Dr.Nabih Pico | Autonomous Robot Navigation | Best Researcher Award

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Dr. Nabih Pico | Autonomous Robot Navigation | Best Researcher Award

Research Professor, Sungkyunkwan University, South Korea

Dr. Nabih Pico is an accomplished researcher and educator in the field of autonomous robot navigation and artificial intelligence. With a Ph.D. in Mechanical Engineering from Sungkyunkwan University, South Korea, he is an expert in mobile robots, robotics intelligence, and machine learning. He currently serves as a Research Professor at Sungkyunkwan University, leading cutting-edge research in robotics, and is also an Assistant Professor at ESPOL-FIEC, Ecuador. Throughout his career, Dr. Pico has made significant strides in the development of autonomous navigation systems, dynamic obstacle tracking, and deep reinforcement learning. His work has been recognized globally, earning awards such as the Grand Prize in Research from Sungkyunkwan University. He has contributed extensively to academic publications, conferences, and has filed numerous patents in the robotics domain. His research continues to push boundaries in autonomous robot navigation, improving performance in diverse and challenging environments.

Profile

Orcid

Education

Dr. Nabih Pico completed his Ph.D. in Mechanical Engineering from Sungkyunkwan University, South Korea, where he focused on autonomous robot navigation, machine learning, and deep reinforcement learning. He earned his Bachelor’s degree in Electronics and Telecommunications Engineering from Escuela Politécnica del Litoral, Ecuador, in 2014. During his Ph.D. studies, Dr. Pico specialized in robotics, working extensively on mobile robot design, dynamic obstacle recognition, and innovative solutions for autonomous navigation in outdoor and indoor environments. His research journey has helped shape the development of smarter, more adaptive robotic systems.

Experience

Dr. Nabih Pico currently holds positions as a Research Professor at Sungkyunkwan University, where he leads research in autonomous robot navigation and AI applications for robotics. He is also an Assistant Professor at ESPOL-FIEC, Ecuador, focusing on robotics and teaching remotely. Dr. Pico’s past roles include a Postdoctoral Research position at Sungkyunkwan University in collaboration with Hyundai Robotics, where he led projects on AI-driven obstacle recognition and dynamic navigation. Previously, he was a Ph.D. student at Sungkyunkwan University-KETI, where he pioneered mobile robot development capable of climbing stairs and detecting irregular terrains using LiDAR sensors. His work has included designing robots to navigate diverse environments and improving their stability and adaptability. Dr. Pico has led multiple industrial and academic projects, contributed to scientific papers, and patented innovative solutions for robotics challenges.

Awards and Honors

Dr. Nabih Pico’s academic achievements have been recognized with several prestigious awards. He received the Grand Prize in Research at the School of Mechanical Engineering, Sungkyunkwan University, for his work on enhancing the intelligence of robots for autonomous navigation in indoor environments based on Deep Reinforcement Learning. In 2024, Dr. Pico was honored with the Postdoctoral Research Award at the 2024 Graduate School Research Achievement Competition at Sungkyunkwan University. His research excellence and contributions to robotics also earned him accolades like the SKKU Human-Centered Convergence Machine Solution Future Talent Training Award. These honors highlight his profound impact on the field of robotics and his leadership in autonomous navigation research, which has advanced the development of intelligent mobile robots.

Research Focus 

Dr. Nabih Pico’s research focuses on autonomous robot navigation, machine learning, and artificial intelligence applications in robotics. He specializes in deep reinforcement learning (DRL) for improving robot decision-making and autonomy in dynamic environments. His projects revolve around mobile robots designed to navigate through complex and irregular terrains, including stairs, slopes, and obstacles. Dr. Pico has developed various solutions, such as dynamic obstacle recognition and the integration of LiDAR sensors for terrain detection. He is committed to advancing the capabilities of robots for both indoor and outdoor applications, including in industrial settings where robots must adapt to challenging conditions. His research also emphasizes enhancing robot mobility through innovative suspension systems and autonomous control strategies. With a keen interest in real-time processing and multi-sensor fusion, Dr. Pico continues to explore ways AI and machine learning can improve robot performance and decision-making in diverse environments.

Publication Top Notes

  1. Memory-driven deep-reinforcement learning for autonomous robot navigation in partially observable environments 📄
  2. Integrating Radar-Based Obstacle Detection with Deep Reinforcement Learning for Robust Autonomous Navigation 🛠️
  3. Task-Motion Planning System for Socially Viable Service Robots Based on Object Manipulation 🤖
  4. Unloading sequence planning for autonomous robotic container-unloading system using A-star search algorithm 🛳️
  5. Simultaneous Multi-channel Positive and Negative Pneumatic Boosting System for Operating Pneumatic Soft Actuators 🌬️
  6. Static and Dynamic Collision Avoidance for Autonomous Robot Navigation in Diverse Scenarios based on Deep Reinforcement Learning ⚙️
  7. Variable Admittance Control for Compliant Collaboration in Physical Human-Robot-Environment Interaction 👫
  8. Application of A Reliable Dynamic Friction Model for Accurate Dynamic Model Parameters Estimation of Robot Manipulators 🔧
  9. Box segmentation, position, and size estimation for robotic box handling applications 📦
  10. Climbing control of autonomous mobile robot with estimation of wheel slip and wheel-ground contact angle 🚶‍♂️

 

Ejup Hoxha | Robotics | Best Researcher Award

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Mr Ejup Hoxha | Robotics | Best Researcher Award

PhD Candidate, The City College of New York, United States

Ejup Hoxha is a Machine Learning Engineer at Amazon Web Services (AWS) in New York, specializing in Large Language Models (LLMs), time series forecasting, and machine learning/deep learning. He is also a PhD candidate in Electrical Engineering at The City College of New York. With experience in robotics, sensor fusion, visual SLAM, and computer vision, Ejup contributes significantly to the field of non-destructive testing (NDT). His work spans across robotics, automation, and software development, making him a versatile and innovative engineer. Ejup has contributed to multiple research projects and has served as an adjunct lecturer, teaching courses related to robotics and engineering. His research, aimed at improving construction and infrastructure processes, has earned recognition in prestigious journals and conferences.

Professional Profile

Google Scholar

Scopus

Strengths for the Award

Ejup Hoxha has demonstrated an exceptional ability to merge cutting-edge machine learning and robotics technologies with practical applications in infrastructure inspection, particularly in non-destructive testing (NDT) and robotic systems. His contributions to fields like Ground Penetrating Radar (GPR) imaging, robotic inspection, and subsurface defect mapping are groundbreaking, as evidenced by his high-quality publications and their citations in top-tier journals and conferences. Notably, his work on automated GPR reconstruction and impact-echo methods for concrete inspection is both innovative and impactful, addressing real-world challenges in construction and infrastructure maintenance. His strong expertise in robotics, reinforcement learning (RL), and sensor fusion enhances his ability to propose novel solutions in both academic and industrial settings. Furthermore, his leadership in developing secure and scalable systems at AWS further solidifies his role as a pioneering researcher.

Areas for Improvements

While Ejup has achieved great success in his technical work, expanding his focus to the commercial viability and broader industrial applications of his research could make his innovations even more impactful. His future work could benefit from fostering collaborations with multidisciplinary teams to integrate more cross-sector knowledge, which would help create versatile and adaptable systems that address a broader range of industry needs. Additionally, increasing his outreach and visibility through more industry-driven projects, real-world implementation, and knowledge-sharing platforms could further enhance the practical application and adoption of his work.

Education

Ejup Hoxha is currently pursuing a PhD in Electrical Engineering at The City College of New York. He holds a Master of Philosophy in Electrical Engineering (2023) from the same institution. Ejup completed a Master of Science in Computer Engineering (2020) and a Master of Science in Computerized Automation and Robotics from the University of Pristina in Kosovo. His educational foundation began with a Bachelor of Science in Electrical and Computer Engineering, specializing in Automation, from the University of Pristina in 2015. Ejup’s rigorous academic background supports his expertise in machine learning, robotics, and control systems, enabling him to lead innovative research and practical applications in his field.

Experience

Ejup Hoxha currently works as a Machine Learning Engineer II at AWS, where he specializes in developing automated LLM evaluation methods and fine-tuning systems. Prior to this, he was a Software Development Engineer I at AWS, responsible for designing secure, scalable, distributed systems. As a Graduate Research Assistant and Adjunct Lecturer at The City College of New York, Ejup led robotics projects involving reinforcement learning (RL), sensor fusion, visual SLAM, and computer vision. He has also worked as a Robotic Systems Engineer at InnovBot LLC, where he developed sensor fusion and control algorithms. Additionally, Ejup has experience in SCADA software development and automation, gained during his roles at N.P. INET and Call Home Electronics in Kosovo.

Awards and Honors

Ejup Hoxha has received recognition for his contributions to robotics and machine learning. His work in robotics, particularly in the area of robotic inspection and subsurface defect mapping, has been presented in renowned conferences and journals. He has been cited for his research on ground penetrating radar (GPR) and robotic systems for underground utilities. Ejup’s academic excellence has been acknowledged through multiple research awards, including his publication in IEEE Sensors Journal and the Journal of Computing in Civil Engineering. His achievements reflect his deep commitment to advancing robotics and NDT technologies, earning him the respect of peers in the engineering community.

Research Focus

Ejup Hoxha’s research focuses on the intersection of machine learning, robotics, and non-destructive testing (NDT). He specializes in robotic systems for infrastructure inspection, employing techniques like reinforcement learning, sensor fusion, and computer vision to enhance the efficiency of underground utility surveys and concrete inspections. His work with ground penetrating radar (GPR) and impact-echo methods aims to improve subsurface defect mapping and utility reconstruction. Additionally, Ejup’s research explores the application of artificial intelligence and deep learning to automation systems, with a focus on time-series forecasting and the development of automated LLM evaluation methods. His interdisciplinary research contributes to the evolution of smart systems for infrastructure monitoring and maintenance.

Publication Top Notes

  • GPR-based model reconstruction system for underground utilities using GPRNet 📑
  • Improving 3D Metric GPR Imaging Using Automated Data Collection and Learning-based Processing 📘
  • Robotic inspection of underground utilities for construction survey using ground penetrating radar 📍
  • Robotic Inspection and Subsurface Defect Mapping Using Impact-echo and Ground Penetrating Radar 🔧
  • Robotic Inspection and Characterization of Subsurface Defects on Concrete Structures Using Impact Sounding 🏗️
  • Automatic Impact-sounding Acoustic Inspection of Concrete Structure 🔊
  • Robotic Inspection and 3D GPR-based Reconstruction for Underground Utilities 🛰️
  • Contrastive learning for robust defect mapping in concrete slabs using impact echo 🎯

Conclusion

Ejup Hoxha is a deserving candidate for the Best Researcher Award. His innovative contributions to robotics, machine learning, and infrastructure inspection place him at the forefront of research in these fields. His ability to leverage advanced AI and robotics technologies to address challenges in non-destructive testing and construction is exemplary. With continued focus on collaboration and the commercialization of his work, Ejup has the potential to make an even greater impact on both academic and industrial domains. His research accomplishments, technical expertise, and commitment to advancing knowledge in his field make him an excellent contender for this prestigious award.

Lijun Zong | Robotics and AI | Best Researcher Award

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Assoc. Prof. Dr Lijun Zong | Robotics and AI | Best Researcher Award

Associate Professor, Northwestern Polytechnical University, China

Lijun Zong, born on April 28, 1991, in Zhangye, Gansu, China, is an Associate Professor at Northwestern Polytechnical University. A prolific researcher in aerospace robotics, his contributions focus on modular, reconfigurable robots and space manipulator systems. He earned his B.Sc. in Detection, Guidance, and Control Technology from Beijing Institute of Technology, followed by M.Sc. and Ph.D. degrees in Aerospace Vehicle Design at Northwestern Polytechnical University. As a visiting scholar at the University of Toronto Institute for Aerospace Studies, he honed his expertise in hardware-in-the-loop synthesis for space manipulators. Dr. Zong’s groundbreaking research has led to numerous publications in top-tier journals, reflecting his leadership in aerospace robotics.

PROFISSIONAL PROFILE

Google Scholar

Scopus

STRENGTHS FOR THE AWARD

Dr. Lijun Zong’s distinguished research contributions to aerospace robotics, particularly in the domain of space manipulators and their control systems, make him an outstanding candidate for the Best Researcher Award. His work on reactionless control, trajectory optimization, and hardware-in-the-loop simulations addresses critical challenges in modern aerospace engineering.

  1. Pioneering Publications: Dr. Zong has authored impactful papers in high-ranking journals such as IEEE Transactions on Aerospace and Electronic Systems and Aerospace Science and Technology. Key works include advancements in reactionless control for free-floating space manipulators and concurrent rendezvous control of underactuated manipulators.
  2. Global Research Exposure: As a visiting scholar at the University of Toronto Institute for Aerospace Studies, Dr. Zong collaborated internationally, enhancing the global applicability and validation of his research.
  3. Advanced Methodologies: His research employs cutting-edge approaches, such as mixed-integer predictive control, concurrent learning, and game-theoretic optimization, to address practical and theoretical aerospace challenges.
  4. Proven Impact: His work has been cited frequently, reflecting its relevance and influence in academia and industry. Topics like modular and reconfigurable robotics demonstrate innovative solutions for future aerospace missions.
  5. Leadership in Aerospace Research: As an Associate Professor at Northwestern Polytechnical University, Dr. Zong has demonstrated his capability in leading research teams, publishing prolifically, and mentoring future aerospace engineers.

AREAS FOR IMPROVEMENT

  1. Industry Collaboration: While Dr. Zong’s academic achievements are remarkable, deeper collaborations with aerospace industries could further validate his methodologies in real-world applications.
  2. Public Engagement: Increasing the visibility of his work through outreach programs or public talks could help bridge the gap between cutting-edge research and societal understanding of aerospace advancements.
  3. Interdisciplinary Expansion: Expanding his research to include intersections with artificial intelligence and machine learning could further enhance the robustness of his control systems for aerospace applications.

EDUCATION 

  • Ph.D. in Aerospace Vehicle Design (2015–2020)
    Northwestern Polytechnical University, Xi’an, China
    Thesis: “Optimal Trajectory Planning and Coordinated Control for Space Manipulators Capturing a Tumbling Target” | Advisor: Prof. Jianjun Luo
  • Visiting Scholar (2016–2018)
    University of Toronto Institute for Aerospace Studies, Toronto, Canada
    Subject: “Hardware-in-the-loop Synthesis and Analysis of Space Manipulators”
  • M.Sc. in Aerospace Vehicle Design (2013–2015)
    Northwestern Polytechnical University, Xi’an, China
    Thesis: “Occasion Determination and Control for Space Manipulators Capturing Tumbling Targets”
  • B.Sc. in Detection, Guidance, and Control Technology (2009–2013)
    Beijing Institute of Technology, Beijing, China

EXPERIENCE 

  • Associate Professor (Present)
    Northwestern Polytechnical University, Xi’an, China
    Specializing in aerospace robotics, modular systems, and trajectory optimization.
  • Visiting Researcher (2016–2018)
    University of Toronto Institute for Aerospace Studies, Toronto, Canada
    Conducted research in hardware-in-the-loop simulations for space manipulators under Prof. M. Reza Emami.
  • Postdoctoral Researcher (2020)
    Focused on control strategies for space manipulators and robotic systems.
  • Early Research Experience (2013–2020)
    Developed concurrent learning and control techniques for space manipulators and obstacle-avoidance strategies during doctoral and master’s studies.

AWARDS AND HONORS 

  • Best Researcher Award in Aerospace Robotics (2023)
  • IEEE Outstanding Contribution Award (2021)
  • Young Scientist Award by Northwestern Polytechnical University (2019)
  • Journal of Aerospace Excellence Reviewer Recognition (2018)
  • Top 10 Innovators in Robotics by China Robotics Forum (2017)

RESEARCH FOCUS 

Dr. Zong’s research focuses on aerospace robotics, including modular and reconfigurable robots, reactionless control mechanisms, and trajectory optimization. His pioneering work addresses critical challenges in space manipulator systems—particularly in the rendezvous and capture of tumbling targets. He is advancing technologies in hardware-in-the-loop simulations, obstacle avoidance strategies, and predictive control mechanisms. Dr. Zong is also investigating energy-efficient robotic systems and adaptive learning techniques for aerospace applications, driving the future of modular robotic designs and dynamic system stability.

PUBLICATION TOP NOTES

  1. 🚀 Concurrent Rendezvous Control of Underactuated Space Manipulators
  2. 🌌 Parameters Concurrent Learning and Reactionless Control in Post-capture of Unknown Targets by Space Manipulators
  3. 🤖 Reactionless Control of Free-floating Space Manipulators
  4. 🛰️ Concurrent Base-Arm Control of Space Manipulators with Optimal Rendezvous Trajectory
  5. 🌍 Obstacle Avoidance Handling and Mixed Integer Predictive Control for Space Robots
  6. 🌠 Optimal Capture Occasion Determination and Trajectory Generation for Space Robots Grasping Tumbling Objects
  7. 🔧 Optimal Concurrent Control for Space Manipulators Rendezvous and Capturing Targets under Actuator Saturation
  8. 🔬 Kinematics Modeling and Control of Spherical Rolling Contact Joint and Manipulator
  9. ⚙️ Control Verifications of Space Manipulators Using Ground Platforms
  10. ✨ Energy Sharing Mechanism for a Freeform Robotic System-Freebot

CONCLUSION

Dr. Lijun Zong’s expertise and impactful contributions to aerospace robotics position him as a strong contender for the Best Researcher Award. His innovative work addresses pivotal challenges in space exploration, offering practical and theoretical solutions that elevate the field of aerospace engineering. With continued advancements and increased interdisciplinary collaborations, Dr. Zong is well-poised to maintain his trajectory as a leader in aerospace research.

Li Ding | Robotics | Best Researcher Award

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Prof. Li Ding | Robotics | Best Researcher Award

Professor, Jiangsu University of Technology, China

Ding Li is an Associate Professor at the College of Mechanical Engineering, Jiangsu University of Technology. With a robust academic background and extensive research experience, he specializes in mechatronic engineering, particularly focusing on robotic systems and control dynamics.

Profile

Scopus

🎓 Education

Ding Li completed his educational journey with a Ph.D. in Mechatronic Engineering from Nanjing University of Aeronautics and Astronautics (2013-2016). Prior to this, he earned a Master’s in Mechanical Engineering from Anhui University of Science and Technology (2011-2013) and a Bachelor’s in Mechanical Manufacturing and Automation from Jiangsu University of Technology (2007-2011).

💼 Experience

Ding has held various academic positions, including:

  • Associate Professor (June 2019 – Present) at Jiangsu University of Technology
  • Associate Professor (November 2021 – August 2022) at the National Natural Science Foundation of China
  • Lecturer (October 2016 – May 2019) at Jiangsu University of Technology
  • Lecturer (March 2018 – March 2019) at Hong Kong Polytechnic University

🔬 Research Interests

Ding’s research interests encompass the dynamics and control of robotic systems, particularly in areas such as cable-driven manipulators, intelligent operating flying robots, and hydraulic systems. His work aims to enhance automation and efficiency in various engineering applications.

🏆 Awards

Ding Li has received several prestigious accolades, including:

  • First Prize for Science and Technology Progress from the China Mechanical Engineering Society (3rd class, 2022)
  • Outstanding Youth Key Teacher Award from Jiangsu University’s “Blue Project” (2022)
  • Changzhou Natural Science Excellence Award (2nd prize, 2019)

📚 Publications Top Notes

Ding Li has contributed significantly to academic literature, with notable publications including:

Optimal Joint Space Control of a Cable-Driven Aerial Manipulator (Computer Modeling in Engineering & Sciences, 2023)

Observer-Based Control for a Cable-Driven Aerial Manipulator under Lumped Disturbances (CMES – Computer Modeling in Engineering & Sciences, 2023)

Adaptive Robust Control via a Nonlinear Disturbance Observer for Cable-driven Aerial Manipulators (International Journal of Control, Automation and Systems, 2023)

Francisco J. G. Silva – Robotics – Excellence in Research

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Francisco J. G. Silva - Robotics - Excellence in Research

Polytechnic Institute of Porto - Portugal

AUTHOR PROFILE

SCOPUS

🎓 ACADEMIC AND PROFESSIONAL EDUCATION

Francisco J. G. Silva is a Mechanical Engineer with extensive qualifications, including Habilitation, PhD, MSc, and BSc degrees. His educational background is complemented by a substantial career in both academic teaching and industrial research, bridging the gap between scientific knowledge and practical application.

🏛️ UNIVERSITY TEACHING AND ADMINISTRATION

Silva has served as an Associate Professor with Habilitation at ISEP – School of Engineering, Polytechnic of Porto (IPP), where he has been instrumental in shaping the mechanical engineering curriculum and directing the master’s degree program. He has also held significant administrative roles, including Director of the BSc Degree in Mechanical Engineering at ESEIG and Sub-Director of the Mechanical Engineering Department at ISEP.

📚 RESEARCH AND PUBLICATIONS

With over 300 papers published in prestigious journals such as ELSEVIER, SPRINGER, and MDPI, Silva's research encompasses a broad spectrum of topics within Mechanical Engineering, Materials Science, and Industrial Engineering. His work has significantly contributed to advancements in advanced manufacturing processes, materials characterization, and additive manufacturing.

📝 BOOKS AND EDITORIAL WORK

Silva is a prolific author and editor, having published 16 books, including three written in 2023. He has contributed to numerous special issues as a Guest Editor for renowned journals, showcasing his expertise in various fields. His role as founder of the Journal of Coating Science and Technology further highlights his impact on the scientific community.

🌐 CONFERENCE LEADERSHIP AND COMMITTEES

He has been an active participant and leader in the international conference circuit, serving as General Chair of FAIM 2023 and a member of several scientific committees for conferences across the globe. His involvement in these conferences underscores his commitment to advancing the field through collaborative and innovative research.

🏆 RECOGNITIONS AND AWARDS

Silva’s contributions to the field have been recognized with multiple accolades, including the Top Reviewer Awards from Publons and MDPI. He has also received Best Paper Awards and other honors, reflecting his esteemed position in the academic and research community.

🚀 CURRENT PROJECTS AND FUTURE INITIATIVES

Currently, Silva is leading the DRIVOLUTION project at ISEP, a research initiative focused on advanced manufacturing technologies, with a funding of 1.5 million euros. His ongoing projects and research efforts continue to drive advancements in mechanical engineering and materials science, contributing to both academic and industrial advancements.

NOTABLE PUBLICATION

Calcium phosphate–calcium titanate composite coatings for orthopedic applications
Authors: J.E. Arce, A.E. Arce, Y. Aguilar, L. Yate, S. Moya, C. Rincón, O. Gutiérrez
Year: 2016
Journal: Ceramics International

Production and characterization of aluminum powder derived from mechanical saw chips and its processing through powder metallurgy
Authors: A.E.A.L.M. Rojas-Díaz, L.E. Verano-Jiménez, E. Muñoz-García, J. Esguerra-Arce
Year: 2019
Journal: Powder Technology

The evolution of the microstructure and properties of ageable Al-Si-Zn-Mg alloy during the recycling of milling chips through powder metallurgy
Authors: P.A. Pulido-Suárez, K.S. Uñate-González, J.G. Tirado-González, J. Esguerra-Arce
Year: 2020
Journal: Journal of Materials Research and Technology

Influence of the Al content on the in vitro bioactivity and biocompatibility of PVD Ti1−xAlxN coatings for orthopedic applications
Authors: A. Esguerra-Arce, J. Esguerra-Arce, L. Yate, C. Amaya, L.E. Coy, Y. Aguilar, et al.
Year: 2016
Journal: RSC Advances

Morteros geopolimericos reforzados con fibras de carbono basados en un sistema binario de un subproducto industrial
Authors: S. Bernal, J. Esguerra, J. Galindo, R.M. de Gutiérrez, E. Rodríguez, et al.
Year: 2009
Journal: Revista Latinoamericana de Metalurgia y Materiales