Dr. XueHua Zhao | Automation | Best Researcher Award

Student, Northwestern Polytechnical University, China.

Dr. XueHua Zhao 🎓 is a dedicated Chinese researcher specializing in advanced filtering algorithms, sensor networks, and non-Gaussian noise modeling. With a strong mathematical foundation and a focus on artificial intelligence in navigation systems, Dr. Zhao has published several impactful research papers in top-tier international journals and conferences. Currently pursuing a Ph.D. in Computer Science and Technology at Northwestern Polytechnical University, her contributions to maximum correntropy filtering and its distributed applications are widely recognized across the control engineering community 🌐.

Publication Profile

Scopus

📘 Education Background

Dr. Zhao began her academic journey with a Bachelor’s degree in Mathematics Education from Henan Normal University (1998–2002) 🧮. She then pursued a Master’s degree in Computational Mathematics at Guizhou Normal University (2004–2006) 📊. Continuing her academic advancement, she embarked on doctoral research in Computer Science and Technology at Northwestern Polytechnical University from 2016 onwards 🖥️, focusing on advanced estimation and filtering techniques.

💼 Professional Experience

With a foundation in mathematics and applied computing, Dr. Zhao has actively contributed to the scientific community through collaborative projects in signal processing and navigation systems 🚀. She has co-authored papers with experts in both academic and industrial research groups, focusing on algorithms like the Unscented Particle Filter and Sparrow Search Algorithm, highlighting her interdisciplinary approach and engineering insight 🤝.

🏅 Awards and Honors

While specific individual awards have not been explicitly mentioned, Dr. Zhao’s selection as a lead author in several high-impact journals and IEEE conferences reflects peer recognition and commendation from the academic community 🌟. Her work has drawn citations from related research in robust control, navigation systems, and sensor networks 🏆.

🔬 Research Focus

Dr. Zhao’s research interests lie at the intersection of control engineering and computational intelligence 🧠. She focuses on robust estimation methods like the Maximum Correntropy Kalman Filter (MCKF), Rational-Quadratic Kernels, and Particle Filtering under non-Gaussian and censored environments. Her work is crucial in advancing INS/GPS integrated navigation, distributed sensor fusion, and optimization algorithms for real-world uncertainty modeling and adaptive control systems 🔍.

🔚 Conclusion

Dr. XueHua Zhao continues to make meaningful contributions to control theory and intelligent filtering under uncertainty. Her deep mathematical insight, algorithmic innovation, and collaborative research spirit position her as a valuable contributor to global advancements in nonlinear filtering and smart navigation technologies 🌐📈.

📚 Publication Top Notes:

Stochastic Stability of the Improved Maximum Correntropy Kalman Filter against Non-Gaussian Noises, International Journal of Control, Automation and Systems, 2024, 22(3): 731–743.
Cited by: 6 articles
Rational-Quadratic Kernel-Based Maximum Correntropy Kalman Filter for the Non-Gaussian Noises, Journal of the Franklin Institute, 2024, 361(17): 107286.
Cited by: 4 articles
Distributed Maximum Correntropy Linear Filter Based on Rational-Quadratic-kernel against Non-Gaussian Noise, Symmetry, 2025 (in press).
Cited by: Awaiting citation
A Fading Factor Unscented Particle Filter and Its Application in INS/GPS Integrated Navigation, ICISCE 2017 Proceedings, IEEE, 2017: 792–796.
Cited by: 19 articles
Adaptive Robust Unscented Particle Filter and Its Application in Sins/Sar Integration Navigation System, IAEAC 2017 Proceedings, IEEE, 2017: 2364–2368.
Cited by: 21 articles
Enhanced Sparrow Search Algorithm Based on Improved Game Predatory Mechanism and Its Application, Digital Signal Processing, 2024, 145: 104310.
Cited by: 5 articles
Linear and Nonlinear Filters Based on Statistical Similarity Measure for Sensor Network Systems, Journal of the Franklin Institute, 2025, 362(1): 107412.
Cited by: Awaiting citation
Random weighted adaptive filtering and its application in integrated navigation , Journal of Projectiles, Rockets, Missiles and Guidance , 2017 , 37(05): 1–5+10.
Cited by: 12 articles

Mr. Ilias Chouridis | Automation | Best Researcher Award

Mechanical Engineer, International Hellenic University, Greece

Ilias Chouridis is a passionate researcher in robotics and mechatronics, currently pursuing his Ph.D. at the International Hellenic University in Thessaloniki, Greece. 🎓 His academic journey began with a diploma in Mechanical Engineering from the Polytechnic School of Aristotle University of Thessaloniki. With a keen interest in bio-inspired optimization methods and evolutionary algorithms, he focuses on enhancing unmanned aerial vehicle (UAV) path planning. 🚀 His expertise in cutting-edge robotic systems has positioned him as an emerging figure in the field of intelligent navigation and optimization.

🎓 Education

Ilias Chouridis obtained his diploma in Mechanical Engineering from the prestigious Polytechnic School of Aristotle University of Thessaloniki. Currently, he is advancing his academic career by pursuing a Ph.D. in Robotics and Mechatronics Systems Navigation at the International Hellenic University, where his research delves into innovative algorithms for UAV path planning. 📡

💼 Experience

As a researcher at the International Hellenic University, Thessaloniki, Ilias Chouridis has actively contributed to the development of advanced robotic navigation systems. 🤖 His work primarily focuses on optimization techniques for three-dimensional path planning, integrating artificial intelligence into robotic applications. Additionally, he has peer-reviewed research in Engineering Applications of Artificial Intelligence, further demonstrating his expertise in the field.

🔬 Research Focus

Ilias Chouridis’ research centers on bio-inspired optimization techniques and evolutionary algorithms, particularly for UAV path planning. 🌍 His studies involve enhancing robotic system efficiency through hybrid artificial intelligence methodologies, ensuring optimal and precise navigation in complex environments. His innovative approach aims to reduce path length and improve the adaptability of autonomous systems in real-world applications.

🔍 Conclusion

Ilias Chouridis is an emerging scholar in robotics and artificial intelligence, with a strong focus on optimization and UAV navigation. His contributions to three-dimensional path planning are shaping the future of autonomous robotic systems. 🌟 His dedication to AI-driven navigation systems ensures that his work will continue to influence robotics research and technological advancements.

📚 Publications

Enhanced Hybrid Artificial Fish Swarm Algorithm for Three-Dimensional Path Planning Applied to Robotic Systems – Robotics, 2025
📄 DOI: 10.3390/robotics14030032

Cited by: 1 article

Three-Dimensional Path Planning Optimization for Length Reduction of Optimal Path Applied to Robotic Systems – Robotics, 2024
📄 DOI: 10.3390/robotics13120178