and research funding would strengthen her profile. Her strong technical skills, research acumen, and commitment to innovation position her as a promising researcher in biomedical engineering. With continued advancements in her research and increased recognition through publications and patents, she has the potential to make lasting contributions to the field of healthcare technology.

Publication Top Notes

  1. “Motion Detection for Patient Safety in CT Scanner”

    • Authors: Zaynab Boujelb, Ahmed Idrissi, Achraf Benba, El Mahjoub Chakir
    • Year: 2025
    • Source: Results in Engineering
    • DOI: 10.1016/j.rineng.2025.103938

  2. “Detecting Hemorrhagic Stroke from Computed Tomographic Scans Using Machine Learning Models Comparison”

    • Authors: Zaynab Boujelb, Ahmed Idrissi, Achraf Benba, El Mahjoub Chakir
    • Year: 2024
    • Source: Data and Metadata
    • DOI: 10.56294/dm2024.548

Ronghao Wang | Engineering | Best Researcher Award

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Prof. Dr. Ronghao Wang | Engineering | Best Researcher Award

Professor from Army Engineering University of PLA, China

Ronghao Wang, PhD, is a professor and doctoral supervisor with extensive experience in control systems and automation. He has led multiple prestigious research projects, including two grants from the National Natural Science Foundation of China (NSFC) and several provincial-level projects. His contributions span over 120 academic papers, with more than 30 indexed in SCI and two highly cited in ESI. He has authored two academic monographs and holds more than 10 authorized invention patents and software copyrights. His expertise lies in computer control, robust control, intelligent control, switching systems, and multi-agent systems. Ronghao Wang serves as a thesis review expert for the Ministry of Education, a communication evaluation expert for NSFC, and holds membership in key professional societies. He has received provincial and ministerial-level awards for scientific and technological progress and enjoys a distinguished reputation in his field. In addition to research, he has editorial roles in core academic journals and contributes significantly to the advancement of automation and control engineering.

Professional Profile

Education

Ronghao Wang earned his PhD in a relevant engineering discipline, specializing in automation and control systems. His academic journey provided him with a strong foundation in computer control, robust control, and multi-agent systems. He pursued undergraduate and graduate studies at esteemed institutions in China, gaining expertise in theoretical and applied research. His doctoral research focused on developing intelligent control methodologies for complex systems, paving the way for his future work in switching systems and automation. Throughout his academic career, he received rigorous training in mathematical modeling, system optimization, and computational techniques, which shaped his approach to solving real-world engineering problems. His education also included interdisciplinary exposure to artificial intelligence, software development, and networked control systems, enhancing his research capabilities. Through continuous learning and professional development, he has remained at the forefront of technological advancements in control engineering.

Professional Experience

Ronghao Wang has a distinguished career in academia and research. He currently serves as a professor and doctoral supervisor, mentoring graduate students and leading cutting-edge research projects. Over the years, he has been at the helm of several national and provincial research initiatives, securing competitive grants and contributing to advancements in automation and control. He has also been actively involved in peer review, serving as an expert evaluator for NSFC and the Ministry of Education. His expertise extends to editorial responsibilities, where he is a board member for multiple core journals. His professional memberships include the Chinese Society of Command and Control and the Chinese Society of Automation. In addition to academic roles, he has contributed to industry collaborations, applying his research to real-world engineering challenges. His experience in managing multidisciplinary projects and fostering innovation has strengthened his reputation as a leader in control systems research.

Research Interests

Ronghao Wang’s research focuses on advanced control systems, including computer control, robust control, intelligent control, switching systems, and multi-agent systems. His work aims to enhance the stability, efficiency, and adaptability of automated processes across various industries. His research explores novel methodologies in intelligent decision-making, real-time system optimization, and networked control applications. He has a keen interest in developing control algorithms for complex and dynamic systems, improving fault tolerance, and enhancing system resilience. His contributions extend to automation in industrial settings, where he investigates smart manufacturing solutions. His interdisciplinary approach integrates artificial intelligence and machine learning into control engineering, pushing the boundaries of automation technology. With a strong publication record and extensive project leadership, he continues to advance the field of intelligent and adaptive control systems.

Research Skills

Ronghao Wang possesses expertise in mathematical modeling, system optimization, algorithm development, and simulation techniques. He is proficient in developing robust control strategies and designing intelligent control frameworks for complex systems. His skills include working with control theory, stability analysis, and real-time system implementation. He has extensive experience with software tools for modeling and simulation, including MATLAB and Simulink, as well as programming languages relevant to control systems. His ability to integrate AI-driven techniques into control applications enhances his research impact. Additionally, he is skilled in technical writing, peer review, and academic publishing, contributing to high-impact scientific literature. His research experience also encompasses experimental validation, prototype development, and interdisciplinary collaboration, making him a well-rounded expert in automation and control engineering.

Awards and Honors

Ronghao Wang has received several prestigious awards in recognition of his research contributions. He has been honored with a second prize and a third prize for scientific and technological progress at the provincial and ministerial levels. His contributions to automation and control have been acknowledged through multiple research grants, including two NSFC projects and a key sub-project under the Science and Technology Innovation Special Zone. He has been appointed as a senior member of the Chinese Society of Command and Control and has received a professional and technical talent allowance at the provincial and ministerial levels. His role as a reviewer and evaluator for national scientific bodies further highlights his influence and standing in the research community. These accolades reflect his commitment to advancing the field of intelligent control and automation.

Conclusion

Ronghao Wang is a leading researcher in automation and control, with significant contributions to academic literature, technological innovation, and project leadership. His extensive research output, professional recognition, and active engagement in national and provincial initiatives make him a strong candidate for prestigious research awards. His ability to secure competitive funding, mentor graduate students, and advance interdisciplinary research further strengthens his profile. While his achievements are commendable, expanding international collaborations and securing higher-tier national or global awards could enhance his impact. His work continues to push the boundaries of intelligent control, automation, and system optimization, making him a key figure in his field.

Publication Top Notes

  1. “Consensus of Multi-Agent Systems with Two-Layer Hierarchical Topology under Intermittent Communication”

    • Authors: Zhaoxia Duan, Jun Dai, Zhen Shao, Ronghao Wang
    • Year: 2024

  2. “Adaptive Finite-Time Stabilizing Control of Fractional-Order Nonlinear Systems with Unmodeled Dynamics via Sampled-Data Output-Feedback”

    • Authors: Jun Mao, Ronghao Wang, Wencheng Zou, Zhengrong Xiang
    • Year: 2024
    • Citations: 1

  3. “Distributed Adaptive Control for Multiple Unmanned Aerial Vehicles with State Constraints and Input Quantization”

    • Authors: Moshu Qian, Tian Le, Cunsong Wang, Ronghao Wang, Cuimei Bo
    • Year: 2024.

  4. “Global Path Planning for Amphibious Unmanned Vehicles with Multiple Constraints via Deep Reinforcement Learning”

    • Authors: Ting Wu, Ronghao Wang, Yan Zhang, Yuzhu Xiang, Zhengrong Xiang

  5. “Fault Diagnosis and Location Research for Distributed Control System of Offshore Wind Turbines”

    • Authors: Shaoping Wang, Ronghao Wang, Zhaoxia Duan

  6. “Improved Quantized Predictive Iterative Learning Control for Systems with Variable Interval Lengths and Data Dropouts”

    • Authors: Zhen Shao, Songyi Xue, Ronghao Wang, Zhaoxia Duan, Fanrong Kong

  7. “A 2-Step Multi-Energy Coupling and Substitution Reconfiguration Strategy for Distribution Network Restoration”

    • Authors: Jiayu Lin, Ronghao Wang

  8. “Harmonic Source State Identification Using Random Forest”

    • Authors: Yundi Chu, Haixia Li, Yu Liu, Ruihai Sun, Ronghao Wang