Xilai li | Engineering | Best Researcher Award

Mr. xilai li | Engineering | Best Researcher Award

Mr. xilai li | Nanjing University of Aeronautics and Astronautics | China

Mr. Li Xilai, a 25-year-old postgraduate student at Nanjing University of Aeronautics and Astronautics, is pursuing a Master’s degree in Mechanical Engineering at the School of Aeronautics, following his Bachelor’s degree in Aircraft Manufacturing Engineering from the Civil Aviation University of China. His academic foundation covers a wide range of aeronautical subjects, including theoretical mechanics, fluid mechanics, structural dynamics, computational aerodynamics, aeroengine principles, and aeronautical systems engineering. He has developed strong technical expertise in advanced engineering software such as ABAQUS, OPENFAST, VABS, BECAS, Bladed, MATLAB, CAD, SolidWorks, and Origin, along with proficiency in programming languages including Python, MATLAB, and FORTRAN. His research interests center on nonlinear blade modeling, aeroelastic response, and vibration suppression in large-scale wind turbines. He has actively contributed to projects such as offshore wind power integrated numerical simulation software evaluation and flow control simulations for blades and airfoils. His innovative research has resulted in two patent applications related to vibration reduction in wind turbine systems and floating platforms. He has also shared his work at prestigious conferences, presenting on topics such as tuned mass-damper inertia systems for vibration control and the influence of control parameters on flutter boundaries in wind turbines. Recognized as an excellent graduate student and outstanding research leader, he combines strong analytical ability with leadership and teamwork. Optimistic, adaptable, and highly motivated, he demonstrates a strong commitment to advancing renewable energy technologies, particularly in offshore wind engineering, while contributing innovative solutions to future challenges in aerospace and energy systems.

Featured Publications

Li Xilai. Numerical Optimization of Tuned Mass-Damper Inertia Systems for Vibration Control in Wind Turbines. China Aerodynamics Conference Proceedings, cited by 8 articles.

Li Xilai. Influence of Control Parameters on Flutter Boundary of Large Horizontal-Axis Wind Turbines. Mechanics & Renewable Energy Forum Proceedings, cited by 5 articles.

Alejandro Medina Santiago | Engineering | Outstanding Scientist Award

Dr. Alejandro Medina Santiago | Engineering | Outstanding Scientist Award

Secretariat of Science, Humanities, Technology and Innovation | Mexico

Dr. Alejandro Medina Santiago is a Mexican researcher in Electrical Engineering, specializing in VLSI integrated circuit design, neural networks, fuzzy logic, intelligent systems, and Industry 4.0 technologies. He earned his Doctor of Science and Master of Science degrees in Electrical Engineering from the Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV-IPN), where his doctoral research focused on the design of arithmetic cells using multi-input floating gate devices for reconfigurable circuits in image processing and pattern recognition, and his master’s thesis concentrated on neural network-based classification systems for analog signals. He also holds a degree in Electronics Engineering from the Technological Institute of Tuxtla Gutiérrez. Since 2017, he has been a Researcher at the National Institute of Astrophysics, Optics, and Electronics (INAOE) and is a member of Mexico’s National System of Researchers (SNI Level 1, 2021–2025). His areas of expertise include signal processing, IoT, cybersecurity, deep learning, automotive ecosystem diagnostics, and circuit design. Dr. Medina Santiago has directed and participated in numerous projects, including deep neural networks for automotive systems, automotive embedded platforms, IoT educational initiatives, and agricultural disease detection through georeferenced image processing. He has authored more than 20 indexed journal articles, published a book, and holds four patents in process. Additionally, he contributes as a reviewer and editorial board member for IEEE, MDPI, Springer, and Elsevier. A committed educator, he teaches both undergraduate and postgraduate courses on IoT, artificial intelligence, machine learning, electronics, and intelligent control, while actively mentoring future engineers and researchers.

Profile: Orcid

Featured Publications

Medina-Santiago, A., et al. (2025). Machine Learning-Powered IDS for Gray Hole Attack Detection in VANETs. World Electric Vehicle Journal, 16(9), 526. [DOI: 10.3390/wevj16090526]

Orozco Torres, J. A., Medina Santiago, A., et al. (2025). A Data-Driven Approach Using Recurrent Neural Networks for Material Demand Forecasting in Manufacturing. Logistics, 9(3), 130. [DOI: 10.3390/logistics9030130]

Aguilar-González, A., Medina Santiago, A. (2025). Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data. Algorithms, 18(3), 127. [DOI: 10.3390/a18030127]

Orozco Torres, J. A., Medina Santiago, A., et al. (2024). Multilayer Fuzzy Inference System for Predicting the Risk of Dropping Out of School at the High School Level. IEEE Access, 12, 3425548. [DOI: 10.1109/ACCESS.2024.3425548]

Bermúdez Rodríguez, J. I., Medina Santiago, A., et al. (2024). Fault Diagnosis for Takagi-Sugeno Model Wind Turbine Pitch System. IEEE Access, 12, 3361285. [DOI: 10.1109/ACCESS.2024.3361285]