Daogen Jiang | Control engineering | Best Researcher Award

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Dr. Daogen Jiang | Control engineering | Best Researcher Award

Dr. Daogen Jiang,Ningbo city college of vacational technology, China

Jiang Daogen is a lecturer in automation with a Master of Engineering degree. He specializes in intelligent control technology, focusing on complex nonlinear system control, including sliding mode variable structure control and adaptive control. He has published over 20 core academic papers, including 8 indexed by SCI and EI. Jiang is the principal investigator of multiple research projects, including the Ningbo Natural Science Foundation and Zhejiang Provincial Department of Education initiatives. He actively mentors students in professional skill competitions, securing top awards. Additionally, he holds several patents and software copyrights related to control systems and automation. 🏆🔬

Publication Profile

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🎓 Education

Jiang Daogen earned his Master of Engineering degree, specializing in automation and intelligent control. His academic training provided a strong foundation in control systems, mechatronics, and adaptive technologies. His postgraduate research delved into complex nonlinear system control, focusing on sliding mode control, state-constrained nonlinear systems, and barrier Lyapunov function applications. Throughout his academic journey, he gained hands-on expertise in designing robust control algorithms for uncertain nonlinear systems. His education also emphasized industrial automation, electrical control, and embedded systems, preparing him for advanced research and teaching in automation. 📚🎓

💼 Experience

Jiang Daogen serves as a lecturer in automation, focusing on intelligent control technology and nonlinear system control. He teaches core courses, including Electrical Control and PLC, Variable Frequency Speed Regulation Technology, and Mechatronic Transmission Technology. Beyond academia, he has extensive experience guiding students in engineering competitions, leading teams to national and provincial awards. He has been the principal investigator in several high-impact research projects, including those funded by the Ningbo Natural Science Foundation. Additionally, Jiang has contributed significantly to industrial automation through his patents and software innovations in multi-axis motion control and robust adaptive control systems. 🏫⚙️

🏆 Awards & Honors

Jiang Daogen has received multiple recognitions, including the Ningbo Municipal Science and Technology Third Prize. His leadership in student competitions has earned him accolades, such as the Special Prize at the 13th Zhejiang “Challenge Cup” and the First Prize at the Zhejiang Rural Revitalization Plan College Student Competition. His research excellence has been acknowledged with funding from prestigious foundations, including the Zhejiang Provincial Department of Education. Additionally, his contributions to automation and control systems have led to several patents and software copyrights. His dedication to advancing engineering education and research continues to be recognized at institutional and governmental levels. 🏅🔬

🔬 Research Focus

Jiang Daogen’s research focuses on intelligent control technology, emphasizing complex nonlinear system control. His expertise spans sliding mode variable structure control, adaptive neural network control, and barrier function-based control strategies. He develops robust algorithms for uncertain nonlinear systems, applying them in automation, robotics, and mechatronic systems. His work also explores state-constrained control for real-world applications, enhancing system stability and performance. Jiang actively contributes to the advancement of adaptive and finite-time control techniques, with applications in precision machinery, multi-axis motion control, and industrial automation. His research outputs have been widely published in SCI and EI-indexed journals. ⚙️📡

 

Publication Top Notes

  • Adaptive Neural Network Terminal Sliding Mode Tracking Control for Uncertain Nonlinear Systems with Time-Varying State Constraints – Measurement and Control (2024-09-28) | DOI: 10.1177/00202940241279360 📝🔍

  • Nonsingular Fast Terminal Sliding Mode Control for Uncertain Nonlinear Systems Based on Adaptive Super-twisting Sliding Mode Disturbance Observer – International Journal of Control, Automation and Systems (2023-10) | DOI: 10.1007/s12555-022-0492-y 📊🔧

  • Adaptive Control for Full-States Constrained Nonlinear Systems with Unknown Control Direction Using Barrier Lyapunov Functionals – Transactions of the Institute of Measurement and Control (2022-11) | DOI: 10.1177/01423312221093826 📚💡

 

Rania Hamdani | Computer science | Best Researcher Award

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Mrs. Rania Hamdani | Computer science | Best Researcher Award

Mrs. Rania Hamdani, University of Luxembourg, Luxembourg

Rania Hamdani is a research scientist specializing in operational research, data management, and cloud architecture for Industry 5.0. Based in Luxembourg, she is currently affiliated with the University of Luxembourg, where she explores advanced methodologies for integrating and managing heterogeneous data sources. She holds an engineering degree in Software Engineering and has extensive experience in software development, AI, and DevOps. Rania has worked on multiple industry and academic projects, publishing three research papers in Ontology-Driven Knowledge Management and Cloud-Edge AI. With a strong background in programming, cloud computing, and AI-driven solutions, she has contributed to platforms ranging from job recommendation systems to adaptive human-computer interaction systems. Her expertise includes Python, SpringBoot, Kubernetes, and Azure DevOps. She is also an active member of IEEE and other technical organizations, promoting innovation and knowledge-sharing in AI and cloud technologies. 🌍💻🔬

Publication Profile

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🎓 Education

Rania Hamdani holds an Engineering Degree in Software Engineering from the National Higher School of Engineers of Tunis (2021–2024), where she specialized in advanced design, service-oriented architecture, object-oriented programming, database management, and operational research. Prior to this, she completed a two-year preparatory cycle at the Preparatory Institute for Engineering Studies of Tunis (2019–2021), undertaking intensive coursework in mathematics, physics, and technology to prepare for engineering studies. She also earned a Mathematics-specialized Baccalaureate from Pioneer High School Bourguiba Tunis (2015–2019), graduating with honors. Throughout her academic journey, she gained expertise in artificial intelligence, machine learning, cloud computing, and DevOps methodologies. Her education provided a solid foundation in programming languages, data processing techniques, and full-stack development. Additionally, she holds multiple Microsoft certifications in Azure fundamentals, AI, data security, and compliance, reinforcing her expertise in cloud-based solutions and AI-driven applications. 📚🎓💡

💼 Experience

Rania Hamdani is a research scientist at the University of Luxembourg, where she focuses on integrating and managing heterogeneous data sources for cloud-based decision-making. Previously, she was a research intern at the same institution, contributing to Ontology-Driven Knowledge Management and Cloud-Edge AI, with three published papers. She also worked as a part-time software engineer at CareerBoosts in Quebec (2021–2025), specializing in Python, Azure DevOps, Docker, and test automation. She gained industry experience through internships at Qodexia (Paris), Sagemcom (Tunisia), and Tunisie Telecom, working on smart recruitment platforms, employee management systems, and server monitoring solutions using SpringBoot, Angular, and PostgreSQL. Her technical expertise spans full-stack development, DevOps, AI-driven applications, and cloud computing. She has contributed to major projects, including an adaptive human-computer interaction system, a job recommendation system, and a problem-solving platform, demonstrating her versatility in research and software engineering. 🚀🖥️🔍

🏆 Awards & Honors

Rania Hamdani has been recognized for her outstanding contributions to AI-driven cloud computing and operational research. She received excellence awards during her engineering studies at the National Higher School of Engineers of Tunis and was among the top-performing students in her Mathematics-specialized Baccalaureate. Her research papers in Ontology-Driven Knowledge Management and Cloud-Edge AI have been acknowledged in academic circles, contributing to the advancement of Industry 5.0 technologies. She has also earned multiple Microsoft certifications in cloud and AI fundamentals, reinforcing her technical expertise. As an active member of IEEE and the Youth and Science Association, she has been involved in technology outreach and innovation-driven initiatives. Her leadership in ENSIT Junior Enterprise as a project manager further showcases her ability to lead and contribute to tech communities. These recognitions highlight her dedication to research, software development, and cloud-based AI applications. 🏅📜🌟

🔬 Research Focus

Rania Hamdani’s research focuses on operational research, data management, cloud-edge AI, and Industry 5.0 applications. She specializes in ontology-driven knowledge management, exploring methodologies for integrating heterogeneous data sources to optimize cloud-based decision-making processes. Her work includes artificial intelligence, machine learning, reinforcement learning, and human-computer interaction systems. She has contributed to projects involving job recommendation systems, adaptive human-computer interaction platforms, and cloud-based problem-solving platforms. Rania is particularly interested in scalable cloud architectures, leveraging technologies like FastAPI, Kubernetes, Docker, and Azure DevOps to build efficient AI-powered solutions. Her research also integrates graph databases, Apache Airflow, and big data analytics for enhanced data processing. By combining AI and cloud computing, she aims to develop innovative, data-driven solutions for automation, decision support, and optimization in various industrial applications. Her expertise bridges the gap between theoretical research and real-world software engineering. ☁️🤖📊

 

Publication Top Notes

Adaptive human-computer interaction for industry 5.0: A novel concept, with comprehensive review and empirical validation

 

Weibing LI | Computational Intelligence and Robotics | Best Researcher Award

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Weibing LI | Computational Intelligence and Robotics | Best Researcher Award

Associate Professor at  Sun Yat-sen University , China

Dr. Weibing Li is an Associate Professor at the School of Computer Science and Engineering, Sun Yat-sen University, China. He holds a Ph.D. in Mechanical Engineering from the University of Leeds, UK (2018) and specializes in robotics 🤖, neural networks 🧠, and optimization 🔢. His research focuses on industrial and medical robotics, deep learning, and nonlinear programming. A recipient of multiple national and regional research grants, he has published extensively in top-tier IEEE journals. Dr. Li also worked as a Postdoctoral Researcher at The Chinese University of Hong Kong. 📧

Publication Profile

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🎓 Academic Background 

Dr. Weibing Li holds a Ph.D. in Mechanical Engineering (2018) from the University of Leeds, UK 🇬🇧, where he worked under Prof. Robert Richardson and Prof. Jongrae Kim. He earned his M.S. in Detection Technology and Automatic Equipment (2014) from Sun Yat-sen University, China 🇨🇳, guided by Prof. Yunong Zhang, and a B.S. in Communication Engineering (2011) from Changchun University. His research focuses on robotics 🤖 (industrial, medical, modular), neural networks 🧠 (deep learning, reinforcement learning), and operations research 🔢 (optimization, nonlinear programming, cybernetics), contributing significantly to AI-driven robotic applications. 🚀

👨‍🏫 Professional Experience

Dr. Weibing Li is an Associate Professor at the School of Computer Science and Engineering, Sun Yat-sen University 🇨🇳 (since 2020), where he advances research in robotics and AI. Previously, he was a Postdoctoral Researcher at the Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong 🇭🇰 (2018-2020), working under Prof. Zheng Li on medical robotics. He also served as a Robotics Assistant at the University of Leeds, UK 🇬🇧 (2017-2018), contributing to advanced robotic systems under Prof. Robert C. Richardson. His expertise spans intelligent automation, neural computation, and robotic control. 🤖🚀

🔬 Research Focus Areas

Dr. Weibing Li’s research spans robotics 🤖, neural networks 🧠, and operations research 📊. His work in industrial, medical, and modular robotics focuses on intelligent control and automation. In neural networks, he explores deep learning, reinforcement learning, and neural computation. His contributions to operations research and cybernetics include optimization techniques like linear and nonlinear programming. He leads multiple projects, including research on robotic endoscopes, intelligent control algorithms, and recurrent neural networks. His work enhances robotic precision, human-robot interaction, and AI-driven automation, contributing significantly to robotic intelligence and healthcare technologies. 🚀

Publication Top Notes

1️⃣ An Accelerated Anti-Noise Adaptive Neural Network for Robotic Flexible Endoscope With Multitype Surgical Objectives and Constraints 🏥🤖
Year: 2025 | Publisher: IEEE

2️⃣ A Quadratic Programming Solution to Position-Level Repetitive Motion Planning and Obstacle Avoidance of Joint-Constrained Robots 📏🤖
Year: 2025 | Publisher: IEEE

3️⃣ A Cerebellar Model Articulation Controller Enhanced Neural Solution to Time-Varying Linear Equations With Robotic Application 🧠🤖
Year: 2024 | Publisher: IEEE

4️⃣ X-Ray-Based Three-Dimensional Shape Reconstruction Method for a Continuum Manipulator 📸🤖
Year: 2024 | Publisher: IEEE

5️⃣ Visual Exploration-Enhanced Quadruped Robot with Active-Passive Composite Telescope Mechanism 🦿🤖
Year: 2024 | Publisher: IEEE