Muhammad Tahir Naseem | Electronic Engineering | Best Research Article Award

Published on by Academic Achievements

Dr. Muhammad Tahir Naseem | Electronic Engineering | Best Research Article Award

Dr. Muhammad Tahir Naseem | Electronic Engineering | Research Professor at Yeungnam University | South Korea

Dr. Muhammad Tahir Naseem is a leading academic and researcher in the field of computer science, with a specialization in artificial intelligence, computer vision, and image processing. His work is recognized internationally for contributing to cutting-edge solutions in medical diagnostics, intelligent systems, and secure image communication. As a faculty member at Yeungnam University, Dr. Muhammad Tahir Naseem continues to advance knowledge through interdisciplinary research, impactful publications, and academic mentorship. With a strong foundation in theoretical and applied domains, he has consistently demonstrated excellence across various research activities and collaborative networks. His reputation for precision, innovation, and scholarly engagement reflects his commitment to both scientific inquiry and societal benefit.

Academic Profile:

Google Scholar

Education:

Dr. Muhammad Tahir Naseem completed his doctoral studies in Electrical and Computer Engineering, focusing on intelligent diagnostic systems and secure signal processing methodologies. His academic journey has been rooted in analytical depth and interdisciplinary orientation, combining core principles of artificial intelligence with real-world applications in healthcare technologies and multimedia systems. Prior to his doctoral research, he obtained strong foundational training in computing and electronics, equipping him with the technical competencies needed to work across a wide range of academic and industrial projects. His educational background laid the groundwork for a successful research career, which has since evolved through both theoretical development and experimental validations.

Experience:

Dr. Muhammad Tahir Naseem possesses extensive teaching and research experience in both national and international institutions. He has held academic roles that involve supervising graduate-level research, delivering specialized courses, and coordinating collaborative initiatives across departments and research labs. He has worked closely with multidisciplinary teams to execute research projects involving medical imaging, wireless communication, and intelligent systems. Dr. Muhammad Tahir Naseem’s academic service also includes peer reviewing for indexed journals and contributing to scientific program committees for international conferences. His experience has enabled him to develop and guide solutions that integrate AI models with practical outcomes in healthcare, communication systems, and data security.

Research Interest:

Dr. Muhammad Tahir Naseem’s primary research interests span artificial intelligence, computer vision, signal and image processing, and intelligent diagnosis. His current focus is on applying deep learning models to medical imaging for disease detection and prognosis, particularly in the areas of histopathology and pathological gait analysis. He is also exploring advancements in resource allocation for wireless communication systems using neural networks and fuzzy logic. Another area of interest includes secure image watermarking and digital authentication techniques using chaos theory and residue number systems. His interdisciplinary research is aimed at improving real-time diagnostic capabilities, data integrity, and resource efficiency in complex systems.

Award:

Dr. Muhammad Tahir Naseem has been consistently recognized for his academic excellence and research contributions in the field of intelligent systems. His work in medical image analysis and adaptive communication networks has earned appreciation from peers and international collaborators. He has been nominated for awards that acknowledge high-impact research, publication quality, and innovation in computing technologies. His leadership in collaborative projects and dedication to solving real-world problems through AI-driven solutions positions him as a strong candidate for academic and research-based honors. His research outputs not only contribute to academic knowledge but also deliver tangible benefits to healthcare and digital communication systems.

Selected Publications:

  • “Malignancy detection in lung and colon histopathology images using transfer learning with class selective image processing” – Published in 2022, with 241 citations

  • “Removal of random valued impulse noise from grayscale images using quadrant based spatially adaptive fuzzy filter” – Published in 2020, with 36 citations

  • “Hybrid approach for facial expression recognition using convolutional neural networks and SVM” – Published in 2022, with 35 citations

  • “Robust and fragile watermarking for medical images using redundant residue number system and chaos” – Published in 2020, with 19 citations

Conclusion:

Dr. Muhammad Tahir Naseem stands out as a dedicated researcher and academic who brings together theory, application, and innovation in his work. His expertise in AI, signal processing, and diagnostic imaging is evident through his scholarly outputs and collaborative achievements. Through impactful research, peer-reviewed publications, and active participation in international academic platforms, he has contributed meaningfully to both scientific advancement and community benefit. Dr. Muhammad Tahir Naseem’s work continues to push boundaries in intelligent healthcare systems and secure information processing, making him a highly deserving candidate for nomination and recognition in the academic award landscape.

 

 

Yi Liu | Robot Manipulators | Best Researcher Award

Published on by Academic Achievements

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.

Profile Verified:

ORCID 

Scopus

🎓 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.