Dr. XueHua Zhao | Automation | Best Researcher Award

Posted on by Computer Scientists Awards

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:

  1. 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

  2. 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

  3. Distributed Maximum Correntropy Linear Filter Based on Rational-Quadratic-kernel against Non-Gaussian Noise, Symmetry, 2025 (in press).
    Cited by: Awaiting citation

  4. 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

  5. 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

  6. Enhanced Sparrow Search Algorithm Based on Improved Game Predatory Mechanism and Its Application, Digital Signal Processing, 2024, 145: 104310.
    Cited by: 5 articles

  7. 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

  8. 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

 

Dr. Lorenz Granrath | Production Technology | Best Researcher Award

Posted on by Computer Scientists Awards

Dr. Lorenz Granrath | Production Technology | Best Researcher Award

Japan Representative , Fraunhofer ICNAP, Japan

Dr. Lorenz Granrath  is a German-born expert in EU-Japan science-industry collaboration, with over 25 years of dedicated work in advanced technology sectors including AI, digital transformation (DX), environmental technology, and renewable energy. Based in Tokyo, Japan, he has held prominent roles such as Professor, Senior Advisor, and Representative in numerous German-Japanese institutional partnerships. He has successfully initiated and led international research projects, founded labs, advised companies, and lectured at leading universities including Waseda University. He is married to Megumi Ishigami and has one daughter.

Publication Profile

Summary of Suitability for Best Research Award – Dr. Lorenz Granrath

Dr. Lorenz Granrath exemplifies an outstanding candidate for the Best Research Award due to his extensive and impactful career in international science-industry collaboration, particularly between the EU and Japan. With over 25 years of strategic involvement in AI, digital transformation (DX), renewable energy, and advanced industrial technologies, he has played a crucial role in bridging academia, government bodies, and industry stakeholders. His leadership in securing funding, initiating R&D centers, establishing major cross-national collaborations (such as between AIST and DFKI), and launching cutting-edge projects like e-VITA, underscores his long-standing commitment to advancing global research agendas.

🎓 Education Background

Dr. Granrath earned his Doctorate in Economics (Dr. oec.) from the University of St. Gallen, Switzerland (1990–1994), where his thesis explored the protection and exchange of technologies between Japanese and Western firms. He also studied as a Visiting Researcher at The University of Tokyo (1992–1993). He holds a diploma in Industrial Engineering (Wirtschaftsingenieurwesen) from the University of Karlsruhe (KIT), Germany, and completed his secondary education at Schloßschule Kirchberg/Jagst in 1981.

💼 Professional Experience

Dr. Granrath currently serves as the Representative at Fraunhofer-ICNAP since November 2024 and at the Institute for Experimental Psychophysiology (IXP) since June 2022, focusing on networked adaptive production and psychophysiological emotion detection. He is an advisor to multiple organizations, including ENV Science Trading and Kienbaum Japan, and has been a Visiting Lecturer at Waseda University since 2013. Notably, he served as Project Assistant Professor at Tohoku University (2021–2022) and held a key position as Supervisory Innovation Coordinator at AIST (2014–2021), where he led international AI and energy collaborations. Earlier roles include Fraunhofer Chief Representative Japan (2001–2013), Liaison Officer at GMD (1997–2001), and Project Manager at ABB STOTZ KONTAKT GmbH (1995–1997), underscoring his deep engagement in research and industrial application across continents.

🏅 Awards and Honors

Dr. Granrath’s contributions to EU-Japan collaboration have been recognized through his leadership roles in landmark projects and his success in securing multimillion-euro research contracts. He has been instrumental in initiating major projects such as e-VITA and CrossCDR, establishing international workshops, and founding research labs. His membership in prominent organizations like the Science & Technology Diplomatic Circle, DJW, JSAI, and the JSPS Alumni reflects his standing in the academic and industrial community.

🔬 Research Focus

His interdisciplinary research spans artificial intelligence, digital twins, circular economy, smart aging, and human-centric computing. He has played a vital role in developing technologies for healthy aging, environmental sustainability, and advanced manufacturing. Dr. Granrath’s involvement in projects like e-VITA and initiatives in digital transformation highlight his commitment to bridging societal needs with cutting-edge scientific innovation, especially within the EU-Japan cooperative framework.

📚 Top Publications with Notes

  1. RE-HAK: A Novel Refurbish-to-Host Solution Using AI-Driven Blockchain to Advance Circular Economy and Revitalize Japan’s Akiyas
    🔹 Buildings (2025)

  2. Designing a circular cities declaration for Japan building on the European Union’s case study
    🔹 Journal of Environmental Management (2024)
    🔹 Cited by: 5 articles

  3. Digital Twins for Supporting Ageing Well: Approaches in Current Research and Innovation in Europe and Japan
    🔹 Sustainability (2024)
    🔹 Cited by: 6 articles

  4. The rising phenomenon of circular cities in Japan: Case studies of Kamikatsu, Osaki and Kitakyushu
    🔹 Science of The Total Environment (2023)
    🔹 Cited by: 12 articles

  5. Circular economy and zero-carbon strategies between Japan and South Korea: A comparative study
    🔹 Science of The Total Environment (2022)
    🔹 Cited by: 18 articles

  6. Social Capital Mediates the Association between the ICT Usage and Well-Being of Older People in Japan
    🔹 Sustainability (2022)
    🔹 Cited by: 15 articles

  7. EU-Japan Project e-VITA in Society 5.0: the “Digital Twin for Smart Aging”
    🔹 LinkedIn Newsletter Article (2022)

 

Wenwei Luo | Automation | Best Researcher Award

Posted on by Computer Scientists Awards

Mr. Wenwei Luo | Automation | Best Researcher Award

Mr. Wenwei Luo at Institute of Logistics Science and Engineering, Shanghai Maritime University, China

Wenwei Luo is a passionate robotics researcher pursuing his Master’s degree at Shanghai Maritime University, specializing in control science and engineering. With a strong foundation in robotics engineering from Zhejiang Normal University, he has demonstrated academic excellence, technical proficiency, and innovative thinking in reinforcement learning and evolutionary robotics. Wenwei has published impactful research, led interdisciplinary projects, and earned recognition in national competitions. He possesses a unique combination of embedded systems expertise and AI-based control strategies, positioning him as a rising talent in intelligent robotics. His vision is to bridge adaptive learning and real-world robotics for autonomous systems. 🤖📚🔍

Publication Profile

Orcid

Academic Background

Wenwei Luo is currently pursuing a Master’s degree in Control Science and Engineering at Shanghai Maritime University under Associate Professor Bo Li, with a GPA of 3.84/4.0 and double First Academic Scholarships. His research interests span reinforcement learning, adaptive control, and evolutionary robotics. Previously, he earned his Bachelor’s degree in Robotics Engineering from Zhejiang Normal University under Associate Professor Hu Lan, graduating with a GPA of 3.40/4.0 and receiving a Third Academic Scholarship. Wenwei’s academic background blends strong theoretical knowledge with hands-on experience in intelligent systems and control engineering. 🧠🎓📈

Professional Experience

Wenwei has led and contributed to various high-impact robotics projects. As Principal Investigator, he developed a novel inner-outer loop framework for modular robots using reinforcement learning and evolutionary optimization. As Co-Investigator, he worked on intelligent drone navigation and pursuit-evasion for port defense. He also led a RoboMaster project, designing embedded software for a wheeled robot with Mecanum wheels and a shooting mechanism. His work integrates control algorithms, real-time systems, and AI-based decision-making, validated through both simulations and real-world experiments. His diverse project roles highlight both leadership and deep technical acumen. 🤖🧪🧑‍🔬

Awards and Honors

Wenwei has received several prestigious awards and honors throughout his academic career. At Shanghai Maritime University, he won the Third Prize in the 2022 “Huawei Cup” China Post-Graduate Mathematical Contest in Modeling. During his undergraduate years, he received the National Third Prize in the 2021 National College Students Robotics Competition (RoboMaster Event). He has also been awarded the First Academic Scholarship twice during his master’s program and the Third Academic Scholarship during his bachelor’s. These recognitions reflect his commitment to excellence and contributions to engineering and robotics research. 🥇🎖️📜

Research Focus

Wenwei’s research centers on intelligent control and adaptive robotics, specifically focusing on reinforcement learning-based control, evolutionary robotics, and adaptive dynamic programming. He has pioneered a hierarchical framework integrating genetic algorithms and deep RL (PPO) for optimizing morphology and control of modular robots. His work extends to autonomous UAV path planning and pursuit-evasion strategies using fuzzy logic, neural networks, and Lyapunov-based verification. His research leverages advanced tools such as JAX and GPU parallelism for real-time learning and optimization. Wenwei aims to develop scalable, autonomous systems capable of intelligent behavior in complex environments. 🧠📡🚀

Publication Top Notes

📄  Inner–Outer Loop Intelligent Morphology Optimization and Pursuit–Evasion Control for Space Modular Robot

 📅Year: 2025 | 📚 Journal: Actuators, Volume 14

Conclusion

Wenwei Luo is a highly promising early-career researcher whose academic excellence, innovative research, and practical contributions make him a strong contender for a Best Researcher Award. With a Master’s GPA of 3.84/4.0 and a strong undergraduate foundation, he has demonstrated consistent academic achievement. His research focuses on cutting-edge areas such as modular robotics, reinforcement learning, and evolutionary optimization, exemplified by his novel inner–outer loop architecture combining genetic algorithms and PPO for pursuit–evasion tasks. He has authored peer-reviewed publications, including a journal article in Actuators, and holds a patent alongside software copyrights, reflecting both theoretical and applied innovation. His technical skill set spans AI frameworks, embedded systems, and robotics platforms, and his leadership roles in multiple projects showcase his capability for independent and collaborative research. Combined with national competition awards and scholarships, Luo’s profile embodies the qualities celebrated by the Best Researcher Award.

 

Ms. Zhengrong Xiang | Control Science | Young Scientist Award

Posted on by Computer Scientists Awards

Ms. Zhengrong Xiang | Control Science | Young Scientist Award

Teaching assistant, School of Physics and Information Engineering, Guangxi Science and Technology Normal University, China

Xiang Zhengrong is a dedicated researcher and educator in Control Science and Engineering with expertise in Unmanned Aerial Vehicle (UAV) Systems 🚀. She holds a Master of Engineering degree and currently serves as a full-time teacher at the School of Physics and Information Engineering, Guangxi Science and Technology Normal University 🏫. With a strong background in control theory, automation, and UAV research, she actively contributes to cutting-edge technological advancements. As a member of the Guangxi Automation Society, she is committed to fostering innovation in aerospace control systems and automation technologies.

Publication Profile

🎓 Education

Xiang Zhengrong has a strong academic foundation in engineering and automation. She earned her Master’s degree in Control Science and Engineering 🎓 from Guangxi University of Science and Technology (2019-2022). Before that, she completed her Bachelor’s degree in Electrical Engineering and Automation ⚡ from Chongqing Three Gorges University (2017-2019). Her early technical education began at Chongqing Vocational and Technical College of Industry and Trade (2014-2017), where she specialized in Refrigeration and Air-conditioning Technology ❄️.

💼 Experience

Since July 2022, Xiang Zhengrong has been a full-time faculty member at Guangxi Science and Technology Normal University 📚. She has also served as a visiting teacher at the School of Automation, Guangxi University of Science and Technology 🏛️. With a keen interest in automation and UAV simulation, she has worked on multiple research projects related to UAV flight control, semi-physical simulation systems, and industrial automation technologies 🔬.

🏆 Awards and Honors

Xiang Zhengrong has actively contributed to research and academia, earning recognition for her work. She has secured funding for multiple research projects, including collaborations with Shenzhen Silop Technology Co., Ltd., and has received research grants from the Guangxi Education Science “14th Five-Year Plan” 📜. Her contributions to UAV technology and automation research have been widely recognized within academic and industrial communities 🏅.

🔬 Research Focus

Her primary research interests revolve around Unmanned Aerial Vehicle (UAV) Systems, Control Theory, and Automation ✈️. She specializes in semi-physical simulation systems, flight controller development, and innovative training models for engineering students 🎯. She has also participated in key projects related to electromagnetic interference technologies, capacitive touchscreens, and AI-driven microgrid control systems ⚙️.

🔖 Conclusion

With a passion for engineering and innovation, Xiang Zhengrong continues to push the boundaries of UAV system research and automation 🚀. As a dedicated educator and researcher, she actively contributes to cutting-edge technological advancements and interdisciplinary collaborations. Her scientific publications in reputed journals and research project involvements highlight her commitment to excellence in automation and aerospace control systems 🌍.

📚 Publications

New Generalization and Refinement of the Local Fractional Integral Cauchy–Schwartz Inequality on Fractal Space – Thermal Science, 2025 (In press, SCI Journal)

Hölder Type Inequality for Conformable Fractional Integral and Some Related Results – Thermal Science, 2025 (In press, SCI Journal) 🔗

An improved UWB indoor positioning approach for UAVs based on the dual-anchor model – Sensors, 2025 (In press, SCI Journal) 🔗

Design of DC motor position tracking system based on LQR – Journal of Physics: Conference Series, 2021 🔗

Time Series Generation Adversarial Network Controller Based on Optimal Control of Micro-Grids – 2nd International Conference on Futuristic Technologies (INCOFT), 2023 🔗 [DOI: 10.1109/INCOFT60753.2023.10425311]

Design of hardware-in-the-loop simulation system based on Pixhawk flight control – Journal of Physics: Conference Series, 2021 🔗

Assist. Prof. Dr. Jianhui Wu | System Control | Best Researcher Award

Posted on by Computer Scientists Awards

Assist. Prof. Dr. Jianhui Wu | System Control | Best Researcher Award

Associate Professor, Hunan Institute of Science and Technology, China

Dr. Jianhui Wu is an accomplished Associate Professor at the Hunan Institute of Science and Technology, China. With a strong background in system control, optimization, and visual navigation, he has made significant contributions to the field of autonomous systems. His research focuses on advanced control technologies, particularly in multi-agent systems and obstacle avoidance. As an IEEE member, Dr. Wu actively collaborates with the scientific community, publishing impactful studies in high-ranking journals. His work is widely cited, showcasing his influence in the academic and industrial sectors.

Publication Profile

🎓 Education

Dr. Wu earned his Ph.D. from Changsha University of Science and Technology, China, in 2019. His doctoral research laid the foundation for his expertise in system control, signal processing, and visual navigation. His academic journey has been marked by a deep commitment to solving complex problems in autonomous systems and optimization.

💼 Experience

Currently serving as an Associate Professor, Dr. Wu is affiliated with the School of Information and Communication at Guilin University of Electronic Technology. Over the years, he has led several research projects funded by the Zhuang Autonomous Region, working on cutting-edge control mechanisms for autonomous multi-agent systems. His contributions span both theoretical advancements and practical applications in the fields of artificial intelligence, automation, and transportation optimization.

🏆 Awards and Honors

Dr. Wu’s work has been widely recognized, with multiple grants supporting his research in intelligent systems and control optimization. His research output has earned high citations in SCI-indexed journals, further cementing his reputation as a leading researcher in his domain.

🔬 Research Focus

Dr. Wu’s research primarily revolves around system control and optimization, visual navigation, and signal processing. His groundbreaking studies on multi-agent autonomous systems explore innovative flocking control mechanisms that enhance obstacle avoidance, navigation, and collaborative behaviors. His research has contributed to designing efficient, self-organizing, and adaptive autonomous systems, essential for advancements in robotics and artificial intelligence.

📌 Conclusion

Dr. Jianhui Wu is a dedicated researcher whose contributions to system control and multi-agent coordination continue to shape the future of automation and intelligent transportation. With numerous publications in top-tier journals and significant industry collaborations, his work is paving the way for smarter, more autonomous systems.

📚 Publications 

Fuzzy Flocking Control for Multi-Agents Trapped in Dynamic Equilibrium Under Multiple Obstacles – International Journal of Control, Automation and Systems, 2024 (DOI: 10.1007/s12555-022-0950-6)

Virtual-Leader Split/Rejoin-Based Flocking Control With Obstacle Avoidance for Multi-Agents – International Journal of Control, Automation and Systems, 2024 (DOI: 10.1007/s12555-022-0950-6)

Anonymous Flocking With Obstacle Avoidance via the Position of Obstacle Boundary Point – IEEE Internet of Things Journal, 2024 (DOI: 10.1109/jiot.2024.3465881)

Obstacle Boundary Point and Expected Velocity-Based Flocking of Multiagents with Obstacle Avoidance – International Journal of Intelligent Systems, 2023 (DOI: 10.1155/2023/1493299)

Optimization Scheme of Fine Toll and Bus Departure Quantity for Bottleneck Congestion Management – Complexity, 2021 (DOI: 10.1155/2021/5518502)

Optimization Scheme of Tradable Credits and Bus Departure Quantity for Travelers’ Travel Mode Choice Guidance – Journal of Advanced Transportation, 2020 (DOI: 10.1155/2020/6665161)

Price Regulation Mechanism of Travelers’ Travel Mode Choice in the Driverless Transportation Network – Journal of Advanced Transportation, 2020 (DOI: 10.1155/2020/9191834)

Guidance Optimization of Travelers’ Travel Mode Choice Based on Fuel Tax Rate and Bus Departure Quantity in Two-Mode Transportation System – Journal of Advanced Transportation, 2020 (DOI: 10.1155/2020/4190632)

A Day-to-Day Stochastic Traffic Flow Assignment Model Based on Mixed Regulation – IEEE Access, 2020 (DOI: 10.1109/access.2019.2962864)

Robust Optimization of Sequence Decision in Urban Road Construction – Computer Science, 2018

 

 

Zahid Ullah | Robotics | Best Researcher Award

Posted on by Computer Scientists Awards

Mr. Zahid Ullah | Robotics | Best Researcher Award

PhD Student, Chulalongkorn University, Thailand

Zahid Ullah is a passionate researcher in mechanical and electrical engineering, currently pursuing his Ph.D. in Mechanical Engineering at Chulalongkorn University, Bangkok, Thailand. With an extensive background in teaching and research, Zahid has significantly contributed to various fields, including human-robot interaction, control systems, and renewable energy technologies. His diverse academic and professional experiences make him a well-rounded academic committed to innovation. 🌍🔧

Publication Profile

ORCID

Education:

Zahid Ullah holds a Ph.D. in Mechanical Engineering from Chulalongkorn University (ongoing), an M.Sc. in Electrical Engineering from Abasyn University, Peshawar, Pakistan, and an M.Sc. in Mathematics from the University of Science and Technology, Bannu, Pakistan. He also earned a B.Sc. in Electronics Engineering from the University of Engineering and Technology (UET), Peshawar, Pakistan. 🎓📚

Experience:

Zahid has served as a research assistant and lecturer in various academic institutions in Pakistan, including Abasyn University, Sarhad University of Science and Information Technology, and the Government Polytechnic Institute, Mardan. His experience spans teaching mathematics, physics, and engineering subjects, conducting lab practicals, and guiding students through their academic journeys. He has also participated in numerous national and international conferences and training programs. 🧑‍🏫🔬

Research Focus:

Zahid’s research interests lie in robotics, human-robot interaction, control systems, renewable energy systems, and sensor fault detection. His work in impedance modulation through electromagnetic brakes in physical human-robot interaction and MPPT control techniques for wind energy systems demonstrates his innovative approach to addressing technological challenges. 🤖⚡

Awards and Honors:

Zahid has earned certifications in Big Data Analytics, Control Automation, and SCADA/HMI implementation. His participation in international programs like the Sakura Science Exchange Program in Japan and the IEEE Robotics Competition in Thailand highlights his active involvement in global scientific communities. 🏆🌟

Publication Top Notes:

Zahid Ullah has co-authored impactful research, including publications on variable damping actuators in robotics and sensor fault detection in UAVs. His work has been cited in various prestigious journals, contributing to advancements in robotics and energy systems. 📑🔗

Ullah, Zahid, Ronnapee Chaichaowarat, and Witaya Wannasuphoprasit. “Variable Damping Actuator Using an Electromagnetic Brake for Impedance Modulation in Physical Human–Robot Interaction.” Robotics 12, no. 3 (2023): 80. Cited by Robotics journal (2023)

Maqsood, Hamid, et al. “Novel sensor fault detection and isolation for an unmanned aerial vehicle.” In IEEE IBCAST (2021), pp. 486-493. Cited by IEEE (2021)

Khan, Umar Habib, et al. “Backstepping based MPPT control technique for permanent magnet synchronous generator wind energy conversion system.” In IEEE iCoMET (2020), pp. 1-7. Cited by IEEE (2020)