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.