Xingjia Li | Engineering | Best Researcher Award

Dr. Xingjia Li | Engineering | Best Researcher Award

Senior Engineer at Shanghai Liangxin Electrical Co. Ltd, China

Dr. Xingjia Li is a promising early-career researcher who earned his Ph.D. in Mechanical Engineering from Jiangsu University in 2023. He is currently a Postdoctoral Associate at the postdoctoral workstation of Shanghai Liangxin Electrical Co., Ltd. in Shanghai, China. His research focuses on robotics and electrical systems, with a particular emphasis on sensor data processing using machine learning techniques. Dr. Li is dedicated to advancing human-centered applications by enhancing the reliability, intelligence, and security of robotic systems in daily life. His interdisciplinary approach integrates mechanical engineering, electronics, and artificial intelligence, aligning with the evolving demands of modern technology. While still in the early stages of his research career, his industry collaboration and applied research focus position him as a strong candidate for future leadership in his field. Dr. Li’s work holds potential for significant contributions to smart systems and intelligent automation in real-world environments.

Professional Profile 

ORCID Profile

Education

Dr. Xingjia Li obtained his Ph.D. in Mechanical Engineering from Jiangsu University, Zhenjiang, China, in 2023. During his doctoral studies, he focused on the integration of robotics and intelligent systems, building a strong foundation in both theoretical and applied aspects of mechanical and electrical engineering. His education emphasized sensor systems, automation, and machine learning, which prepared him for interdisciplinary research and practical implementation in advanced robotics. Dr. Li demonstrated strong academic performance and research capabilities throughout his graduate studies, contributing to academic discussions and research forums. His educational background reflects a rigorous training in engineering principles, analytical thinking, and innovation, which has shaped his approach to problem-solving in complex systems. Through research projects, seminars, and collaboration with faculty, he developed a deep understanding of how mechanical systems can be enhanced through intelligent control and data-driven methods, laying the groundwork for his postdoctoral research and future contributions to intelligent automation.

Professional Experience

Following his Ph.D., Dr. Xingjia Li joined the postdoctoral workstation at Shanghai Liangxin Electrical Co., Ltd., a key player in the electrical technology industry. In this role, he has been actively involved in research and development, focusing on advanced robotics and intelligent systems. His work emphasizes real-world implementation of sensor-based machine learning techniques to enhance system performance, reliability, and human-machine interaction. At Liangxin, Dr. Li collaborates with both engineering teams and academic partners to design and improve intelligent robotic systems that can operate efficiently in complex environments. His professional experience bridges academia and industry, allowing him to apply theoretical models to practical challenges in automation and electrical systems. This hands-on engagement with cutting-edge technologies has not only expanded his technical skill set but also positioned him as a valuable contributor in the emerging fields of smart manufacturing and AI-powered industrial automation, where reliability and adaptive performance are critical.

Research Interest

Dr. Xingjia Li’s research interests lie at the intersection of robotics, electrical systems, and machine learning, with a strong focus on sensor data processing for human-centered applications. He is passionate about enhancing the intelligence, reliability, and safety of robotic systems operating in dynamic environments. His work aims to empower robots with the ability to interpret complex sensory inputs through machine learning algorithms, thereby enabling real-time decision-making and adaptive behavior. He is particularly interested in applications that improve quality of life, such as assistive robotics, industrial automation, and intelligent monitoring systems. By integrating advanced data analytics and control strategies, Dr. Li seeks to develop systems that can function autonomously with minimal human intervention while maintaining high levels of trust and safety. His interdisciplinary approach combines the strengths of mechanical design, signal processing, and artificial intelligence, positioning him to contribute meaningfully to the advancement of next-generation robotics and smart systems.

Award and Honor

As a rising researcher in the field of intelligent robotics, Dr. Xingjia Li is at the beginning of his professional recognition journey. While specific awards and honors have not been listed in the available information, his acceptance into a postdoctoral research position at Shanghai Liangxin Electrical Co., Ltd. itself signifies recognition of his academic potential and technical proficiency. The opportunity to work in a dedicated industrial research environment reflects a high level of trust in his expertise and capability to contribute to meaningful innovation. His early involvement in cutting-edge projects and interdisciplinary work also positions him as a strong candidate for future academic and industrial awards. As he continues to publish research, develop prototypes, and contribute to real-world solutions, it is expected that Dr. Li will accumulate professional honors that recognize his growing impact in the fields of robotics, electrical systems, and intelligent automation technologies.

Conclusion

Dr. Xingjia Li is an emerging researcher whose interdisciplinary expertise bridges mechanical engineering, robotics, and artificial intelligence. With a strong educational foundation from Jiangsu University and practical postdoctoral experience at Shanghai Liangxin Electrical Co., Ltd., he is well-positioned to make significant contributions to the field of intelligent systems. His research aims to improve human-robot interaction and automation reliability through advanced sensor data processing and machine learning techniques. Though still in the early stages of his career, Dr. Li’s work shows great promise for practical impact in industry and society. His commitment to innovation, real-world application, and cross-disciplinary collaboration sets the stage for a distinguished research trajectory. With continued focus, publication, and recognition, Dr. Li has the potential to emerge as a thought leader in the development of smart, adaptive, and secure robotic systems that support both industrial and human-centered needs.

Publications Top Notes

Xiaoxu Liu | Engineering | Best Researcher Award

Dr. Xiaoxu Liu | Engineering | Best Researcher Award

Associate Professor at Shenzhen Technology University, China

Dr. Xiaoxu Liu is an accomplished Associate Professor at the Sino-German College of Intelligent Manufacturing, Shenzhen Technology University. He holds a Ph.D. in Electrical Engineering from the University of Northumbria and specializes in robust fault diagnosis, fault-tolerant control, stochastic systems, and multi-agent systems. Dr. Liu has published extensively in top-tier journals such as IEEE Transactions on Industrial Electronics and Automatica, and has served as Associate Editor for IEEE Transactions on Industrial Informatics. He has led multiple nationally funded research projects, securing over 3 million RMB in grants. His work integrates control theory with data-driven methods, addressing challenges in cyber-physical systems. Recognized as a Shenzhen Overseas High-level Talent, he has received numerous awards for research excellence and student mentorship. With international research experience and significant editorial contributions, Dr. Liu is a prominent figure in intelligent systems and control, demonstrating both academic leadership and impactful research contributions.

Professional Profile 

Scopus Profile

Education

Dr. Xiaoxu Liu possesses a strong and progressive academic background in engineering and applied mathematics. He earned his Ph.D. in Electrical Engineering from the University of Northumbria in the UK (2014–2018), where he specialized in fault-tolerant control systems and robust estimation. Prior to this, he completed a Master’s degree in Operations Research and Cybernetics at Northeastern University (2012–2014), and a Bachelor’s degree in Information and Computing Science at the same university (2008–2012). His educational path reflects a solid foundation in both theoretical and applied aspects of control systems, cybernetics, and intelligent systems. This combination of mathematical rigor and engineering application has laid the groundwork for his interdisciplinary research approach. His international academic journey has also helped him build a global perspective and a collaborative mindset, both of which have been instrumental in his subsequent professional and research achievements.

Professional Experience

Dr. Xiaoxu Liu has built an impressive academic and research career marked by rapid progression and leadership. Since December 2021, he has served as an Associate Professor at the Sino-German College of Intelligent Manufacturing, Shenzhen Technology University. Before that, he was an Assistant Professor at the same institution from 2018 to 2021. He also held research and teaching positions internationally, including as a Research Associate at the Faculty of Mathematics, City University of Hong Kong, and as a Lecturer at the University of Northumbria. Throughout these roles, Dr. Liu has led cutting-edge research projects, mentored students, and contributed to institutional development. He has acted as the principal investigator for numerous funded research programs, reflecting his capacity to lead independently and strategically. His experience demonstrates not only academic proficiency but also a sustained commitment to advancing intelligent systems research and fostering interdisciplinary collaboration in both teaching and applied engineering contexts.

Research Interest

Dr. Xiaoxu Liu’s research spans several high-impact areas within intelligent systems and control engineering. His primary interests include robust fault diagnosis, fault-tolerant control, stochastic nonlinear systems, and multi-agent systems. He also ocuses on cyber-physical systems and data-driven control, areas highly relevant to Industry 4.0 and autonomous system applications. Dr. Liu’s work often combines theoretical rigor with practical relevance, leveraging modern tools like deep reinforcement learning and Takagi-Sugeno fuzzy models to address real-world challenges such as actuator faults in UAVs or wind turbine resilience. His interdisciplinary approach blends classical control theory with artificial intelligence, enhancing system adaptability and reliability. His research outputs—published in top-tier journals like IEEE Transactions on Industrial Electronics—demonstrate not only novelty but also applicability to emerging technologies. Dr. Liu’s ability to connect robust theory with practical implementations positions him as a thought leader in intelligent manufacturing and autonomous system control.

ward and Honor

Dr. Xiaoxu Liu has received multiple awards that recognize his research excellence, academic leadership, and contributions to engineering education. He was honored as a Shenzhen Overseas High-level Talent in 2019, highlighting his strategic value to China’s academic and technological development. He has earned several Best Paper and Best Presentation Awards from prestigious conferences and journals, such as the IEEE Industrial Electronics Society and Processes. Dr. Liu also received the IEEE IES Student Paper Travel Award and various recognitions for his mentorship of student teams who achieved national-level prizes in robotics and circuit design competitions. These accolades underscore both the quality and impact of his scholarly work and his dedication to student development. His involvement as an Associate Editor for IEEE Transactions on Industrial Informatics and reviewer for top IEEE journals further validates his status as a trusted expert in his field. These honors collectively reflect his rising prominence in the global research community.

Conclusion

In summary, Dr. Xiaoxu Liu stands out as a highly capable and accomplished researcher in the field of intelligent control systems. With a solid educational foundation, diverse professional experience across top institutions, and a research portfolio that blends theoretical innovation with real-world application, he exemplifies academic excellence. His focus on robust fault diagnosis, resilient control systems, and data-driven approaches addresses some of the most pressing challenges in cyber-physical systems and smart manufacturing. Recognized nationally and internationally through numerous awards, editorial roles, and funded projects, Dr. Liu has established himself as a leader in his domain. He continues to advance the field through impactful publications, student mentorship, and collaborative projects. His trajectory reflects not only technical expertise but also a broader commitment to scientific progress and educational excellence. As such, Dr. Liu is highly deserving of recognition through accolades such as the Best Researcher Award.

Publications Top Notes

  • Title: Joint Observer Based Fault Tolerant Control for Discrete-Time Takagi-Sugeno Fuzzy Systems With Immeasurable Premise Variables

    • Authors: Xiaoxu Liu, Risheng Li, Zhiwei Gao, Bowen Li, Tan Zhang

    • Year: 2025

  • Title: Multiagent Formation Control and Dynamic Obstacle Avoidance Based on Deep Reinforcement Learning

    • Authors: Zike Yuan, Chenhao Yao, Xiaoxu Liu, Zhiwei Gao, Wenwei Zhang

    • Year: 2025

  • Title: Fault Estimation for Cyber–Physical Systems with Intermittent Measurement Transmissions via a Hybrid Observer Approach

    • Authors: Jingjing Yan, Chao Deng, Weiwei Che, Xiaoxu Liu

    • Year: 2024

    • Citations: 5

  • Title: Reinforcement Learning-Based Fault-Tolerant Control for Quadrotor UAVs Under Actuator Fault

    • Authors: Xiaoxu Liu, Zike Yuan, Zhiwei Gao, Wenwei Zhang

    • Year: 2024

    • Citations: 12