Juan Carlos Antolin Urbaneja | Vision Sensing | Best Researcher Award

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Dr. Juan Carlos Antolin Urbaneja | Vision Sensing | Best Researcher Award

Dr. Juan Carlos Antolin Urbaneja, TECNALIA, Basque Research and Technology Alliance, BRTA, Spain.

Juan Carlos Antolín Urbaneja is a Senior Researcher at TECNALIA, part of the Basque Research & Technology Alliance (BRTA). With over 25 years of experience in robotics and automation, Juan Carlos specializes in 3D vision, 3D reconstruction, robotized inspection, and image analysis. He has worked on diverse technologies, including surface treatment, water quality identification, robots, and additive manufacturing. His contributions extend to various industrial sectors such as biomedical, automotive, and aeronautical, where he develops custom software and hardware solutions. He has led numerous public and private research projects and co-authored a European patent.

Professional Profile

ORCID

Suitability of Juan Carlos Antolín Urbaneja for the Best Researcher Award

Juan Carlos Antolín Urbaneja, I believe he is highly suitable for the Best Researcher Award. He has successfully managed and executed around 40 research projects, including both public and private funding, indicating a strong ability to drive innovative research initiatives.

Education 🎓

Juan Carlos holds a degree in Industrial Engineering with an electrical specialty (2000) from Bilbao Faculty of Engineering, Basque Country University. He also completed a degree in Innovation and Technology Management (2004) from Deusto Faculty (ESIDE). His academic journey culminated in a Ph.D. in Control Engineering, Automation, and Robotics from the University of the Basque Country in 2017. This foundation in engineering and management has propelled him into an influential career in robotics and automation, blending theoretical knowledge with practical applications in cutting-edge technologies.

Experience 💼

With a robust career spanning 25 years, Juan Carlos has been deeply involved in the research, development, and execution of advanced robotic systems. He has participated in over 40 projects, both public and private, and has contributed significantly to the development of innovative machines used in various industries. His expertise includes electrical and electronic design, where he applies programming tools like Matlab-Simulink and LabVIEW. Juan Carlos is also a peer reviewer and co-author of scientific papers, contributing to the field’s growth. His notable contributions include robotic inspection systems and advanced additive manufacturing techniques.

Research Interests 🔬

Juan Carlos’s research interests are centered around robotics, automation, and additive manufacturing. His work explores the development of systems for robotized inspection and 3D scanning, with applications in large-scale parts inspection and dimensional qualification. He is particularly interested in enhancing the capabilities of robots to interact with complex materials and environments, such as biomedical and automotive sectors. His research also spans innovations in wave energy and surface treatment, continuously striving for breakthroughs that bridge the gap between theoretical research and practical industrial solutions.

Awards 🏆

Juan Carlos has received numerous accolades throughout his career. He is the recipient of more than 20 awards, including recognition for his contributions to robotics, automation, and innovation. His work in additive manufacturing and robotized inspection has earned him widespread recognition in scientific communities. As a testament to his contributions, he was nominated for several prestigious awards, including the Distinguished Scientist Award and the Outstanding Scientist Award. These honors reflect his excellence in both research and industrial applications, highlighting his impact on technological advancements.

Publications Top Notes📚

Automated MOLDAM Robotic System for 3D Printing: Manufacturing Aeronautical Mould Preforms

Robotized 3D Scanning and Alignment Method for Dimensional Qualification of Big Parts Printed by Material Extrusion

Experimental Characterization of Screw-Extruded Carbon Fibre-Reinforced Polyamide: Design for Aeronautical Mould Preforms with Multiphysics Computational Guidance

Coordination of Two Robots for Manipulating Heavy and Large Payloads Collaboratively: SOFOCLES Project Case Use

Robot Coordination: Aeronautic Use Cases Handling Large Parts

 

Assoc. Prof. Dr.Dongdong Li | Vision Sensing Award| Best Researcher Award

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Assoc. Prof. Dr.Dongdong Li | Vision Sensing Award| Best Researcher Award

Assoc. Prof. Dr.Dongdong Li ,National University of Defense Technology,China

Dr. Dongdong Li is an Associate Researcher and Master Tutor at the College of Electronic Science and Technology, National University of Defense Technology (NUDT), Hunan, China. He also serves as the deputy director of the “Distributed Reconnaissance and Countermeasures” program and leads the Vision4Drone research team. Dr. Li earned his PhD in Information and Communication Engineering from NUDT in 2018, with his research focusing on robust visual tracking and UAV vision systems. His academic journey includes a joint doctoral program at the Australian National University and a master’s degree from NUDT. Dr. Li has received several prestigious awards, including the Military Scientific and Technological Progress Second Prize and the Outstanding Doctoral Dissertation Nomination from the China Education Society. He has been recognized as a leading young scientist by various institutions and has presided over numerous significant research projects. Dr. Li is actively involved in editorial and guest editing roles for several high-impact journals and conferences.

Professional Profile:

Google Scholar

Summary of Suitability for the Best Researcher Award: Dongdong Li

Dongdong Li exemplifies the qualities of a leading researcher through his substantial contributions to computer vision and drone technology. His leadership in groundbreaking research, recognition through prestigious awards, active involvement in academic publications and editorial roles, and dedication to teaching and mentorship collectively position him as a highly suitable candidate for the Best Researcher Award. His work not only advances scientific understanding but also has practical implications for technology development and application.

🎓Education:

Dr. Dongdong Li earned his PhD in Information and Communication Engineering from the National University of Defense Technology (NUDT), Changsha, Hunan, China, in December 2018. His dissertation, titled “When Correlation Filters Meet Siamese Networks for Robust Visual Tracking,” was recognized as an Outstanding Doctoral Dissertation of Hunan Province and was supervised by Prof. Gongjian Wen. He completed his Master’s in Information and Communication Engineering at NUDT in December 2014, with his thesis on “Research on Cross-ratio Based Camera Calibration and Vibration Correction in Digital Steak Photogrammetric Measurement,” which received the Excellent Master Dissertation of Hunan Province award, also under the supervision of Prof. Gongjian Wen. Dr. Li obtained his Bachelor’s in Information and Communication Engineering from Wuhan University, China.

🏢Work Experience:

Dr. Dongdong Li has held several prominent academic positions. Since October 2021, he has been an Associate Professor at the College of Electronic Science and Technology, National University of Defense Technology (NUDT), Changsha, Hunan, China. He has also been serving as a Postdoctoral Fellow at the School of Aerospace Science, NUDT, since August 2021, under the guidance of Academician Qifeng Yu. Prior to these roles, Dr. Li was a Lecturer at the School of Electronic Science, NUDT, from December 2018 to September 2021, where he worked with Professor Gongjian Wen. He participated in a Joint Doctoral Program at the School of Computer Science and Engineering, Australian National University, from February 2017 to February 2018, with Professor Fatih Porikli as his co-supervisor. Dr. Li conducted his PhD research at NUDT from March 2015 to December 2018 and completed his Master’s research there from September 2012 to December 2014.

🏆Awards:

Dr. Dongdong Li has received several notable awards for his contributions to his field. In 2020, he was honored with the Second Prize of Military Scientific and Technological Progress and the Outstanding Doctoral Dissertation Nomination Award from the China Education Society. He also received the Excellent Paper Nomination Award at the China Information Fusion Conference in 2021 and the Hunan Province Excellent Doctoral Dissertation Award in the same year. In 2017, he was recognized with the Hunan Excellent Master’s Degree Thesis Award. Dr. Li’s achievements extend to competitive events as well, with his team winning the Graduate Electronic Design Competition National Finals First Prize in 2022. He also served as the Second Prize Instructor for the Army’s “Maker Action-2022” Big Data Application Track and was an advisor for teams that earned Third Prizes at both the 5th China Graduate Robot Innovation Design Competition and the 5th China Graduate Artificial Intelligence Innovation Competition in 2023.

Publication Top Notes:

  • Title: Bioinspired Multi-Stimuli Responsive Actuators with Synergistic Color-and Morphing-Change Abilities
    • Citations: 127
  • Title: Template-Based Synthesis and Magnetic Properties of Cobalt Nanotube Arrays
    • Citations: 126
  • Title: Overcoming the Strength–Ductility Trade-Off by Tailoring Grain-Boundary Metastable Si-Containing Phase in β-Type Titanium Alloy
    • Citations: 100
  • Title: Flexible Solar Cells Based on Foldable Silicon Wafers with Blunted Edges
    • Citations: 95
  • Title: The Study on Oxygen Bubbles of Anodic Alumina Based on High Purity Aluminum
    • Citations: 82

 

 

 

Lijuan Jia | Vision Sensing Award | Best Researcher Award

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Prof. Lijuan Jia | Vision Sensing Award | Best Researcher Award

Professor at Beijing institute of technology – Huddersfield, China

Jia Lijuan is an accomplished researcher and academic with expertise in electrical and electronic engineering, particularly in the areas of signal processing and vision sensing. She received her Ph.D. from Kyushu University, Japan, and has held various academic positions, including lecturer at Kyushu University and associate professor at Beijing Institute of Technology. Jia’s research interests include multi-living agent system theory, distributed adaptive networks, statistical signal processing, Artificial Intelligence, and Remote Sensing. She has published extensively, with over 70 papers as the first author or corresponding author, including over 50 SCI and EI papers. Jia has also been actively involved in professional committees and has received recognition for her contributions to the field. She is a member of the China Automation Society and the China Electronics Society, showcasing her commitment to advancing the field of electrical and electronic engineering.

Professional Profile

Education:

Jia Lijuan received her Ph.D. degree in electrical and electronic engineering from Kyushu University, Japan, in 2002. She pursued her doctoral studies after completing her undergraduate education.

Work Experiences:

Jia Lijuan has a diverse and extensive work experience in academia and research. She began her career as a lecturer at the Department of Electrical and Electronic Engineering at Kyushu University, Japan, where she taught from 2002 to 2005. Following this, she joined the School of Information and Electronics at Beijing Institute of Technology, where she has been serving as an associate professor since 2005. In addition to her academic roles, Jia has also been actively involved in research and professional activities. She spent a year as a visiting scholar at the Department of Electrical Engineering at the University of California, Los Angeles, USA, from 2013 to 2014. Throughout her career, Jia has demonstrated a commitment to academic excellence and has contributed significantly to the fields of multi-living agent system theory, distributed adaptive networks, statistical signal processing, Artificial Intelligence, and Remote Sensing. Jia has also played important roles in various academic and professional committees. She served as the Secretary General of the Beijing District Proposition Review Committee of the China Graduate Electronic Design Competition in 2011. Furthermore, she was a member of the Technical Procedures Committee of the International Conference on Signal Processing Systems in 2022 and served as the Invited Session Co-organizer at the 2022 China Automation Conference. Jia’s work has been recognized through numerous publications, including over 70 papers as the first author or corresponding author, including over 50 SCI and EI papers. She is also an inventor, holding more than 10 authorized patents, and has authored 2 books.

Skills:

Jia Lijuan possesses a wide range of skills in the field of electrical and electronic engineering, with a particular focus on signal processing and related areas. Her expertise includes but is not limited to multi-living agent system theory, distributed adaptive networks, statistical signal processing, Artificial Intelligence, and Remote Sensing. Jia has demonstrated proficiency in conducting advanced research, as evidenced by her extensive publication record, which includes over 70 papers as the first author or corresponding author, including over 50 SCI and EI papers. In addition to her research skills, Jia has also shown proficiency in academic leadership and organizational roles. She has served as the Secretary General of the Beijing District Proposition Review Committee of the China Graduate Electronic Design Competition, showcasing her ability to coordinate and manage academic initiatives. Furthermore, her role as the Invited Session Co-organizer at the 2022 China Automation Conference highlights her organizational skills and ability to collaborate with peers in the field. Jia’s skills extend beyond academia, as she is also an inventor with more than 10 authorized patents. This demonstrates her ability to translate theoretical knowledge into practical applications. Overall, Jia Lijuan’s skills reflect her dedication to advancing the field of electrical and electronic engineering through innovative research, academic leadership, and practical contributions.

Research Interest:

Jia Lijuan’s research interests span several areas within the field of electrical and electronic engineering, with a focus on signal processing and related disciplines. She has a particular interest in multi-living agent system theory, which involves studying the behavior and interactions of complex systems composed of multiple agents. This area of research has applications in various fields, including robotics, control systems, and networked systems. Additionally, Jia is interested in distributed adaptive networks, which involve developing algorithms and protocols for networks that can adapt and optimize their performance based on changing conditions. This research area is crucial for improving the efficiency and reliability of communication networks, especially in dynamic environments. Statistical signal processing is another area of interest for Jia. This field involves developing mathematical models and algorithms for analyzing and interpreting signals, such as audio, video, and sensor data. This research is essential for applications such as speech recognition, image processing, and biomedical signal analysis. Jia also has a keen interest in Artificial Intelligence (AI) and its applications in signal processing. This includes developing AI algorithms for tasks such as pattern recognition, machine learning, and data mining. Finally, Jia’s research interests extend to Remote Sensing, which involves using satellite and airborne sensors to collect data about the Earth’s surface and atmosphere. This research has applications in environmental monitoring, disaster management, and resource management. Overall, Jia Lijuan’s research interests reflect her commitment to advancing the field of signal processing and its applications through innovative research and interdisciplinary collaboration.

Publications:

An automatic extraction method for geothermal radiation sources based on an LST retrieval algorithm and semantic network

Authors: He, R., Jia, L., Zhang, J.

Citations: 0

Year: 2023

Shale Core Fracture Extraction Method Based on Edge Detection and Hierarchical Semantic Fusion Network

Authors: He, R., Jia, L., Zhang, J., Peng, S.

Citations: 0

Year: 2023

A Novel Bias-Compensated Linear Constrained Least Mean Squares Algorithm Over Distributed Network

Authors: Wang, L., Jia, L., Miao, D., Guo, Y., Kanae, S.

Citations: 0

Year: 2023

Close-in weapon system planning based on multi-living agent theory

Authors: Tang, T., Wang, Y., Jia, L.-J., Hu, J., Ma, C.

Citations: 1

Year: 2022

Blind adaptive identification and equalization using bias-compensated NLMS methods

Authors: Zhang, Z., Jia, L., Tao, R., Wang, Y.

Citations: 1

Year: 2022

Diffusion bias-compensated recursive maximum correntropy criterion algorithm with noisy input

Authors: Li, Y., Jia, L., Yang, Z.-J., Tao, R.

Citations: 8

Year: 2022

Reliability analysis and selective maintenance for multistate queueing system

Authors: Tang, T., Jia, L., Hu, J., Wang, Y., Ma, C.

Citations: 4

Year: 2022

Spatial-Temporal Minimum Error Random Interaction Networks for Distributed Estimation

Authors: Zhu, C., Jia, L., Yang, Z.-J., Tao, R.

Citations: 0

Year: 2022

Robust Diffusion Adaptive Networks with Noisy Link and Input

Authors: Zhu, C., Jia, L., Kanae, S., Yang, Z.

Citations: 0

Year: 2022

Bias-compensated Sparse RLS Algorithms Over Distributed Networks

Authors: Peng, S., Jia, L., Kanae, S., Yang, Z.-J.

Citations: 0

Year: 2022