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

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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.

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