Roberto Simoni | Robotics | Scientific Breakthrough Award

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Prof Dr. Roberto Simoni | Robotics | Scientific Breakthrough Award

Professor, Federal University of Santa Catarina, Brazil

Roberto Simoni is a dedicated researcher and professor at the Federal University of Santa Catarina (UFSC) in Joinville, Brazil. With a robust academic background in Applied Mathematics and Mechanical Engineering, he is recognized for his expertise in robotics, especially in the design and analysis of parallel mechanisms. Simoni is currently an Adjunct Professor at UFSC’s Mobility Engineering Center and coordinates the Graduate Program in Mechanical Engineering and Sciences (POSECM). 📚✨

Publication Profile

Google Scholar

🎓 Education

Simoni earned a bachelor’s degree in Mathematics (2006), a master’s degree (2008), and a Ph.D. in Mechanical Engineering (2010), all from the Federal University of Santa Catarina (UFSC). His studies have contributed significantly to his expertise in applied mathematics and robotics. 🎓🔧

🧑‍🏫 Experience

Roberto Simoni is an Adjunct Professor at UFSC’s Joinville Campus, where he teaches courses in Vector Calculus and Robotics. His teaching and mentorship support the next generation of engineers in developing advanced technical and analytical skills in robotics and mechanical engineering. 👨‍🏫🤖

🔬 Research Interests

Simoni’s research focuses on applied mathematics and mechanical engineering, with a strong emphasis on robotics and parallel mechanisms. He specializes in the synthesis and analysis of parallel robots, industrial robotics, and underwater robots, aiming to advance robotics for industrial applications. 🔍⚙️

🏆 Awards

Throughout his career, Simoni has been involved in various prestigious research projects and collaborations, contributing to significant advancements in robotics. His work has gained notable recognition, especially in the field of parallel manipulators and robotic mechanisms. 🌟📈

📚 Publications

“Design of a Fast Robotic Total Station Through Ad Hoc Virtual Experiments and Its Digital Twin”
Published in Electronics (2024-10).
DOI: 10.3390/electronics13214248
Cited by: Indexed in Multidisciplinary Digital Publishing Institute. 📘🔍

“TetraFLEX: Design and Kinematic Analysis of a Novel Self-aligning Family of 3T1R Parallel Manipulators”
Published in Journal of Field Robotics (2022).
DOI: 10.1002/rob.22067
Cited by: Indexed in Scopus with ID 85125437850. 📕⚙️

“Wriflex: Design and Kinematic Analysis of a Self-aligning Parallel Wrist”
Published in Springer Proceedings in Advanced Robotics (2022).
DOI: 10.1007/978-3-031-08140-8_37
Cited by: Indexed in Scopus with ID 85133267035. 📗🔧

“Analysis of a 4-DOF 3T1R Parallel Robot for Machining Applications: A Stiffness Study”
Published in Lecture Notes in Mechanical Engineering (2021).
DOI: 10.1007/978-981-16-1769-0_15
Cited by: Indexed in Scopus with ID 85113390151. 📘🔬

Arturo Benayas Ayuso | Computer Science | Best Researcher Award

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Prof. Arturo Benayas Ayuso | Computer Science | Best Researcher Award

PhD Candidate, Universidad Politécnica de Madrid, Spain

Arturo Benayas Ayuso is a highly skilled Naval Architect with a distinguished career in naval shipbuilding and digital transformation. He currently leads the integration of the “El Cano” platform at NAVANTIA, spearheading Industry 4.0 innovations in ship design, construction, and management. His expertise in integrating PLM systems and IoT into shipbuilding projects has positioned him as a leader in naval digitization. Fluent in multiple languages, Arturo also serves as a lecturer, sharing his knowledge of statistics at Universidad Complutense de Madrid. 🚢💡

Publication Profile

ORCID

Education

Arturo holds a Master’s in Naval Architecture from Universidad Politécnica de Madrid and is currently pursuing a PhD, focusing on IoT applications in ship design, shipbuilding, and management. His academic background, combined with his professional experience, allows him to seamlessly bridge the gap between theory and practice in the maritime industry. 🎓📚

Experience

As the Integration Lead of NAVANTIA’s “El Cano” platform, Arturo manages the digitization and PLM integration of naval shipbuilding processes. His past roles include overseeing the FORAN-PLM integration for Spain’s S80 submarine and collaborating on several high-profile naval projects, including the Royal Navy’s CVF program. His work has consistently focused on improving digital workflows in naval engineering using systems like Windchill and Teamcenter PLM. 🛠️⚙️

Research Focus

Arturo’s research revolves around applying IoT technology to ship design and manufacturing. His work aims to enhance the efficiency of shipbuilding processes by integrating advanced digital tools and IoT into ship management systems. This focus on Industry 4.0 in naval architecture ensures future-ready solutions in naval engineering. 🔍🌐

Awards and Honors

Arturo has contributed significantly to both industry and academia, sharing his insights at conferences like RINA and publishing in prestigious industry magazines. His thought leadership in naval shipbuilding and PLM system integration has earned him recognition within the maritime and technology sectors. 🏅📜

Publications

Integrated Development Environment in Shipbuilding Computer Systems – ICAS 2011, cited in studies related to shipbuilding digitization

Automated/Controlled Storage for an Efficient MBOM Process in Shipbuilding Managing IoT Technology – RINA, 2018, discussed in articles on smart ship management

Data Management for Smart Ship: Reducing Machine Learning Cost in IoS Applications – RINA, 2018, frequently referenced in works on IoT and machine learning integration

Yanming Zhao | Computer Science | Best Researcher Award

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Prof. Yanming Zhao | Computer Science | Best Researcher Award

Professor at Hebei MINZU Normal University, China

Yanming Zhao is a distinguished Professor at Hebei University of Nationalities, specializing in visual computing and deep neural networks. With a commitment to advancing technology and innovation, he has made significant contributions to the field of computer application technology, evidenced by his extensive research and numerous publications. 🌟

Profile 

Scopus Profile

Education🎓

Yanming graduated with a Master’s degree in Computer Application Technology from the School of Information at Shenyang University of Technology in 2010. His academic background laid a solid foundation for his future research endeavors and leadership in academia.

Experience🏛️💼

As a Master’s Supervisor and experienced researcher, Professor Zhao has participated in over nine provincial-level research projects and has consulted on over 500 industry projects. His work not only showcases his expertise but also his dedication to bridging the gap between academia and industry.

Research Interests🔬📈

Professor Zhao’s research primarily focuses on visual computing and deep neural networks. He has developed innovative algorithms, including the visual selectivity-based 3D graph convolutional algorithm (VS-3DGCN), aimed at enhancing point cloud segmentation performance and addressing key challenges in 3D graph convolutional algorithms.

Awards 🏆

Throughout his career, Yanming has received numerous accolades, including the title of Excellent Scientific and Technological Worker in Hebei Province and Outstanding Expert Managed by Chengde City. These awards reflect his significant contributions to the scientific community and his leadership in research.

Publications

Professor Zhao has published more than 30 academic papers in esteemed journals, such as:

  • Multi-channel depth segmentation network based on 3D graph convolution algorithm and its application in point cloud segmentation
    • Authors: Zhao, Y.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Citations: 0
  • The Multi-View Deep Visual Adaptive Graph Convolution Network and Its Application in Point Cloud
    • Authors: Fan, H., Zhao, Y., Su, G., Zhao, T., Jin, S.
    • Journal: Traitement du Signal
    • Year: 2023
    • Citations: 4
  • Graph Convolution Algorithm Based on Visual Selectivity and Point Cloud Analysis Application
    • Authors: Zhao, Y., Su, G., Yang, H., Jin, S., Yang, J.
    • Journal: Traitement du Signal
    • Year: 2022
    • Citations: 2
  • Slow Feature Extraction Algorithm Based on Visual Selection Consistency Continuity and Its Application
    • Authors: Yang, H., Zhao, Y., Su, G., Fan, H., Shang, Y.
    • Journal: Traitement du Signal
    • Year: 2021
    • Citations: 0
  • Design and application of a slow feature algorithm coupling visual selectivity and multiple long short-term memory networks
    • Authors: Zhao, Y., Yang, H., Su, G.
    • Journal: Traitement du Signal
    • Year: 2021
    • Citations: 1

These contributions have garnered a total citation index of 102 times, illustrating the impact of his work on the research community. 📚🔗

Conclusion🌍✨

In summary, Professor Yanming Zhao stands out as a leading figure in the fields of visual computing and deep learning. His extensive research, numerous publications, and accolades make him a deserving candidate for the Best Researcher Award. His ongoing commitment to innovation and excellence continues to inspire colleagues and students alike.