Yi Liu | Robot Manipulators | Best Researcher Award

Prof. Dr. Yi Liu | Robot Manipulators | Best Researcher Award

Prof. Dr. Yi Liu | Robot Manipulators – Dalian Maritime University, China

Yi Liu is a dedicated and innovative researcher in the fields of robotics, marine systems, and intelligent control strategies. With a strong foundation in engineering and systems theory, Liu has carved out a niche in designing robust, adaptive, and fault-tolerant control methods for autonomous vehicles and intelligent machines. His scholarly output demonstrates a blend of theoretical depth and applied problem-solving, especially in marine autonomy and neural network stability. He collaborates internationally, contributing to high-impact publications that advance both academia and industry.

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🎓 Education:

Yi Liu pursued a rigorous academic path grounded in automation, systems engineering, and control theory. Throughout his academic career, he focused on the development of control algorithms, fuzzy logic, nonlinear systems, and real-time optimization. This educational background laid a strong foundation for his contributions to autonomous system control and intelligent robotics. His formal training sharpened his expertise in dynamic systems modeling, multi-agent systems, and advanced computational methods, which are integral to his research success.

💼 Experience:

With several years of experience in academic and collaborative research environments, Liu has worked across a variety of interdisciplinary projects involving underwater vehicles, mobile robotics, and adaptive control systems. He has been instrumental in leading or contributing to research projects involving fault diagnosis, autonomous trajectory tracking, event-triggered control, and predictive modeling. Liu has collaborated extensively with both domestic and international scholars, enhancing his versatility in addressing real-world engineering challenges using theoretical tools.

🔬 Research Interest:

Yi Liu’s research interests focus on robust and intelligent control systems, particularly in the context of underactuated Autonomous Underwater Vehicles (AUVs), delayed neural networks, robotic path planning, and nonlinear system optimization. He specializes in fault-tolerant mechanisms, adaptive fuzzy logic control, distributed control systems, and trajectory tracking under real-world constraints like actuator faults and input saturation. Liu is passionate about bridging AI-driven control strategies with marine engineering to improve system efficiency, safety, and autonomy.

🏆 Award:

Although Yi Liu has not yet received a major global award, his track record of high-quality research and consistent contributions to leading journals positions him as a strong candidate for the Best Researcher Award. His scholarly reputation, collaborative output, and citation impact speak volumes about the relevance and rigor of his work. His eligibility for this recognition is bolstered by the interdisciplinary nature and real-world applicability of his research across robotics, control systems, and marine technologies.

📚 Publications:

Below are seven notable publications by Yi Liu with emojis, publication year, journal, and a one-line citation prompt:

  1. 🧠 “Finite-time stability and anti-disturbance synchronization for switched delayed neural networks using a ranged dwell time switching strategy”Information Sciences, 2025
    📌 Cited by 12+ articles — introduces ranged dwell time strategies for neural synchronization.
  2. 🌊 “Distributed data-driven 3D optimal formation control for underactuated AUVs” – Ocean Engineering, 2025
    📌 Cited by 15+ — proposes control for marine vehicles under saturation and unknown dynamics.
  3. 🚢 “Fuzzy Optimal Fault-Tolerant Trajectory Tracking for AUVs in 3-D Space” – IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2025
    📌 Cited by 18+ — combines fuzzy control with fault tolerance for marine systems.
  4. 🤖 “Efficient Exploration of Mobile Robot Based on DL-RRT and AP-BO” – IEEE Transactions on Instrumentation and Measurement, 2024
    📌 Cited by 20+ — integrates deep learning with real-time path planning.
  5. 🔁 “Fuzzy Adaptive Fault-Tolerant Control with Input Saturation for AUVs” – Ocean Engineering, 2024
    📌 Cited by 10+ — enhances underwater vehicle control under input limits.
  6. 🧩 “Robust Optimal Tracking for Underactuated AUVs in 3D Space” – International Journal of Robust and Nonlinear Control, 2024
    📌 Cited by 13+ — addresses position and velocity constraints robustly.
  7. 🛠️ “3D Laser-Guided Robotic Cutting of Porcine Belly” – IEEE/ASME Transactions on Mechatronics, 2022
    📌 Cited by 25+ — applies automation in bio-mechanical processing.

🔚 Conclusion:

Yi Liu’s body of work is a testament to his passion for impactful and intelligent engineering solutions. His deep knowledge of adaptive control systems, robust design, and fault mitigation strategies positions him at the forefront of next-generation autonomous technologies. Through consistent publication in high-impact journals and growing citation metrics, he has built a strong case for recognition. His work is not only theoretically robust but also industrially applicable, making him a deserving candidate for the Best Researcher Award. With continued dedication and collaborative energy, Yi Liu is poised to make even greater contributions to the fields of intelligent systems, robotics, and marine engineering.

 

 

 

 

Ahmed Ghazi BLAIECH | Artificial intelligence | Best Researcher Award

Mr. Ahmed Ghazi BLAIECH | Artificial intelligence | Best Researcher Award

Mr. Ahmed Ghazi BLAIECH | Artificial intelligence-Associate professor at Higher Institute of Applied Sciences and Technology of Sousse, Tunisia

Ahmed Ghazi Blaiech is a distinguished academic and researcher in the field of computer science, currently serving as an Assistant Professor at the High Institute of Applied Sciences and Technology of Sousse (ISSATSo), University of Sousse. With extensive experience in artificial intelligence, machine learning, and real-time computing, he has made significant contributions to the development of innovative deep learning models and neural networks. His research focuses on medical imaging, embedded systems, and FPGA-based accelerators. Over the years, he has been instrumental in fostering cutting-edge technological advancements through both research and academic mentoring.

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Orcid | Scopus | Google Scholar

Education:

Ahmed Ghazi Blaiech has an extensive academic background in computer science and informatics systems. He obtained his Habilitation thesis in Engineering of Informatics Systems from the National Engineering School of Sfax (ENIS) in 2022. Prior to that, he earned his PhD in Engineering of Informatics Systems in 2015 from the same institution, graduating with first-class honors. He also holds a Master’s degree in Safety and Security of Industrial Systems with a specialization in Real-Time Computer Science from the High Institute of Applied Sciences and Technology of Sousse. His foundational academic journey began with a Licence degree in Computer Science from the same institute in 2006.

Experience:

Dr. Blaiech has accumulated over a decade of teaching and research experience in academia. Since 2017, he has been an Assistant Professor at ISSATSo, contributing to various undergraduate and postgraduate courses. Before this, he served as an Assistant in Computer Science at ISSATSo (2016-2017) and at the High Institute of Computer Science and Multimedia of Gabes, University of Gabes (2011-2015). He also worked as a contractual assistant at the Faculty of Sciences of Monastir, University of Monastir (2008-2011). In addition to his teaching roles, he has actively led numerous research initiatives and coordinated academic programs.

Research Interests:

Dr. Blaiech’s research interests span multiple domains within artificial intelligence, machine learning, and real-time computing. His work is particularly focused on deep learning applications in medical imaging, embedded systems, and hardware-accelerated computing using FPGA-based architectures. He has also contributed to the advancement of intelligent pervasive systems and neural networks for real-time applications. His research outputs have been widely recognized in high-impact journals, showcasing innovative methodologies in biomedical signal processing, image synthesis, and classification techniques.

Awards and Recognitions:

Throughout his career, Dr. Blaiech has received several accolades for his contributions to the field of computer science. He holds multiple prestigious certifications, including the Huawei Certified ICT Associate (HCIA) in Artificial Intelligence and the Microsoft Technology Associate (MTA) for Python programming. He has also been recognized for his mentorship and coaching in AI-related competitions, playing a crucial role in fostering innovation among students and researchers.

Publications:

Dr. Blaiech has authored numerous research papers in high-impact journals, contributing to advancements in artificial intelligence and medical imaging. Some of his notable publications include:

📌 “CNN-based classification of epileptic states for seizure prediction using combined temporal and spectral features” – Biomedical Signal Processing and Control, 2022. DOI 📖
📌 “An innovative medical image synthesis based on dual GAN deep neural networks for improved segmentation quality” – Applied Intelligence, 2022. DOI 📖
📌 “Comparison by multivariate auto-regressive method of epileptic seizures prediction for real patients and virtual patients” – Biomedical Signal Processing and Control, 2021. DOI 📖
📌 “Innovative deep learning models for EEG-based vigilance detection” – Neural Computing and Applications, 2020. DOI 📖
📌 “A Novel Hardware Systolic Architecture of a Self-Organizing Map Neural Network” – Computational Intelligence and Neuroscience, 2019. DOI 📖
📌 “A New Hardware Architecture for Self-Organizing Map Used for Colour Vector Quantization” – Journal of Circuits, Systems, and Computers, 2019. DOI 📖
📌 “A Survey and Taxonomy of FPGA-based Deep Learning Accelerators” – Journal of Systems Architecture, 2019. DOI 📖

Conclusion:

Dr. Ahmed Ghazi Blaiech’s contributions to the field of artificial intelligence and medical computing have been impactful in both research and academia. His dedication to technological innovation, particularly in neural networks and real-time computing, has positioned him as a leader in the domain. His extensive research output, coupled with his teaching and mentoring experience, underscores his significant role in advancing knowledge and fostering the next generation of AI researchers. Through his work, he continues to drive progress in medical imaging, deep learning applications, and FPGA-based architectures, making a lasting impact in his field.

Shashank Pasupuleti | Robotics | Best Researcher Award

Mr. Shashank Pasupuleti | Robotics | Best Researcher Award

Mr. Shashank Pasupuleti | Robotics – Senior Product and Systems Engineer at Capgemini Engineering, United States

Shashank Pasupuleti is an accomplished Mechanical Systems Engineer with significant contributions to the medical device and robotics industries. With a robust background in system design, validation, and risk analysis, Shashank has demonstrated expertise in bridging engineering innovation with industry compliance. His proficiency in model-based systems engineering (MBSE) and various engineering tools has propelled advancements in product development, especially in robotic surgical platforms. Over the years, his contributions have positively influenced patient care through innovative technologies.

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ORCID | Google Scholar

Education

Shashank holds a Master’s degree in Mechanical Systems from the University of North Texas and a Master of Science in Project Management from the University of the Cumberlands. His academic journey began with a Bachelor’s degree in Mechanical Engineering from Jawaharlal Nehru Technological University. These academic achievements laid the foundation for his expertise in mechanical design, project management, and system engineering methodologies.

Experience

Shashank has over seven years of progressive experience in leading-edge projects across globally recognized organizations. As a Senior Product and Systems Engineer at Capgemini Engineering, he spearheaded the development of system engineering models for risk management, system architecture, and validation processes, enhancing project quality and efficiency. His tenure at THINK Surgical as a Senior System Engineer saw him develop TMINI, a miniature surgical robotic platform, significantly improving precision in total knee replacement surgeries. Additionally, at Auris Health Inc. (Johnson & Johnson), Shashank contributed to the development of the Monarch robotic platform, optimizing testing strategies and supporting regulatory approvals. His early career roles at Fresenius Medical Care and GE Healthcare honed his expertise in verification and validation (V&V) strategies and compliance with FDA and ISO standards.

Research Interests

Shashank’s research interests lie at the intersection of robotics, medical devices, and MBSE. He focuses on advancing system integration techniques and enhancing reliability in medical devices. His dedication to innovation in healthcare robotics is evident in his work on surgical platforms, usability studies, and cybersecurity strategies for regulatory compliance. Shashank also actively explores how digital continuity and data-driven design can transform medical device development, making healthcare safer and more effective.

Awards

Shashank has been consistently recognized for his technical acumen and leadership in engineering projects. He was an integral part of teams that achieved successful 510(k) FDA approvals for medical devices such as the Monarch Bronchoscopy System and TMINI robotic platform. His technical presentations, including his work on MBSE advancements at the INCOSE IS 2023 conference, underscore his role as a thought leader in his domain. His contributions have not only driven innovation but also positioned him as a prominent figure in the medical robotics field.

Publications

“Advanced Sensor Technologies in Autonomous Robots: Improving Real-time Decision Making and Environmental Interaction” – Published in International Journal of Innovative Research and Creative Technology, December 2024. Part of ISSN: 2454-5988. 🌐
Cited by: Articles in progress.
“Elevating Systems Engineering Through Digital Transformation for Interconnected Systems” – Published in International Journal of Leading Research Publication, December 2024. Part of ISSN: 2582-8010. 🔗
Cited by: Articles in progress.
“Engineering the Future: Mastering Systems Design and Resilience” – Published by Eliva Press, November 2024. ISBN: 978-99993-2-174-7. 📚
Cited by: Not available.
“Model-Based Systems Engineering (MBSE) in Medical Device Development: Enhancing Efficiency and Quality” – Presented at INCOSE Symposium 2023, July 2023. 🤖
Cited by: Research in progress.
“The Integration of Robotic Systems in Healthcare Infrastructure: Challenges and Solutions” – Published in Scientific Research and Community, April 29, 2022. Part of ISSN: 2755-9866. 🩺
Cited by: 14 articles.
“System Integration Failures and Their Impact on Patient Safety in Critical Care Settings” – Published in International Journal of Scientific Research in Engineering and Management (IJSREM), October 2021. Part of ISSN: 2582-3930. 🛠️
Cited by: 10 articles.
“The Role of Robotic Systems in Minimally Invasive Surgery: Benefits, Risks, and Future Directions” – Published in International Journal of Scientific Research in Engineering and Management (IJSREM), March 2021. Part of ISSN: 2582-3930. 🦾
Cited by: 18 articles.

Conclusion

Shashank Pasupuleti embodies excellence in engineering, with a career that bridges cutting-edge technology and real-world medical applications. His dedication to advancing healthcare robotics and medical device engineering has led to significant industry contributions, including successful FDA approvals and innovative system designs. With a strong focus on research, leadership, and compliance, Shashank continues to push the boundaries of what is possible in the realm of medical technology. His expertise and achievements make him a deserving candidate for the Best Researcher Award, reflecting his impact on the field and the broader community.