Prof. Yunxia Chen | Intelligent Manufacturing | Best Researcher Award

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Prof. Yunxia Chen | Intelligent Manufacturing | Best Researcher Award

School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, China

Dr. Yunxia Chen is a distinguished professor at Shanghai Polytechnic University, specializing in Materials Science and Engineering. With a Ph.D. from Shanghai Jiaotong University, Dr. Chen has an extensive academic and professional background in advanced welding technologies and materials science. Throughout his career, he has contributed to the field with research focused on the weldability of dissimilar metals, microstructure and mechanical properties of welded joints, and cutting-edge welding technologies. Dr. Chen has worked as a professor, associate professor, and postdoctoral researcher, and has extensive industrial experience as a welding engineer. His academic journey is complemented by his roles in organizing significant international conferences and publishing numerous impactful research papers.

Publication Profile

Scopus

Education:

Dr. Yunxia Chen earned his Ph.D. in Materials Science and Engineering from Shanghai Jiaotong University in 2010, under the supervision of Prof. Shun Yao. His thesis titled “Research of Rapid Prototyping System Based On 3D Scanning Electron Beam” reflects his focus on advanced manufacturing technologies. He completed his M.Sc. in the same field from Dalian Jiaotong University in 2005, where he worked under Prof. Xiongming Zhang on the “Electric Control Study of Conform Production Line Drawing and Rolling Machine.” He received his B.Eng. in Materials Science and Engineering from Dalian Jiaotong University in 1999.

Experience:

Dr. Yunxia Chen has held several prominent academic and professional positions. Since 2024, he has been serving as a professor at Shanghai Polytechnic University. Prior to that, he was an Associate Professor and Professor at Shanghai Dianji University from 2015 to 2023. Dr. Chen also held a postdoctoral position at Shanghai Jiaotong University from 2013 to 2015. Early in his career, he worked as a Welding Engineer at Changchun Railway Vehicles Co., Ltd., from 1999 to 2002. Dr. Chen has also contributed to the academic community by interviewing for significant international conferences, including the 4th International Conference on Robotic Welding, Intelligence, and Automation, in 2014.

Awards and Honors:

Dr. Yunxia Chen’s work has earned him several accolades, reflecting his excellence in research and teaching. He has received awards for his contributions to the field of welding and materials science, including recognition at international conferences and accolades for his innovative research in welding technologies. His research excellence has made a significant impact in both academic and industrial sectors.

Research Focus:

Dr. Chen’s primary research interests lie in the weldability of metals, particularly dissimilar metal welding, and the microstructural and mechanical properties of welded joints. He has extensively explored advanced welding technologies and the effects of welding processes on material properties. His work is pivotal in understanding the behavior of metals during welding and the challenges associated with improving the quality and strength of welded joints. Dr. Chen also investigates the role of microstructure in determining the mechanical properties and performance of materials used in welding.

Conclusion:

Dr. Yunxia Chen’s career stands as a testament to his dedication to advancing materials science and welding technology. His innovative research has paved the way for improvements in the welding industry, addressing both practical and theoretical challenges. Through his academic roles, industrial experience, and research endeavors, Dr. Chen continues to make significant contributions to the field, impacting both the scientific community and industrial practices.

Publications:

Detection of Welding Defects Tracked by YOLOv4 Algorithm
Published: 2025, Applied Sciences
Link: DOI: 10.3390/app15042026

NiFe2O4/Polypyrrole Metacomposites with Tunable Negative Permittivity for Enhanced Electromagnetic Wave Adsorption
Published: 2022, Journal of Materials Science & Technology
Link: Journal of Materials Science & Technology, 108:64-72

Hot Compression Bonding Behavior and Constitutive Model of Spray Deposited 2195 Al-Cu-Li Alloy
Published: 2023, Vacuum
Link: DOI: 10.1016/j.vacuum.2023.111896

A Comparative Study on Microstructural Characterization of Thick High Strength Low Alloy Steel Weld by Arc Welding and Laser Welding
Published: 2023, Materials
Link: Materials 2023, 16, 2212

Microstructure Characterization and Wear Performance of WC-10Co/Ti-6Al-4V Coating Fabricated via Electron Beam Cladding
Published: 2021, Surface and Coatings Technology
Link: DOI: 10.1016/j.surfcoat.2021.127493

Effect of Temperature and Hold Time of Induction Brazing on Microstructure and Shear Strength of Martensitic Stainless Steel Joints
Published: 2018, Materials
Link: DOI: 10.3390/ma1111586

Role of Reversed Austenite Behavior in Determining Microstructure and Toughness of Advanced Medium Mn Steel by Welding Thermal Cycle
Published: 2018, Materials
Link: DOI: 10.3390/ma112127

Metallurgical and Mechanical Properties of Fibrous Laser Welded Thick Q890 High Strength Low Alloy Steel with Varying Weld Geometries
Published: 2022, Journal of Materials Engineering and Performance
Link: DOI: 10.1007/s11665-021-06516-3

Ms. Zhengrong Xiang | Control Science | Young Scientist Award

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Ms. Zhengrong Xiang | Control Science | Young Scientist Award

Teaching assistant, School of Physics and Information Engineering, Guangxi Science and Technology Normal University, China

Xiang Zhengrong is a dedicated researcher and educator in Control Science and Engineering with expertise in Unmanned Aerial Vehicle (UAV) Systems 🚀. She holds a Master of Engineering degree and currently serves as a full-time teacher at the School of Physics and Information Engineering, Guangxi Science and Technology Normal University 🏫. With a strong background in control theory, automation, and UAV research, she actively contributes to cutting-edge technological advancements. As a member of the Guangxi Automation Society, she is committed to fostering innovation in aerospace control systems and automation technologies.

Publication Profile

🎓 Education

Xiang Zhengrong has a strong academic foundation in engineering and automation. She earned her Master’s degree in Control Science and Engineering 🎓 from Guangxi University of Science and Technology (2019-2022). Before that, she completed her Bachelor’s degree in Electrical Engineering and Automation ⚡ from Chongqing Three Gorges University (2017-2019). Her early technical education began at Chongqing Vocational and Technical College of Industry and Trade (2014-2017), where she specialized in Refrigeration and Air-conditioning Technology ❄️.

💼 Experience

Since July 2022, Xiang Zhengrong has been a full-time faculty member at Guangxi Science and Technology Normal University 📚. She has also served as a visiting teacher at the School of Automation, Guangxi University of Science and Technology 🏛️. With a keen interest in automation and UAV simulation, she has worked on multiple research projects related to UAV flight control, semi-physical simulation systems, and industrial automation technologies 🔬.

🏆 Awards and Honors

Xiang Zhengrong has actively contributed to research and academia, earning recognition for her work. She has secured funding for multiple research projects, including collaborations with Shenzhen Silop Technology Co., Ltd., and has received research grants from the Guangxi Education Science “14th Five-Year Plan” 📜. Her contributions to UAV technology and automation research have been widely recognized within academic and industrial communities 🏅.

🔬 Research Focus

Her primary research interests revolve around Unmanned Aerial Vehicle (UAV) Systems, Control Theory, and Automation ✈️. She specializes in semi-physical simulation systems, flight controller development, and innovative training models for engineering students 🎯. She has also participated in key projects related to electromagnetic interference technologies, capacitive touchscreens, and AI-driven microgrid control systems ⚙️.

🔖 Conclusion

With a passion for engineering and innovation, Xiang Zhengrong continues to push the boundaries of UAV system research and automation 🚀. As a dedicated educator and researcher, she actively contributes to cutting-edge technological advancements and interdisciplinary collaborations. Her scientific publications in reputed journals and research project involvements highlight her commitment to excellence in automation and aerospace control systems 🌍.

📚 Publications

New Generalization and Refinement of the Local Fractional Integral Cauchy–Schwartz Inequality on Fractal Space – Thermal Science, 2025 (In press, SCI Journal)

Hölder Type Inequality for Conformable Fractional Integral and Some Related Results – Thermal Science, 2025 (In press, SCI Journal) 🔗

An improved UWB indoor positioning approach for UAVs based on the dual-anchor model – Sensors, 2025 (In press, SCI Journal) 🔗

Design of DC motor position tracking system based on LQR – Journal of Physics: Conference Series, 2021 🔗

Time Series Generation Adversarial Network Controller Based on Optimal Control of Micro-Grids – 2nd International Conference on Futuristic Technologies (INCOFT), 2023 🔗 [DOI: 10.1109/INCOFT60753.2023.10425311]

Design of hardware-in-the-loop simulation system based on Pixhawk flight control – Journal of Physics: Conference Series, 2021 🔗

Dr. Pengtao Song | Control Science | Best Researcher Award

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Dr. Pengtao Song | Control Science | Best Researcher Award

Student, Xi’an Jiaotong University, China

Pengtao Song is a dedicated Ph.D. student at Xi’an Jiaotong University, China, specializing in Control Science and Engineering. With a strong foundation in automation from Northeastern University, he has been actively involved in groundbreaking research in cyber-physical systems, networked control, and intelligent control of industrial processes. His expertise extends to the diagnosis and control of mechatronic systems, with a focus on improving the robustness and efficiency of complex engineering networks. As a member of the Chinese Association of Automation (CAA), Pengtao continues to contribute significantly to the field of control engineering.

Publication Profile

🎓 Education

Pengtao Song earned his B.S. degree in Automation from Northeastern University, Qinhuangdao, China, in 2020. Currently, he is pursuing his Ph.D. in the Faculty of Electronics and Information Engineering at Xi’an Jiaotong University, where he focuses on cyber-physical systems and networked control.

💼 Experience

Pengtao has been actively engaged in advanced research projects, including the prestigious National Science and Technology Major Project of China. His collaboration with the Logistics Science and Innovation Integration Development Research Center at Xi’an Jiaotong University has further enriched his experience in applied research and industrial innovation. His work has been recognized in high-impact journals such as Aerospace Science and Technology, IEEE Transactions on Automation Science and Engineering, and Nonlinear Dynamics, demonstrating his expertise in system modeling and intelligent control.

🏆 Awards and Honors

Pengtao Song’s outstanding contributions to control engineering have earned him recognition in the academic community. His publications in SCI and Scopus-indexed journals have made a significant impact, contributing to the advancement of cyber-physical systems. His research excellence has positioned him as a strong candidate for the Best Researcher Award in the field of Computer Science.

🔍 Research Focus

Pengtao’s research is centered on ensuring the efficient scheduling and robust operation of aero-engine networked systems. His work addresses challenges such as model perturbation, external disturbances, and communication delays, offering innovative control strategies like sliding mode control (SMC), H∞ control, fuzzy control, and data-driven control. His findings enhance the response performance of complex engineering systems, making significant contributions to the field of control and automation.

🚀Conclusion

Pengtao Song is an emerging leader in the field of control science and automation, contributing cutting-edge solutions to complex engineering challenges. His research in robust control strategies for networked systems has been widely recognized in top-tier journals, making a significant impact in the domain. As he continues his Ph.D. journey, his work promises to drive advancements in intelligent control, cyber-physical systems, and industrial automation.

📚 Publications

Pengtao Song has published extensively in leading journals and conferences, contributing valuable insights into control science and automation. Some of his notable works include:

Disturbance-Compensation-Based Predictive Sliding Mode Control for Aero-Engine Networked Systems With Multiple Uncertainties – IEEE Transactions on Automation Science and Engineering (2025)
DOI: 10.1109/TASE.2024.3350020

Charge or Pick Up? Optimizing E-Taxi Management: A Dual-Stage Heuristic Coordinated Reinforcement Learning Approach – IEEE Transactions on Automation Science and Engineering (2024)
DOI: 10.1109/TASE.2024.3486342

Model-free event-triggered resilient control for discrete-time nonlinear systems under sparse actuator attacks via GrHDP – Nonlinear Dynamics (2024)
DOI: 10.1007/s11071-024-10477-2

Observer-based H∞ Sliding Mode Control for Networked Systems with Stochastic Communication Protocol and Packet Loss– 14th Asian Control Conference (ASCC 2024)
EID: 2-s2.0-85205697035

TAMTL: A Novel Meta-Transfer Learning Approach for Fault Diagnosis of Rotating Machinery – 14th Asian Control Conference (ASCC 2024)
EID: 2-s2.0-85205678502

Fuzzy H∞ robust control for T-S aero-engine systems with network-induced factors under round-robin-like protocol – Aerospace Science and Technology (2023)
DOI: 10.1016/j.ast.2023.108258

Observer-based output feedback control for networked systems with dual-channel event-triggered sampling and quantization – Journal of the Franklin Institute (2022)
DOI: 10.1016/j.jfranklin.2022.07.042

Assist. Prof. Dr. Jianhui Wu | System Control | Best Researcher Award

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Assist. Prof. Dr. Jianhui Wu | System Control | Best Researcher Award

Associate Professor, Hunan Institute of Science and Technology, China

Dr. Jianhui Wu is an accomplished Associate Professor at the Hunan Institute of Science and Technology, China. With a strong background in system control, optimization, and visual navigation, he has made significant contributions to the field of autonomous systems. His research focuses on advanced control technologies, particularly in multi-agent systems and obstacle avoidance. As an IEEE member, Dr. Wu actively collaborates with the scientific community, publishing impactful studies in high-ranking journals. His work is widely cited, showcasing his influence in the academic and industrial sectors.

Publication Profile

🎓 Education

Dr. Wu earned his Ph.D. from Changsha University of Science and Technology, China, in 2019. His doctoral research laid the foundation for his expertise in system control, signal processing, and visual navigation. His academic journey has been marked by a deep commitment to solving complex problems in autonomous systems and optimization.

💼 Experience

Currently serving as an Associate Professor, Dr. Wu is affiliated with the School of Information and Communication at Guilin University of Electronic Technology. Over the years, he has led several research projects funded by the Zhuang Autonomous Region, working on cutting-edge control mechanisms for autonomous multi-agent systems. His contributions span both theoretical advancements and practical applications in the fields of artificial intelligence, automation, and transportation optimization.

🏆 Awards and Honors

Dr. Wu’s work has been widely recognized, with multiple grants supporting his research in intelligent systems and control optimization. His research output has earned high citations in SCI-indexed journals, further cementing his reputation as a leading researcher in his domain.

🔬 Research Focus

Dr. Wu’s research primarily revolves around system control and optimization, visual navigation, and signal processing. His groundbreaking studies on multi-agent autonomous systems explore innovative flocking control mechanisms that enhance obstacle avoidance, navigation, and collaborative behaviors. His research has contributed to designing efficient, self-organizing, and adaptive autonomous systems, essential for advancements in robotics and artificial intelligence.

📌 Conclusion

Dr. Jianhui Wu is a dedicated researcher whose contributions to system control and multi-agent coordination continue to shape the future of automation and intelligent transportation. With numerous publications in top-tier journals and significant industry collaborations, his work is paving the way for smarter, more autonomous systems.

📚 Publications 

Fuzzy Flocking Control for Multi-Agents Trapped in Dynamic Equilibrium Under Multiple Obstacles – International Journal of Control, Automation and Systems, 2024 (DOI: 10.1007/s12555-022-0950-6)

Virtual-Leader Split/Rejoin-Based Flocking Control With Obstacle Avoidance for Multi-Agents – International Journal of Control, Automation and Systems, 2024 (DOI: 10.1007/s12555-022-0950-6)

Anonymous Flocking With Obstacle Avoidance via the Position of Obstacle Boundary Point – IEEE Internet of Things Journal, 2024 (DOI: 10.1109/jiot.2024.3465881)

Obstacle Boundary Point and Expected Velocity-Based Flocking of Multiagents with Obstacle Avoidance – International Journal of Intelligent Systems, 2023 (DOI: 10.1155/2023/1493299)

Optimization Scheme of Fine Toll and Bus Departure Quantity for Bottleneck Congestion Management – Complexity, 2021 (DOI: 10.1155/2021/5518502)

Optimization Scheme of Tradable Credits and Bus Departure Quantity for Travelers’ Travel Mode Choice Guidance – Journal of Advanced Transportation, 2020 (DOI: 10.1155/2020/6665161)

Price Regulation Mechanism of Travelers’ Travel Mode Choice in the Driverless Transportation Network – Journal of Advanced Transportation, 2020 (DOI: 10.1155/2020/9191834)

Guidance Optimization of Travelers’ Travel Mode Choice Based on Fuel Tax Rate and Bus Departure Quantity in Two-Mode Transportation System – Journal of Advanced Transportation, 2020 (DOI: 10.1155/2020/4190632)

A Day-to-Day Stochastic Traffic Flow Assignment Model Based on Mixed Regulation – IEEE Access, 2020 (DOI: 10.1109/access.2019.2962864)

Robust Optimization of Sequence Decision in Urban Road Construction – Computer Science, 2018

 

 

IDRISS DAGAL | Electrical Engineering | Best Researcher Award

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Dr. IDRISS DAGAL | Electrical Engineering | Best Researcher Award

Assistant Professor, Istanbul Beykent University, Turkey

Dr. Idriss Dagal, an Assistant Professor at Istanbul Beykent University, is a researcher and engineer from Chad specializing in Electrical Engineering, Renewable Energy, and Artificial Intelligence. With a career spanning over a decade, he has worked in various roles, including Aircraft Engineer and Lecturer, and has contributed extensively to the field of electrical systems, power electronics, and optimization algorithms. His academic journey includes a Ph.D. from Yıldız Technical University, Istanbul, Turkey, where he also completed his MSc in Avionics Engineering. Dr. Dagal has authored over 30 publications and is an active reviewer for renowned journals. 🌍💡

Publication Profile

ORCID

Education:

Dr. Dagal holds a Bachelor of Science (B.S.) degree in Industrial and Maintenance Engineering from Mongo Polytechnic University (Chad, 2006), a Master of Science (M.Sc.) in Aviation Engineering from Ethiopian Airlines Aviation School (Ethiopia, 2010), and a Ph.D. in Electrical Engineering from Yıldız Technical University (Turkey, 2022). He is currently pursuing a second M.Sc. in Avionics Engineering at Yıldız Technical University. 🎓📚

Experience:

Dr. Dagal’s professional experience spans multiple countries and roles, including serving as an Aircraft Maintenance Engineer in Chad, a Lecturer at various institutions in Chad, and a Sales Engineer in Turkey. Since 2024, he has been serving as an Assistant Professor at Istanbul Beykent University, Turkey, specializing in electrical engineering, renewable energy, and avionics. 🛠️✈️

Awards and Honors:

Dr. Dagal has received several prestigious awards, including the Chad’s Government National Scholarship (2003), Ethiopian Airlines Aviation School International Scholarship (2008), Turkish Government International Scholarship (2015), Young Research Scholarship Award for Eurasia Research (2019), and the Leadership Skills African Civic Engagement Academy (2022). 🏆🌟

Research Focus:

Dr. Dagal’s research interests are centered on optimization algorithms, artificial intelligence, renewable energy systems, power electronics, and aircraft control systems. His doctoral research focused on optimizing photovoltaic battery charging systems using hybrid particle swarm-based algorithms. He has a strong background in developing control mechanisms for sustainable energy systems and dynamic systems in aviation. 🔋🔧🚀

Conclusion:

Dr. Idriss Dagal is an accomplished academic and researcher who combines his expertise in electrical and aerospace engineering with a deep commitment to renewable energy and technology optimization. His interdisciplinary work continues to contribute to advancements in energy systems, aircraft control, and smart technologies. 🌱💻

Publications 

Energy transfer from PV panel to Battery via Buck-Boost Converter, International Journal of Technology and Science, Vol. 5, Issue 3, pp. 46-60, 26 November 2019. DOI

Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems, International Journal of Energy Research, 2022; 1-18. DOI: 10.1002/er.7753. Impact Factor: 4.3, Q1.

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization (PSOSSO) algorithm for battery charging through Simulink, Scientific Reports Journal, 2022; 12:2664. DOI. Impact Factor: 3.8, Q1.

A Novel Hybrid Series Salp Particle Swarm Optimization (SSPSO) for Standalone Battery Charging Applications, Ain Shams Engineering Journal, 2022; 13:10174. DOI. Impact Factor: 6, Q1.

Improved Particle Swarm Optimization based Buck-Boost converter (IPSOBBC) for Photovoltaic System Application, Recent Advances in Science & Engineering (RASE), 2022.

Transformer rail-tapped buck-boost converter design-based feedback controller for battery charging systems, Energy Storage Journal, 2022; e414, DOI. ESCI.

Secure and Optimized Satellite Image Sharing based on Chaotic eπ Map and Racah Moments” Expert Systems with Applications, Volume 236, February 2024, 121247, DOI: 10.1016/j.eswa.2023.121247. Impact Factor: 7.5, Q1.

Hybrid SSA-PSO-based intelligent direct sliding-mode control for extracting maximum photovoltaic output power and regulating the DC-bus voltage, International Journal of Hydrogen Energy, Volume 51, Part C, 2 January 2024, Pages 348-370, DOI. Impact Factor: 8.1, Q1.

An Improved Constant Current Step-based Grey Wolf Optimization Algorithm for Photovoltaic Systems, Journal of Intelligent & Fuzzy Systems, 2024, DOI. Impact Factor: 1.7, Q3.

A Modified Multi-Stepped Constant Current Based on Grey Wolf Algorithm for Photovoltaics Applications, Springer, Electrical Engineering, 2024, DOI. Impact Factor: 1.6, Q3.