Pengwen Xiong | Robotics | Best Researcher Award

Published on by Best Achievements

Prof. Dr. Pengwen Xiong | Robotic Sensing and Control | Best Researcher Award

Prof. Dr. Pengwen Xiong | Nanchang University | China

Prof. Dr. Pengwen Xiong is a Professor and Doctoral Supervisor at Nanchang University, serving as Director of the Jiangxi Provincial Key Laboratory of Intelligent Robotics and Vice Dean of the School of Advanced Manufacturing. He has published over 100 academic papers, applied for 32 national invention patents (20 authorized), and led multiple national and provincial research projects. His expertise spans robotic sensing and control, artificial intelligence, and intelligent instruments, and he has received prestigious awards including the Jiangxi Provincial Science and Technology Progress Award.

Profiles

Orcid
Google Scholar

Early Academic Pursuits

Prof. Dr. Pengwen Xiong began his academic journey with a strong focus on robotics, artificial intelligence, and intelligent systems, completing advanced studies and postdoctoral research that laid the foundation for his career. His early dedication to innovative research and rigorous scientific methodology established him as a rising expert in robotic sensing, AI, and intelligent instruments, enabling him to contribute significantly to both theoretical frameworks and applied robotics technologies.

Professional Endeavors

Dr. Xiong currently serves as Director of the Jiangxi Provincial Key Laboratory of Intelligent Robotics and Vice Dean of the School of Advanced Manufacturing at Nanchang University. He is also an IEEE Senior Member and actively contributes to professional societies including the Chinese Society of Automation, China Computer Federation, and the Chinese Association for Artificial Intelligence. Over his career, he has presided over multiple high-profile projects, including the National Key R&D Program’s “Intelligent Robot” sub-project, four National Natural Science Foundation projects, and numerous provincial and ministerial projects.

Contributions and Research Focus

Prof. Xiong’s primary contribution is the development of the Dictionary-Reconstruction-based Deep Learning (DRDL) method for texture recognition, which preserves critical low-level features often lost in deep learning models. By integrating multi-level feature fusion with early multimodal data combination, his DRDL approach achieves state-of-the-art accuracy, significantly impacting industrial applications where robust and precise recognition is critical. His work focuses on robotic sensing, AI, and intelligent instrumentation, driving both academic advancements and technological innovation.

Impact and Influence

Dr. Xiong’s research has been widely cited, with over 1,100 citations, an H-index of 19, and i10-index of 27 on Google Scholar. His innovations have influenced both academic peers and industry applications, particularly in enhancing intelligent robotic systems’ accuracy and reliability. His work bridges the gap between cutting-edge AI theory and practical implementation, making him a leading figure in robotics and AI research in China and internationally.

Research Skills

Prof. Xiong possesses expertise in robotic sensing and control, artificial intelligence, and intelligent instruments, alongside strong capabilities in deep learning model design, multimodal data integration, and industrial robotics applications. His skill set extends to project leadership, scientific writing, and editorial contributions, demonstrated through over 100 academic publications and leadership roles in prestigious journals.

Awards and Honors

Dr. Xiong has been recognized with prestigious accolades including the First Prize of the Jiangxi Provincial Science and Technology Progress Award and the Second Prize of the Wu Wenjun Artificial Intelligence Science and Technology Progress Award. He has also been granted 20 national invention patents out of 32 applications and holds editorial positions such as Associate Editor for the International Journal of Robotics and Automation and Special Issue Associate Editor for IEEE Transactions on Cognitive and Developmental Systems.

Legacy and Future Contributions

Prof. Xiong continues to advance intelligent robotics and AI research, shaping the next generation of robotics technologies and intelligent manufacturing systems. His legacy lies in bridging theoretical AI research with real-world industrial applications, mentoring young researchers, and driving innovation that will influence robotics, AI, and intelligent instrumentation for years to come.

Publications Top Notes

Dynamic sign language recognition based on video sequence with BLSTM-3D residual networks

Authors: Y Liao, P Xiong, W Min, W Min, J Lu

Journal: IEEE Access

Year: 2019

Citations: 189

Ship trajectory reconstruction from AIS sensory data via data quality control and prediction

Authors: X Chen, J Ling, Y Yang, H Zheng, P Xiong, O Postolache, Y Xiong

Journal: Mathematical Problems in Engineering

Year: 2020

Citations: 64

Visual-haptic aid teleoperation based on 3-D environment modeling and updating

Authors: X Xu, A Song, D Ni, H Li, P Xiong, C Zhu

Journal: IEEE Transactions on Industrial Electronics

Year: 2016

Citations: 54

Detecting dynamic behavior of brain fatigue through 3-D-CNN-LSTM

Authors: EQ Wu, P Xiong, ZR Tang, GJ Li, A Song, LM Zhu

Journal: IEEE Transactions on Systems, Man, and Cybernetics: Systems

Year: 2021

Citations: 52

AGV-based vehicle transportation in automated container terminals: A survey

Authors: PZH Sun, J You, S Qiu, EQ Wu, P Xiong, A Song, H Zhang, T Lu

Journal: IEEE Transactions on Intelligent Transportation Systems

Year: 2022

Citations: 46

Mining ship deficiency correlations from historical port state control (PSC) inspection data

Authors: J Fu, X Chen, S Wu, C Shi, H Wu, J Zhao, P Xiong

Journal: PLoS One

Year: 2020

Citations: 39

Design of an accurate end-of-arm force display system based on wearable arm gesture sensors and EMG sensors

Authors: P Xiong, C Wu, H Zhou, A Song, L Hu, XP Liu

Journal: Information Fusion

Year: 2018

Citations: 39

ROpenPose: a rapider OpenPose model for astronaut operation attitude detection

Authors: EQ Wu, ZR Tang, P Xiong, CF Wei, A Song, LM Zhu

Journal: IEEE Transactions on Industrial Electronics

Year: 2021

Citations: 37

Brain-computer interface using brain power map and cognition detection network during flight

Authors: EQ Wu, Z Cao, P Xiong, A Song, LM Zhu, M Yu

Journal: IEEE/ASME Transactions on Mechatronics

Year: 2022

Citations: 35

Development of a multidirectional controlled small-scale spherical MR actuator for haptic applications

Authors: D Chen, A Song, L Tian, Q Ouyang, P Xiong

Journal: IEEE/ASME Transactions on Mechatronics

Year: 2019

Citations: 35

Conclusion

Prof. Dr. Pengwen Xiong is a leading researcher in robotics and artificial intelligence, with over 100 publications, 32 patent applications (20 authorized), and significant contributions such as the Dictionary-Reconstruction-based Deep Learning (DRDL) method. His innovative research, project leadership, and editorial roles demonstrate exceptional scientific excellence and practical impact. With strong professional memberships and awards, he is highly deserving of the Best Researcher Award, reflecting both global influence and advancement of intelligent robotics and AI technologies.

Jing-Li Fu | Robotics | Best Research Article Award

Published on by Best Achievements

Prof. Dr. Jing-Li Fu | Robotics | Best Research Article Award

Prof. Dr. Jing-Li Fu | Shandong Vocational University of Foreign Affairs, Zhejiang Sdi-Tech University |  China 

Prof. Dr. Fu Jingli is a distinguished scholar in mathematics and applied mechanics, currently serving as a second-level professor and doctoral supervisor at Zhejiang University of Technology. With a prolific academic career, he has authored over 150 research papers, with more than 100 indexed by SCI and over 70 by EI. His work has been cited over 1,000 times in SCI journals. He is known for advancing the theory of symmetries in dynamical systems. His contributions span theoretical innovation and practical applications, establishing him as a prominent figure in China’s scientific and educational landscape.

Profile

Scopus
Orcid 

Education

Prof. Dr. Fu Jingli earned his Ph.D. in a technical field and currently serves as a second-level professor and doctoral supervisor at Zhejiang University of Technology. His academic journey has been marked by rigorous scientific training and specialization in mechanics and dynamical systems. With deep expertise developed through advanced research and mentoring, he has cultivated a strong academic foundation. His education laid the groundwork for hosting several national-level projects and producing highly cited publications. Prof. Fu’s scholarly background reflects a commitment to excellence, both in teaching and research, and has significantly shaped his contributions to science and engineering.

Prof. Dr. Fu Jingli is a senior academic with extensive experience in research, teaching, and supervision. As a second-level professor at Zhejiang University of Technology, he has led five projects funded by the National Natural Science Foundation of China. With a strong research record and mentoring history, he has guided numerous postgraduate and doctoral students. He contributed to both theoretical research and curriculum innovation. His experience also includes collaboration with national educational and scientific bodies, significantly advancing the field of dynamical systems and mathematical modeling. His expertise is reflected in national and provincial awards and a substantial publication record.

Research Focus

Prof. Fu Jingli’s research focuses on Noether symmetries, conserved quantities in nonconservative dynamical systems, and geometric mechanics. His influential 2003 paper in Physics Letters A, co-authored with Li-Qun Chen, has been cited over 50 times, showcasing its impact in theoretical physics. He explores differential equations, variational principles, and symmetry-based analytical mechanics. His work aids in understanding physical systems lacking traditional conservation laws. Through mathematical modeling and theoretical analysis, his contributions bridge pure mathematics with applied science, supporting advances in physics, engineering, and control systems. His research significantly shapes developments in symmetry methods and integrability in modern dynamics.

Awards and Honors

Prof. Fu Jingli has received multiple prestigious honors for his contributions to science and education. He earned a second prize (first place) in the Zhejiang Provincial Science and Technology Award and a second prize in the Natural Science Award from the Ministry of Education (second place). He also received a second prize in the Shanghai Science and Technology Progress Award (second place). In the field of education, he won a first prize in provincial teaching achievements (first place). These accolades reflect his dual excellence in research and pedagogy, marking him as a key contributor to China’s scientific and academic progress.

 Publications Top Notes

Title: Basic Principles of Deformed Objects with Methods of Analytical Mechanics
Journal: Journal of Nonlinear Mathematical Physics
Year: 2024
Citations: 1
Authors: Fu Jingli, others not specified

Title: Lie Symmetries and Conserved Quantities of Static Bertotti–Robinson Spacetime
Journal: Chinese Journal of Physics
Year: 2024
Citations: 2
Authors: Fu Jingli, others not specified

Title: Dynamics Analysis of a Nonlinear Controlled Predator–Prey Model with Complex Poincaré Map
Journal: Nonlinear Analysis: Modelling and Control
Year: 2024
Citations: 1
Authors: Fu Jingli, others not specified

Title: Fractional Hamilton’s Canonical Equations and Poisson Theorem of Mechanical Systems with Fractional Factor
Journal: Mathematics
Year: 2023
Citations: 1
Authors: Fu Jingli, others not specified

Title: Dynamic Analysis of a Phytoplankton-Fish Model with the Impulsive Feedback Control Depending on the Fish Density and Its Changing Rate
Journal: Mathematical Biosciences and Engineering
Year: 2023
Citations: 2
Authors: Fu Jingli, others not specified

Title: Lie Group Analysis Method for Wall Climbing Robot Systems
Journal: Indian Journal of Physics
Year: 2022
Citations: 4
Authors: Fu Jingli, others not specified

Title: Noether Symmetries and Conserved Quantities of Wall Climbing Robot System
Journal: Lixue Xuebao (Chinese Journal of Theoretical and Applied Mechanics)
Year: 2022
Citations: 6
Authors: Fu Jingli, others not specified

Title: A Symplectic Algorithm for Constrained Hamiltonian Systems
Journal: Axioms
Year: 2022
Citations: 4
Authors: Fu Jingli, others not specified

Title: Sensitivity Analysis of Pesticide Dose on Predator-Prey System with a Prey Refuge
Journal: Journal of Applied Analysis and Computation
Year: 2022
Citations: 4
Authors: Fu Jingli, others not specified

Title: On Noether Symmetries and Conserved Quantities of Nonconservative Dynamical Systems
Journal: Physics Letters A
Year: 2003
Citations: 50+
Authors: Jing-Li Fu, Li-Qun Chen

Conclusion

Prof. Dr. Fu Jingli exemplifies academic excellence through his profound research, impactful teaching, and national-level recognition. With over 150 publications and significant citations, his theoretical advancements in dynamical systems have influenced both academia and practical applications. His awards and leadership in major national research projects further reinforce his stature as a scholar of distinction. Through his role as a doctoral supervisor and educator, he continues to nurture the next generation of researchers. His sustained contributions to mathematics and engineering position him as a deserving candidate for honors like the Best Researcher Award.

Muhammad Taha Tariq | Robotics | Best Researcher Award

Published on by Best Achievements

Mr. Muhammad Taha Tariq | Robotics | Best Researcher Award

Mr. Muhammad Taha Tariq, Nanjing University of Aeronautics and Astronautics, China.

Muhammad Taha Tariq 🎓 is a dedicated researcher in Control Science and Engineering from Nanjing University of Aeronautics and Astronautics. His focus lies in 🤖 mobile robot path planning, using 🧠 Deep Reinforcement Learning and 🗺️ Large Language Models for dynamic navigation. With nationally funded projects and publications in top-tier venues, he brings innovation, precision, and AI-driven impact to the field. He is an active member of IEEE and ASME, continually pushing the boundaries of robotic intelligence.

🌟 Professional Profile

🎓 Early Academic Pursuits

Muhammad Taha Tariq began his academic journey with a strong inclination towards automation and artificial intelligence. He pursued a Master’s degree in Control Science and Engineering at Nanjing University of Aeronautics and Astronautics, where he built a robust foundation in machine learning, deep learning, and robotics. His early academic exposure shaped his research orientation toward practical innovation in intelligent systems, especially mobile robots and their navigation capabilities.

💼 Professional Endeavors

As a student researcher, Taha has embarked on ambitious projects combining theoretical excellence with practical implementations. He is affiliated with leading research programs and has actively contributed to funded projects, focusing on Deep Reinforcement Learning and Large Language Models. Despite being at an early stage of his career, his engagement with prestigious funding programs in China highlights his dedication and potential in academic research.

🔬 Contributions and Research Focus On Robotics 

Taha’s research specializes in mobile robot path planning, emphasizing dynamic environments and obstacle avoidance. His 2023–2024 project introduced a Deep Reinforcement Learning-based framework to calculate collision probabilities in real-time. In 2024–2025, he developed an innovative system that integrates LLMs for dynamic waypoint generation, achieving a 95.5% success rate and average task completion in 9.43 seconds. These contributions are both nationally funded and recognized through publications and technical demonstrations.

🌍 Impact and Influence

Though early in his career, Taha’s work reflects a deep commitment to open science. He provides preprints on arXiv, demonstration videos on YouTube, and open-source code on GitHub, fostering transparency and reproducibility in AI research. His methods are not only academically sound but also scalable for real-world robotic applications, influencing future trends in intelligent automation systems.

🏆 Awards and Honors

Taha has been nominated for the Best Researcher Award, a testament to his innovative work in automation and robotics. His selection is supported by successful national grants and active contributions to IEEE and ASME student communities.

📚 Academic Citations

As of now, Muhammad Taha Tariq does not report a citation index, but with publications accepted in journals like Expert Systems with Applications and conference presentations at the WRC Symposium, his research is gaining scholarly visibility and is poised to attract academic citations in the near future.

🚀 Legacy and Future Contributions

Muhammad Taha Tariq’s journey reflects a promising trajectory toward becoming a leading AI researcher. His legacy will likely include scalable frameworks for autonomous navigation and AI integration. Moving forward, he envisions enhancing robot-environment interaction using cutting-edge language models, contributing to safer and more efficient robotics applications in industries and smart cities.

📚Publications Top Notes

📄 1. Deep Reinforcement Learning-Based Path Planning with Dynamic Collision Probability for Mobile Robots

Geng Yang | Robot Sensing | Best Researcher Award

Published on by Best Achievements

Prof. Dr. Geng Yang | Robot Sensing | Best Researcher Award

Prof. Dr. Geng Yang, Zhejiang University, China.

Prof. Geng Yang is a distinguished researcher in robot sensing, human-robot interaction, and biomedical IoT. He is a Professor at the School of Mechanical Engineering, Zhejiang University, China, and previously held positions at Fudan University and the Royal Institute of Technology, Sweden. A recipient of China’s National Distinguished Young Talents Program, he serves as an Associate Editor for top IEEE journals. His pioneering work in human cyber-physical systems and flexible sensors has significantly advanced healthcare and industrial automation.

Professional Profile

🎓 Education

  • 2006—2013 🏅 Ph.D. in Electronic Systems, Royal Institute of Technology (KTH), Stockholm, Sweden
  • 2003—2006 🎓 M.Sc. in Instrument Science & Technology, Zhejiang University (ZJU), China
  • 1999—2003 📖 B.Sc. in Instrument Science & Technology, Zhejiang University (ZJU), China

🔬Research Contributions On Robot Sensing

Prof. Geng Yang has made significant contributions to robot sensing, human-robot interaction, and biomedical IoT, advancing safer and more efficient healthcare and industrial automation systems. His research on multimodal robot skin technology enhances tactile perception for human-cyber-physical systems. He has pioneered flexible circuits and biomedical micro-systems, integrating heterogeneous technologies for healthcare applications. His extensive publications, editorial roles, and leadership in IEEE and ACM conferences further solidify his impact in next-generation robotics, smart sensing, and assistive healthcare technologies.

💼 Work Experience

Prof. Geng Yang has an extensive academic and research career in mechanical engineering and biomedical systems. Since 2016, he has been a Professor at Zhejiang University, contributing to advancements in human-robot interaction and healthcare IoT. He previously served as an Associate Professor at Fudan University (2015–2016) and a Postdoctoral Researcher at the Royal Institute of Technology (KTH), Sweden (2013–2015). His expertise spans robot sensing, flexible circuits, and biomedical micro-systems, making significant contributions to academia and industry.

🏆 Editorial & Academic Contributions

  • Associate Editor:
    • IEEE Review in Biomedical Engineering (IEEE RBME)
    • Chinese Journal of Mechanical Engineering (CJME)
    • IEEE Journal of Biomedical and Health Informatics (IEEE JBHI)
    • Bio-Design and Manufacturing (Springer BDM)
  • Technical Committees: IEEE Industrial Electronics Society (IES)

🎤 Invited Talks & Tutorials (Recent)

  • Robot Tactile Perception for Safer Human-Robot Interaction – MDBS-BHE’ 2024, China 🇨🇳
  • Bionic Skin & Collaborative Robots in Healthcare 4.0 – Neural Engineering & Rehabilitation 2023, China
  • Multimodal Robot Skin for Safer Human-Robot Interaction – MDBS-CHE’ 2022, Hong Kong

Conclusion

Prof. Geng Yang’s exceptional contributions to robot sensing, human-robot interaction, and biomedical IoT establish him as a leader in research and innovation. His extensive publications, editorial roles, and global recognition underscore his impact. With a distinguished career and groundbreaking advancements, he is highly deserving of the Best Researcher Award for his remarkable achievements in science and technology.

📚Publication Top Notes

1️⃣ A health-IoT platform based on the integration of intelligent packaging, unobtrusive bio-sensor, and intelligent medicine box
📖 IEEE Transactions on Industrial Informatics (2014) – 865 citations 📊

2️⃣ Wearable Internet of Things: Concept, architectural components and promises for person-centered healthcare
📖 4th International Conference on Wireless Mobile Communication (2014) – 451 citations 🏥

3️⃣ An IoT-enabled stroke rehabilitation system based on smart wearable armband and machine learning
📖 IEEE Journal of Translational Engineering in Health and Medicine (2018) – 217 citations 🧠

4️⃣ IoT-based remote pain monitoring system: From device to cloud platform
📖 IEEE Journal of Biomedical and Health Informatics (2017) – 200 citations ☁️💉

5️⃣ Human Digital Twin in the context of Industry 5.0
📖 Robotics and Computer-Integrated Manufacturing (2024) – 197 citations 🤖

6️⃣ Homecare robotic systems for healthcare 4.0: Visions and enabling technologies
📖 IEEE Journal of Biomedical and Health Informatics (2020) – 197 citations 🏠🤖

7️⃣ Multifunctional flexible humidity sensor systems towards noncontact wearable electronics
📖 Nano-Micro Letters (2022) – 195 citations 🔬💧

8️⃣ Introduction to the special section: convergence of automation technology, biomedical engineering, and health informatics toward the healthcare 4.0
📖 IEEE Reviews in Biomedical Engineering (2018) – 185 citations 🏥🖥️

9️⃣ Stretchable graphene–hydrogel interfaces for wearable and implantable bioelectronics
📖 Nature Electronics (2024) – 153 citations 🧪🩺

🔟 Keep healthcare workers safe: application of teleoperated robot in isolation ward for COVID-19 prevention and control
📖 Chinese Journal of Mechanical Engineering (2020) – 153 citations 🦠🤖