Longxing Liao | Mechanical Engineering | Best Researcher Award | 13160

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Dr. Longxing Liao | Mechanical Engineering | Best Researcher Award

Dr. Longxing Liao, Jimei University, China

Dr. Longxing Liao is an accomplished researcher and academic affiliated with Jimei University, China. With expertise in marine engineering and renewable energy systems, Dr. Liao focuses on innovative solutions for sustainable development in coastal and maritime environments. He has contributed to cutting-edge research in renewable energy integration, resource optimization, and advanced marine technology applications. Dr. Liaoā€™s work aims to promote environmental sustainability and economic growth through the development of efficient energy systems and technologies, solidifying his reputation as a forward-thinking leader in his field.

Profile

Scopus

Early Academic Pursuits šŸŽ“

Dr. Longxing Liao embarked on his academic journey with a strong passion for engineering and innovation. He obtained his Doctor of Philosophy degree, laying the groundwork for a career focused on advancing knowledge and technological progress. Early in his studies, Dr. Liao developed an interest in high-performance manufacturing processes and chemical mechanical polishing, which would later become his primary areas of research. This foundational phase of his academic career equipped him with the technical expertise and critical thinking skills necessary to excel in the competitive field of mechanical and marine engineering.

Professional Endeavors šŸ”§

Currently, Dr. Liao serves as a lecturer and postgraduate supervisor at the School of Marine Equipment and Mechanical Engineering at Jimei University, China. In this capacity, he has been instrumental in shaping the next generation of engineers and researchers. He is not only an educator but also a hands-on researcher who has managed several high-impact projects. Dr. Liao has successfully secured funding for research initiatives from prestigious organizations, including:

  • The National Natural Science Foundation of China
  • Provincial and Municipal Natural Science Foundations
  • The Provincial Education Department

These projects have allowed Dr. Liao to explore innovative approaches to mechanical engineering challenges, emphasizing sustainability and efficiency.

Contributions and Research Focus šŸ› ļø

Dr. Liaoā€™s research primarily focuses on chemical mechanical polishing and high-performance manufacturing. His work in these areas has led to the publication of over 20 SCI-indexed papers in top-tier international journals, such as Applied Surface Science and the Journal of Manufacturing Processes. These publications are widely recognized for their innovative methodologies and impactful findings, contributing significantly to the body of knowledge in manufacturing and surface science.

Additionally, Dr. Liao holds an impressive portfolio of over 20 invention patents, with many ranked in the top two positions. His patented innovations demonstrate practical applications of his research, particularly in optimizing manufacturing processes and advancing material sciences.

Accolades and Recognition šŸ†

Dr. Liao’s contributions have not gone unnoticed. Among his many accolades are:

  • Second Prize of the Liaoning Provincial Patent Award in 2022 (ranked 2/6).
  • First Prize of the China Industry-University-Research Institute Collaboration Innovation Achievement Award (ranked 9/10).

Dr. Liaoā€™s commitment to fostering talent is evident in his guidance of undergraduate teams to achieve notable success:

  • Two National Third Prizes in the China Undergraduate Mechanical Engineering Innovation and Creativity Competition.
  • One National Second Prize in the National College Students’ Social Practice and Science Contest on Energy Saving, Emission Reduction, and Environmental Protection.

Furthermore, he was personally honored with the First Prize in the 2024 Young Teachers’ Award, highlighting his dual excellence as an educator and researcher.

Publication Top NotesšŸ“

A novel process of chemical-mechanical fluid-solid coupling polishing with high-quality and high-efficiency for turbine blisk

Author: Luo, S., Liao, L., Wang, Y.

Journal: Manufacturing Processes

Year: 2024

Structural design and hydrostatic analysis of an intelligent glass cleaning robot

Author: Wang, B., Liao, L., Zhou, M., Lin, Q., Chen, L.

Journal: The International Society for Optical Engineering,Ā 

Year: 2024

Study on the mechanism of chemical mechanical polishing on high-quality surface of single crystal diamond

Author: Liao, L., Luo, S., Chang, X., Li, S., Shutin, D.

Journal: Manufacturing Processes

Year: 2023

Geometric design and dynamic characteristics of a novel abnormal cycloidal gear reducer

Author: Mo, J., Gong, X., Luo, S., … Chang, X., Liao, L.

Journal: Advances in Mechanical Engineering

Year: 2023,

Study on hydrodynamic lubrication and friction reduction performance of spur gear with groove texture
Author: Chang, X., Renqing, D., Liao, L., … Huang, Y., Luo, S.

Journal: Tribology International

Year:Ā  2023

 

Carlo Alessi | Robotics and Automation | Best Researcher Award

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Mr. Carlo Alessi | Robotics and Automation | Best Researcher Award

Ph.D. Candidate at The Bio Robotics Institute, Sant’Anna School of Advanced Studies, Italy.

Carlo Alessi is a Ph.D. candidate specializing in BioRobotics at Scuola Superiore Santā€™Anna in Pisa, Italy. His research focuses on reinforcement learning for soft robot control, supported by a prestigious three-year grant under the EU project PROBOSCIS. Carlo’s academic journey includes M.Sc. and B.Sc. degrees in Computer Science from the University of Pisa, where he explored artificial intelligence and robotics through international study grants and research internships. He has contributed to notable publications and actively participates in leading conferences, showcasing his expertise in machine learning frameworks and robotics technologies. Carlo’s future endeavors include a post-doctoral position at the Italian Institute of Technology, Genova, where he will continue advancing robotic manipulation using tactile sensors in projects like ergoCub and FAIR. His interdisciplinary approach and commitment to innovation position him as a promising leader in the field of robotics and AI.

Professional Profiles:

Education šŸŽ“

Carlo Alessi holds a Bachelor of Science degree in Computer Science with honors from the University of Pisa, Italy, complemented by an Erasmus+ Study grant at the University of Bristol. His research during this period centered on convolutional neural networks for species detection in natural images. He proceeded to earn a Master of Science in Computer Science (Artificial Intelligence) at the same institution, achieving distinction. His master’s thesis focused on modulating motor commands using FORCE-trained Spiking Neural Networks, with additional studies at the University of Barcelona and Polytechnic University of Catalonia through another Erasmus+ grant. Currently a Ph.D. candidate in BioRobotics at The BioRobotics Institute, Scuola Superiore Santā€™Anna Pisa, Carlo’s research is funded by a three-year grant under the EU project PROBOSCIS, exploring Reinforcement Learning for Soft Robot Control. He actively tutors M.Sc. students and participates in leading conferences like the IEEE-RAS International Conference on Soft Robotics and Mediterranean Machine Learning Summer School.

Professional Experience

Carlo Alessi’s professional journey is marked by significant roles in cutting-edge robotics research. As a Research Assistant at The BioRobotics Institute, Scuola Superiore Santā€™Anna Pisa, Italy, he developed educational tools for soft robotics control using machine learning. His Ph.D. Research Internship at Bristol Robotics Laboratory, UK, focused on reinforcement learning for soft robot control, supported by an Erasmus+ Traineeship grant. Moving forward, Carlo is poised to join the Italian Institute of Technology, Genova, Italy, as an (Incoming) Post-Doctoral Researcher in the HumanoiD Sensing and Perception Group under Dr. Lorenzo Natale. Here, he will advance his expertise in machine learning for robot manipulation using tactile sensors, contributing to projects like ergoCub and FAIR. Carlo’s career highlights his dedication to robotics and artificial intelligence, coupled with a commitment to pushing the boundaries of research in bio-robotics. His contributions in academia and industry underscore his role as a leader in the field, driving innovation and technological advancement.

Research Interest

Carlo Alessi’s research interests revolve around the intersection of robotics, artificial intelligence, and machine learning, particularly in the domain of soft robotics. His doctoral research focuses on reinforcement learning techniques for enhancing the control and adaptability of soft robotic systems. Carlo is keenly interested in applying these methodologies to improve robot manipulation and sensory perception, with a specific emphasis on tactile sensors and their integration into robotic platforms. He is also intrigued by the broader implications of his research in advancing human-robot interaction and exploring new paradigms in robotic control strategies. Carlo’s work aims to contribute significantly to the development of intelligent robotic systems capable of autonomous learning and adaptation in dynamic environments. His interdisciplinary approach combines theoretical insights with practical applications, aiming to address real-world challenges in robotics and pave the way for future innovations in bio-robotics and beyond.

Award and Honors

Carlo Alessi has earned several prestigious accolades and honors throughout his academic and professional journey. He secured a significant Ph.D. research grant to advance his studies in BioRobotics at The BioRobotics Institute, Scuola Superiore Santā€™Anna Pisa, Italy, where his focus lies in reinforcement learning for enhancing soft robot control capabilities. His academic pursuits were further enriched by Erasmus+ Study Grants, facilitating enriching experiences at the University of Bristol, UK, and the University of Barcelona & Polytechnic University of Catalonia, Spain, where he explored cutting-edge applications in computer science and artificial intelligence. Carlo’s commitment to research excellence is underscored by impactful internships at institutions like Bristol Robotics Laboratory, UK, and Technical University of Munich, Germany, where he contributed to pioneering research in robotics and AI. He actively engages in the global academic community through participation in esteemed conferences such as the IEEE-RAS International Conference on Soft Robotics and the Mediterranean Machine Learning Summer School, where he shares insights and collaborates on advancing technological frontiers in his field. These honors highlight Carlo’s dedication to pushing the boundaries of robotics research and his significant contributions to the academic community.

Research Skills

Carlo Alessi possesses a strong foundation in robotics and artificial intelligence research, emphasizing expertise in reinforcement learning and machine learning frameworks such as Stable-baselines, OpenAI Gym, and PyTorch. His practical skills extend to ROS, Gazebo simulation, Arduino, and Lego Mindstorms, facilitating the development and integration of robotic systems. Proficient in C, C++, Python, and Java, Carlo applies these languages alongside Matlab, Bash scripting, and SQL for algorithm development and data analysis. He excels in experimental design, execution, and statistical analysis, pivotal for deriving insights in his research. Carlo’s ability to communicate findings effectively through publications and presentations at international conferences underscores his dedication to advancing the field, making significant contributions to robotics and AI research.

Publications

  1. Learning a Controller for Soft Robotic Arms and Testing its Generalization to New Observations, Dynamics, and Tasks
    • Authors: Alessi, C., Hauser, H., Lucantonio, A., Falotico, E.
    • Conference: 2023 IEEE International Conference on Soft Robotics, RoboSoft 2023
    • Year: 2023
    • Citations: 2
  2. Ablation Study of a Dynamic Model for a 3D-Printed Pneumatic Soft Robotic Arm
    • Authors: Alessi, C., Falotico, E., Lucantonio, A.
    • Journal: IEEE Access, 2023, 11, pp. 37840ā€“37853
    • Year: 2023
    • Citations: 7