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Assoc. Prof. Dr. Miao Li | Dexterous Hand | Best Researcher Award

Associate professor at Wuhan University, China

Miao Li is a distinguished robotics researcher with notable contributions to fields such as robotic grasping, robot learning, tactile sensing, and medical robots. His work has focused on improving the interaction between robots and their environment, particularly in sensitive domains like healthcare. Dr. Li’s extensive academic qualifications and ongoing research in robotics and medical technology demonstrate his commitment to advancing the field. As a Senior Member of IEEE, he is recognized for his scholarly work and leadership within the academic and professional community. His multidisciplinary research merges mechanical engineering with cutting-edge technology, allowing him to address pressing real-world problems, such as improving medical robots’ tactile sensitivity or enhancing robotic learning mechanisms. Dr. Li’s research has influenced both theoretical and applied robotics, contributing to the development of smarter, more capable robotic systems with real-world applications in medicine and autonomous operations.

Professional Profile

Education:

Miao Li’s academic journey has been marked by excellence in engineering and robotics. He obtained his bachelor’s and master’s degrees from the School of Mechanical Science and Engineering at Huazhong University of Science and Technology in Wuhan, China, in 2008 and 2011, respectively. His strong foundation in mechanical engineering propelled him to further his studies at Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland, where he completed his Ph.D. in 2016. At EPFL, Dr. Li honed his research skills, focusing on areas related to robotics, particularly robotic manipulation and medical applications. His educational background from prestigious institutions equipped him with both theoretical knowledge and practical insights, enabling him to contribute meaningfully to the field of robotics. Through his academic pursuits, Dr. Li has demonstrated a passion for pushing the boundaries of robotic technology, which is evident in the quality and impact of his research.

Professional Experience:

Miao Li’s professional experience encompasses a wide array of research and academic roles, each contributing to his expertise in robotics. After completing his Ph.D., he pursued advanced research in robotic systems, focusing on the integration of tactile sensing and learning algorithms into robotic platforms. His academic and professional career has seen him work with leading research institutions, contributing significantly to the field of robotics through both his research projects and collaborations. As a Senior Member of IEEE, Dr. Li has gained recognition for his thought leadership in the robotics community, publishing extensively in peer-reviewed journals and conferences. Additionally, his work in medical robots has seen collaborations with medical institutions, where his research has led to advances in the tactile capabilities of surgical robots. These collaborations are a testament to his ability to bridge the gap between academic research and practical applications, particularly in the healthcare sector. Through his career, Dr. Li has gained a comprehensive understanding of robotic technologies, further strengthening his contributions to both industry and academia.

Research Interests:

Miao Li’s primary research interests lie at the intersection of robotics, artificial intelligence, and healthcare. He is particularly focused on robotic grasping and manipulation, key areas of research aimed at improving how robots interact with objects and environments. Another significant aspect of his research is robot learning, which aims to enhance the adaptability and efficiency of robots in various tasks. Tactile sensing is another crucial area of interest for Dr. Li, as it plays an integral role in the development of robots that can sense and react to touch, improving their performance in delicate operations, such as in medical robotics. Furthermore, Dr. Li’s research in medical robots seeks to enhance the precision and capabilities of robotic systems used in surgery and rehabilitation. His work combines mechanical engineering, AI, and medical science to create more intelligent and responsive robotic systems that can assist in complex tasks, particularly in healthcare settings. Dr. Li’s research continues to evolve as he explores new frontiers in robotics, with the ultimate goal of developing robots capable of performing intricate tasks with minimal human intervention.

Research Skills:

Miao Li possesses a wide array of research skills that span several fields of robotics and engineering. One of his core strengths lies in the development and optimization of robotic manipulation algorithms, which are essential for enhancing robots’ ability to grasp and manipulate objects with precision. In this area, Dr. Li has demonstrated expertise in tactile sensing technologies, which allow robots to “feel” and interact with their environment in a way that closely mimics human touch. Additionally, his work in robot learning involves the use of machine learning techniques to improve robots’ ability to learn from their environment and perform tasks autonomously. His expertise in sensor technologies, algorithm development, and machine learning is complemented by a strong foundation in mechanical engineering, providing him with the skills to design and build the physical systems required for his research. Moreover, Dr. Li is well-versed in using simulation software to model robotic systems and test their performance in virtual environments before deployment. His multidisciplinary skill set has enabled him to tackle complex problems in both theoretical and applied robotics, making his research highly impactful.

Awards and Honors:

Miao Li has received several accolades throughout his academic and professional career, marking his contributions to the fields of robotics and engineering. Notably, he is a Senior Member of IEEE, an honor given to professionals who have demonstrated significant achievements in their field and contributed to advancing the engineering profession. His research in robotic manipulation, tactile sensing, and medical robotics has been widely recognized in the academic community, with several publications in high-impact journals and conferences. Additionally, Dr. Li’s work has been acknowledged through various institutional awards, including research grants and fellowships that have enabled him to pursue groundbreaking research in robotics. His recognition within the IEEE community highlights the significant impact of his work on the field of robotics. Dr. Li’s commitment to advancing technology in both theoretical and practical domains has earned him respect among his peers, further cementing his reputation as a leading researcher in the robotics field.

Conclusion:

Miao Li’s contributions to robotics research make him a highly deserving candidate for the Best Researcher Award. His expertise in robotic grasping and manipulation, robot learning, tactile sensing, and medical robotics reflects the depth and impact of his work in the field. With a solid academic background, extensive professional experience, and an ongoing commitment to innovative research, Dr. Li continues to push the boundaries of robotics and artificial intelligence. His research has not only advanced the understanding of robotic systems but also opened doors for practical applications in industries such as healthcare. Despite some potential areas for growth, particularly in expanding his commercial collaborations, Miao Li’s work remains at the forefront of robotics research. His contributions are helping shape the future of autonomous and medical robots, ensuring that he remains a key figure in advancing the field. As his career progresses, Miao Li’s research will undoubtedly continue to make significant strides in robotic technology, driving both academic and real-world innovations.

Publication Top Notes

  1. Title: A robotized framework for real-time detection and in-situ repair of manufacturing defects in CFRP patch placement
    Authors: Gong, Y., Li, X., Zhou, R., Li, M., Liu, S.
    Journal: Robotics and Computer-Integrated Manufacturing
    Year: 2025
    Volume: 92
    Article ID: 102882
  2. Title: Learning automatic navigation control skills for miniature helical robots from human demonstrations
    Authors: Li, M., Deng, X., Zhao, F., Liu, S., Li, M.
    Journal: Engineering Applications of Artificial Intelligence
    Year: 2024
    Volume: 137
    Article ID: 109187
  3. Title: Path planning for dual-arm fiber patch placement with temperature loss constraints
    Authors: Li, X., Zhou, R., Wang, W., Gong, Y., Li, M.
    Journal: Engineering Applications of Artificial Intelligence
    Year: 2024
    Volume: 133
    Article ID: 108518
    Citations: 2
  4. Title: Bioinspired Bidirectional Stiffening Soft Actuators Enable Versatile and Robust Grasping
    Authors: Lin, J., Ke, J., Xiao, R., Xiao, X., Guo, Z.
    Journal: Soft Robotics
    Year: 2024
    Volume: 11(3)
    Pages: 494–507
    Citations: 2
  5. Title: A Review on Robotized Automated Lay-up Technology for Composite Material Manufacturing | 机器人化复合材料自动铺层技术综述
    Authors: Guo, P., Yang, C.-G., Li, X.-L., Zhang, Y., Li, M.
    Journal: Zidonghua Xuebao/Acta Automatica Sinica
    Year: 2024
    Volume: 50(5)
    Pages: 873–897
  6. Title: IHUVS: Infinite Homography-Based Uncalibrated Methodology for Robotic Visual Servoing
    Authors: Lei, X., Fu, Z., Spyrakos-Papastavridis, E., Li, M., Chen, X.
    Journal: IEEE Transactions on Industrial Electronics
    Year: 2024
    Volume: 71(4)
    Pages: 3822–3831
    Citations: 1
  7. Title: Design of a Double-joint Robotic Fish Using a Composite Linkage
    Authors: Zhang, R., Zhou, W., Li, M., Li, M.
    Journal: Proceedings of the IEEE International Conference on Cybernetics and Intelligent Systems
    Year: 2024
    Pages: 279–283
  8. Title: Freehand Interaction With Visual Control and Haptic Feedback in Electromagnetically Assisted Interventional Surgery
    Authors: Deng, X., Zhao, J., Yuan, Z., Du, B., Yang, Z.
    Journal: IEEE Internet of Things Journal
    Year: 2024
    Volume: 11(24)
    Pages: 40845–40860
  9. Title: Design and Fabrication of a Novel Miniature Magnetic Gripper
    Authors: Li, M., Zhao, F., Li, X., Liu, S., Li, M.
    Journal: Proceedings – IEEE International Conference on Robotics and Automation
    Year: 2024
    Pages: 1964–1970
  10. Title: Learning Freehand Ultrasound Through Multimodal Representation and Skill Adaptation
    Authors: Deng, X., Jiang, J., Cheng, W., Yang, C., Li, M.
    Journal: IEEE Transactions on Automation Science and Engineering
    Year: 2024
    Citations: 1

 

Miao Li | Dexterous Hand | Best Researcher Award

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