Longfei Yue | AI Advancements | Best Researcher Award

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Dr. Longfei Yue | AI Advancements | Best Researcher Award

Dr. Longfei Yue | NUE | China

Longfei Yue is an influential researcher in the fields of unmanned aerial vehicles (UAVs), reinforcement learning, multi-agent systems, and intelligent autonomous control. His work focuses on advancing next-generation autonomous flight technologies, with major contributions to cooperative decision-making, swarm intelligence, guidance laws, and mission-planning strategies for aerial and aerospace systems. He has produced an extensive body of work, reflected through a strong publication record and impactful citation metrics. His research outputs include dozens of journal articles and conference papers, spanning high-quality platforms such as international aeronautical and aerospace journals, IEEE publications, machine learning proceedings, and multidisciplinary scientific journals. His citation 300, H-index 11, and 286 publication data highlight the growing influence and visibility of his contributions in the global research community. Yue’s research emphasizes cutting-edge reinforcement learning approaches such as hierarchical learning, multi-agent reinforcement learning, soft actor-critic frameworks, and constrained learning techniques. These methods are applied to challenging aerospace scenarios including exoatmospheric evasion, missile guidance, cooperative multi-target tracking, aerial confrontation strategies, dual-UAV reconnaissance, and intelligent route planning for UAV swarms. His studies integrate autonomy, control theory, optimization, and machine learning to develop efficient, safe, and robust decision-making mechanisms for complex flight environments. His work also extends to the development of unsupervised learning techniques for grouping aerial swarms and dynamic policy learning for combat maneuvering. Many of his publications have received substantial citations, demonstrating wide academic and practical relevance. Beyond UAVs, Yue has collaborated on interdisciplinary studies in applied sciences, psychology, medical engineering, and data-driven modeling, further broadening his research impact. Overall, Longfei Yue’s research significantly advances autonomous aerial systems, cooperative robotics, and intelligent control engineering. His contributions play a pivotal role in shaping the future of UAV autonomy, multi-agent intelligence, and high-level aerospace decision-making technologies.

Profile: Scopus

Featured Publications

Collaborative energy-saving path planning of unmanned surface vehicle cluster based on multi-head attention mechanism and multi-agent deep reinforcement learning. (2025). Engineering Applications of Artificial Intelligence.

 CAP planning method based on elliptic fitting of optimal detection routes. (2025). Beijing Hangkong Hangtian Daxue Xuebao (Journal of Beijing University of Aeronautics and Astronautics).

Exoatmospheric evasion guidance law with total energy limit via constrained reinforcement learning. (2024). International Journal of Aeronautical and Space Sciences.

Huan Wang | Smart Manufacturing | Best Researcher Award

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Dr. Huan Wang | Smart Manufacturing | Best Researcher Award

Dr. Huan Wang | sun yat-sen university | China

Huan Wang is a dedicated researcher currently pursuing a Ph.D. at the School of Advanced Manufacturing, Sun Yat-sen University, building upon a strong academic foundation established during his master’s studies in aerospace engineering at the same institution. His research focuses on advancing sensor technology through innovative approaches in temperature compensation, fault diagnosis, and the reliability assessment of pressure scanners—key components in precision measurement and industrial instrumentation. Over the years, he has contributed significantly to national and industry-driven scientific efforts, including participation in one National Key R&D Program, one National Natural Science Foundation project, and three important commissioned projects involving electronic pressure scanning valves. His expertise extends to instrumentation and measurement consultancy, allowing him to bridge academic research with practical engineering applications. Dr. Wang’s scholarly output includes more than eight peer-reviewed research articles, several of which he authored as first author in highly regarded SCI-indexed journals such as Measurement, Measurement Science and Technology, Micromachines, Instrumentation Science and Technology, and Metrology and Measurement Systems. His research demonstrates a strong commitment to integrating intelligent optimization algorithms with sensor systems to improve accuracy, stability, and reliability in real-world applications. Alongside his research achievements, he is a professional member of AAAS and IEEE, showcasing his active engagement with the global scientific community. Through his interdisciplinary skills, academic rigor, and industry collaborations, Huan Wang continues to make meaningful contributions to the fields of sensor technology, advanced manufacturing, and applied measurement science. His growing body of work reflects not only technical depth but also a forward-looking approach aimed at enhancing next-generation intelligent measurement systems. With a strong commitment to innovation, integrity, and scientific excellence, he stands out as a promising researcher who significantly contributes to the advancement of engineering research and instrumentation technologies.

Profile: Orcid

Featured Publications

Wang, H., Chen, X., Xia, J., Zhao, H., & Maddaiah, P. N. (2026). Newton-Raphson-based optimizer combined with LSSVM: Temperature compensation applied to small-range electronic pressure scanners. Flow Measurement and Instrumentation. https://doi.org/10.1016/j.flowmeasinst.2025.103127

Wang, H., Chen, X., Xia, J., Liu, P., & Zhao, H. (2025). A novel model fusing ALA and integrated learning: Temperature compensation for 700 kPa pressure scanners. International Journal of Thermophysics. https://doi.org/10.1007/s10765-025-03638-x

Wang, H. (2025). Hybrid mechanism and data driven approach for high-precision modeling of gas flow regulation systems of VFDR. Journal article. https://doi.org/10.1007/s40747-025-01899-5

Wang, H., Wu, T., Liu, P., Zou, Y., & Zeng, Q. (2025). Kernel extreme learning machine combined with gray wolf optimization for temperature compensation in pressure sensors. Metrology and Measurement Systems. https://doi.org/10.24425/mms.2025.152773

Wu, T., Wang, H., Huang, Z., & Maddaiah, P. N. (2025). Optimal tracking differentiator algorithm for accurate pressure scanner measurements. Instrumentation Science and Technology. https://doi.org/10.1080/10739149.2025.2556107

Liu, C., Wang, H., Zhu, H., Zhou, W., & Zhao, H. (2025). Optimized design of support points in solar panels based on thermal deformation analysis. Journal of Physics: Conference Series, 3039(1), 012004. https://doi.org/10.1088/1742-6596/3039/1/012004

Marwan | AI Advancements | Excellence in Research

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Dr. Marwan | AI Advancements | Excellence in Research

Dr. Marwan | King Faisal University | Saudi Arabia

The applicant is an accomplished scholar in Computer Information Systems with specialized expertise in Artificial Intelligence and Data Science, supported by extensive experience in academia, research, and innovation. Over more than a decade of university-level teaching and research, the applicant has contributed significantly to advancing intelligent systems, machine learning applications, IoT security, biomedical imaging, and pattern recognition. Their doctoral work introduced a novel model for Arabic handwritten text recognition, forming the foundation for a strong research career in AI-driven language and image processing technologies. The applicant has authored and co-authored numerous impactful, refereed journal publications in well-recognized international outlets such as Sustainability, IJACSA, Traitement du Signal, and the Journal of Ayub Medical College. Research contributions span cancer therapy enhancement, anomaly detection, cephalometric landmark detection, multiple sclerosis classification, industrial IoT security, biometric iris recognition, palm disease classification, and Arabic word recognition. Several works have been indexed in Scopus and other reputable databases, with active collaborations involving interdisciplinary and multinational research teams. Beyond publications, the applicant has secured competitive research funding, including a grant supporting the development of a weighted-voting IoT security model targeting BASHLITE and Mirai cyberattacks. Ongoing research activities include hybrid deep learning systems for intrusion detection, medical image analysis, human nail disease diagnosis, music-brain interactions, and predicate-logic-based machine translation. The applicant has demonstrated strong academic service through extensive peer-reviewing, participation in scientific councils, and membership in research committees. Their professional development includes participation in conferences, training programs, and workshops focused on e-learning, scientific publishing, and advanced teaching strategies. Recognized for excellence, the applicant has received awards such as the Distinguished Scientific Research Award and the Outstanding International Publishing Award, reflecting sustained research quality and global scholarly impact. Their overall portfolio showcases a balanced blend of innovative research, academic leadership, and contributions to the AI and data science community.

Profiles: Scopus 

Featured Publications

Siddiqi, M. H., Alhwaiti, Y., Elaiwat, S., & Abu-Zanona, M. (2024). Dynamic healing process analysis: Image morphing with warping technique for nose and esophagus studies. The International Arab Journal of Information Technology, 21(3). (Accepted December 26, 2023).

 

Keyi Chen | AI Advancements | Best Researcher Award

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Mr. Keyi Chen Jihua Laboratory | AI Advancements | Best Researcher Award

Mr. Keyi Chen | Jihua Laboratory | China

Keyi Chen is a dedicated research engineer at Jihua Laboratory, Foshan, Guangdong Province, China. He obtained his MSc in Crop Informatics from Huazhong Agricultural University , where he built a strong foundation in computational modeling and artificial intelligence applications. His research primarily focuses on deep learning algorithms, particularly their integration into computer-based recognition systems and intelligent environmental analysis. He has completed three research projects and participated in one industry consultancy project, demonstrating both academic and applied innovation. His current research explores AI-driven recognition of marine microalgae, an essential area for assessing aquatic ecological health. In this domain, Chen developed a ResNeXt-50-based multi-expert network with an exponential feature compression mechanism that effectively mitigates class imbalance issues. Evaluated on the WHIO-Plankton dataset, his model achieved a state-of-the-art performance with an average precision and average recall , outperforming existing baselines. The system’s low inference latency demonstrates high real-time feasibility. His contributions provide a robust framework for marine microalgae recognition, supporting environmental monitoring and marine life science research. With Citations by 38 documents, 3 publications, and an h-index of 2, Chen has established himself as a rising researcher in applied AI and computational biology. His ongoing innovations signify impactful potential in environmental intelligence, sustainable technology, and bioinformatics applications.

Profile: Scopus | Orcid

Featured Publications

Chen, K., Cui, S., Zhong, J., & Wang, Q. (2025). MicroalgaeNet: Enhancing recognition of long-tailed marine microalgae images through multi-expert networks and feature compression. Algal Research, 92, 104333. https://doi.org/10.1016/j.algal.2025.104333

Song, P., Chen, K., Zhu, L., Yang, M., Ji, C., Xiao, A., Jia, H., Zhang, J., & Yang, W. (2022). An improved cascade R-CNN and RGB-D camera-based method for dynamic cotton top bud recognition and localization in the field. Computers and Electronics in Agriculture, 202, 107442. https://doi.org/10.1016/j.compag.2022.107442

Bao Liu | Emerging Technologies | Best Researcher Award

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Dr. Bao Liu | Emerging Technologies | Best Researcher Award

Dr. Bao Liu | Xi’an University of Science and Technology | China

Dr. Liu Bao is an Associate Professor and Academic Leader in the field of Pattern Recognition and Intelligent Systems at the School of Electrical and Control Engineering, Xi’an University of Science and Technology, where he also serves as a Graduate Supervisor and Project-based Ph.D. Supervisor. He earned his doctorate in engineering from Xi’an Jiaotong University, completed postdoctoral research at Xi’an University of Science and Technology, and broadened his academic experience as a visiting fellow at Macquarie University in Australia. Recognized as a Senior Data Analyst by the Ministry of Industry and Information Technology of China, Dr. Liu is an active member of several national academic societies and professional committees. His research focuses on multi-source information fusion and intelligent technologies for coal fire disaster prevention and control, integrating advanced computational and automation techniques to address complex industrial challenges. Throughout his career, he has led diverse national, provincial, and industry-based research projects and contributed extensively to scientific publications and technological innovation through patents and software developments. As a committed educator and mentor, Dr. Liu has inspired students to excel in academic and professional pursuits and has been honored with multiple awards recognizing his dedication to teaching, research, and academic service.

Profile: Orcid

Featured Publications

Liu, B., Liu, Q., & Wu, Z. (2026, February). A novel robust Student’s t scale mixture distribution based Kalman filter. Signal Processing. https://doi.org/10.1016/j.sigpro.2025.110296

Liu, B., Wu, Z., & Liu, Q. (2025). Gaussian mixture model-based variational Bayesian approach for extended target tracking. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2025.3565347

Liu, B., & Jiang, W. (2024). DFKD: Dynamic focused knowledge distillation approach for insulator defect detection. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2024.3485446

Liu, B., & Jiang, W. (2024, December). LA-YOLO: Bidirectional adaptive feature fusion approach for small object detection of insulator self-explosion defects. IEEE Transactions on Power Delivery. https://doi.org/10.1109/TPWRD.2024.3467915

Liu, B., Zhou, N., & Wang, Z. (2024, December 27). DFI-YOLOv8 based defect detection method for fan blades. In Proceedings of the 2024 Conference on [Insert Conference Name]. https://doi.org/10.1145/3722405.3722437

Alejandro Sabán Fosch | Systems Design | Best Researcher Award

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Mr. Alejandro Sabán Fosch | Systems Design | Best Researcher Award

Mr. Alejandro Sabán Fosch, GTD SSI, Spain

Mr. Alejandro Sabán Fosch is a Ph.D. candidate in Aerospace Engineering at UPC-EMFA and a Systems & Software Aerospace Engineer at GTD System & Software Engineering, Spain. With strong expertise in launcher safety, guidance, and simulation systems, he is actively contributing to cutting-edge European space initiatives including SALTO, ENVOL, and ESRANGE-RSD. His work focuses on developing autonomous flight safety systems and modular flight software solutions aimed at advancing reusable launch technologies. Alejandro combines deep technical knowledge with hands-on experience in avionics, flight dynamics, and predictive maintenance systems, supported by a solid academic foundation and international project collaboration.

Author Profile

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🎓 Early Academic Pursuits

Alejandro Sabán Fosch’s journey into aerospace engineering began with a strong academic foundation at the Universitat Politècnica de Catalunya (UPC). He earned his Bachelor’s degree in Aerospace Science and Technology from EETAC-UPC, Castelldefels, specializing in air navigation, rocket and jet engines, aeroelasticity, and finite element methods. His academic excellence was quickly recognized, earning him the Best Academic Record award (2014–2018) from EETAC and the HEMAV Foundation. Notably, his Bachelor’s thesis—“Analysis of the Air Flow in Through a Car Diffuser”—was completed with honors, highlighting his ability to blend practical application with theoretical knowledge. During his undergraduate years, Alejandro also broadened his perspective through a six-month academic exchange with ETSIAE-UPM in Madrid. He later pursued a Master’s in Aeronautical Engineering with a specialization in Aerospace Vehicles at ESEIAAT-UPC, where he continued to thrive academically. His Master’s thesis on a “Modular Plant Generator Tool for Space Mission Launchers Optimization”, done in collaboration with GTD System & Software Engineering, laid the groundwork for his early industry integration and long-term research direction.

💼 Professional Endeavors

Alejandro’s professional trajectory is deeply embedded within GTD System & Software Engineering, where he has grown from a software system engineering intern to a full-fledged Systems & Software Aerospace Engineer. Since June 2020, he has been at the forefront of European space projects, notably contributing to next-generation reusable launch systems, flight safety solutions, and mission software development. In the Horizon Europe SALTO project, Alejandro leads the development and testing of an Autonomous Flight Safety System (AFSS), a groundbreaking system designed to enhance the safety and reusability of future European launchers. He plays a key role in designing ground-based systems and preparing for test campaigns at the ESRANGE Space Center in Sweden. His efforts also extend to the ESRANGE-RSD project, where he has developed real-time tracking and safety algorithms tailored to launch base operations. Beyond SALTO, he has contributed to several influential projects such as MASSIM (simulation software for flight software validation), ANDOYA LCS (launch control systems for Andøya Space Port), ENVOL (avionics and FSW for micro-launchers), and SAMMBA (virtualized launch base services). His work spans simulation, GNC (guidance, navigation, and control), and safety systems, showcasing his versatility across hardware, software, and systems engineering domains.

🔬 Contributions and Research Focus

Currently pursuing his Ph.D. in Aerospace, Aeronautical and Astronautical/Space Engineering at UPC-EMFA, Alejandro’s research focuses on Autonomous Flight Safety Systems and Predictive Maintenance—critical areas for the future of reusable spaceflight. His doctoral work is being conducted in close collaboration with GTD System & Software Engineering and forms part of the Horizon Europe SALTO initiative, a flagship project aimed at positioning Europe at the forefront of reusable launch technologies. He has authored several impactful publications, including the 2025 Acta Astronautica article titled “Towards the First European Autonomous Flight Safety System – Software and Hardware Design” and contributions to major conferences such as IAC and EUCASS. His work bridges academic research and real-world application, particularly in the fields of real-time decision-making, mission-specific flight software, and modular avionics architectures.

🏅 Accolades and Recognition

Alejandro’s career has been marked by continuous academic and professional recognition. His early academic performance earned him the Best Academic Record award for his undergraduate studies. More recently, his innovative work has gained visibility through peer-reviewed publications and presentations at prestigious aerospace conferences. His career has been supported by the Doctorats Industrials programme of the Generalitat de Catalunya, a selective initiative that fosters cooperation between academia and industry for high-impact doctoral research. He has also pursued additional certifications in machine learning, Docker, and PLC development, showcasing his commitment to continuous learning and technological advancement.

🌍 Impact and Influence

Alejandro’s contributions are already influencing the development of safer, more autonomous, and reusable launch vehicles in Europe. By helping to develop systems that reduce reliance on human-in-the-loop decision-making, Alejandro is helping to lay the technical groundwork for the next generation of commercial and scientific launch systems. His work has direct applications in flight safety, predictive maintenance, GNC systems, and virtualized launch services, and he frequently collaborates with partners across Europe, including ArianeGroup, CNES, and NAMMO. His cross-functional expertise—from real-time software design to systems-level simulation—positions him as a key player in the evolution of European spaceflight infrastructure.

🌠 Legacy and Future Contributions

As he continues his Ph.D. and gains further experience in high-level aerospace systems, Alejandro is poised to become a leading figure in the next wave of European launch innovations. His contributions to SALTO and other pioneering projects signal a strong future impact on the space industry, particularly in areas like AI-driven safety systems, software-in-the-loop environments, and mission adaptability for NewSpace operators. Looking forward, Alejandro aims to bridge the gap between academic research and industrial application, fostering interdisciplinary collaborations and pushing the envelope of aerospace system design. His career is a testament to what can be achieved through a blend of technical expertise, curiosity, and vision—qualities that will undoubtedly shape his legacy in the field of space engineering.

✍️Notable Publications

Towards the first European Autonomous Flight Safety System- Software and Hardware Design 

Contributors: Alejandro Sabán-Fosch; Eduard Diez-Lledó; Manel Soria; Miquel Sureda

Journal: Acta Astronautica

Year: 2025

Autonomous Flight Safety System: Embedded Software and Hardware Equipment for NewSpace Ground and Onboard Safety

Contributors: Alejandro Sabán; Eduard Diez; Manel Soria; Miquel Sureda

Journal: IAF Space Operations Symposium

Year: 2024

Missionisable on-board flight safety based on real-time autonomous decision-making for microlauncher services

Contributors: Nil Martin; Carla Navarro; Eduard Díez; Alejandro Sabán-Fosch; Jordi Martín; Magda Escorsa
Journal: Proceedings of the 9th European Conference for Aerospace Sciences. Lille, France, 27 June – 1 July, 2022
Year: 2022