Size Ai | Engineering | Research Excellence Award

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Mr. Size Ai | Engineering | Research Excellence Award 

Harbin Institute of Technology | China

Dr. Size Ai, currently a PhD researcher at the Harbin Institute of Technology, is an emerging scholar in the field of mechanical metamaterials and advanced structural design. Holding a PhD in Mechanics from Harbin Institute of Technology, Dr. Ai has developed strong expertise in the design, modeling, and steady-state analysis of mechanical metamaterials, focusing particularly on negative stiffness structures, multi-stable metastructures, and pneumatic actuators with tunable mechanical responses. His academic journey reflects a commitment to high-quality research, having published three SCI-indexed papers in top-tier JCR Q1 journals such as Thin-Walled Structures and Engineering Structures. His works include: “Analysis of Negative Stiffness Structures with B-spline Curved Beams” (Thin-Walled Structures, 2024), “Design and Analysis of an Origami-Embedded Multi-Stable Metastructure with Shape Reconfiguration” (Engineering Structures, 2025), and “Deep Learning-Based Structural Design and Mechanical Properties Analysis of Pneumatic Actuators with Tunable Multistability” (Thin-Walled Structures, 2025). These publications highlight Dr. Ai’s ability to integrate theoretical modeling, simulation optimization, deep learning techniques, and experimental validation to solve complex challenges in structural mechanics. He has contributed significantly to ongoing national research through his involvement in the National Natural Science Foundation of China project (Grant No. 12372041), which further demonstrates his active engagement in advancing scientific knowledge. One of Dr. Ai’s major contributions includes developing a configuration parameterization method based on B-spline curves to customize negative stiffness characteristics in metamaterials. Additionally, he proposed a steady-state switching strategy using reconfigurable energy barrier elements, enabling precise control over multi-stability and shape transformation in engineered structures. His work successfully demonstrates, through combined theory, simulations, and experiments, the feasibility of programmable mechanical behavior after forming—an advancement with promising applications in soft robotics, adaptive structures, vibration isolation, and smart materials. Dr. Ai’s research continues to attract academic attention, with citations indexed in the Web of Science database. He maintains a strong ethical commitment to research integrity, with no consultancy projects, patents, or books yet undertaken. While he currently holds no editorial appointments, professional memberships, or formal collaborations, his research trajectory shows excellence, independence, and innovation, positioning him as a competitive candidate for the Research Excellence Award. Dr. Ai affirms that all submitted information is accurate, verifiable, and supported by relevant research links, including: 10.1016/j.tws.2025.114287 and 10.1016/j.tws.2023.111418. He fully agrees to the terms, policies, and responsibilities associated with this award nomination and submits this application with the highest level of integrity.

Profile: Scopus

Featured Publications

Ai, S., Xie, Z., & Wei, J. (2025, November). Deep learning-based structural design and mechanical properties analysis of pneumatic actuators with tunable multistability.

Ai, S., Hou, S., Wei, J., & Xie, Z. (2025, October). Design and analysis of an origami-embedded multi-stable metastructure with shape reconfiguration.

Hou, S., Wei, J., Ai, S., & Tan, H. F. (2025, March). Broadband nonlinear vibration isolation for a friction dynamic system via quasi-zero stiffness isolator.

Bian, S., Ai, S., Wei, J., & Qingxiang, J. (2025, March). Structural design and performance analysis of large inflatable solar membrane reflector.

Ai, S., Wei, J., Xie, Z., & Tan, H. F. (2023, November). Analysis of negative stiffness structures with B-spline curved beams.

Sedighe Mirbolouk | Engineering | Editorial Board Member

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Dr. Sedighe Mirbolouk | Engineering | Editorial Board Member 

Iran National Science Foundation | Iran

Dr. Sedighe Mirbolouk is a dedicated postdoctoral researcher and advanced machine learning specialist with strong expertise in communication systems, data science, and artificial intelligence. She is affiliated with the Iran National Science Foundation and has built a diverse research portfolio spanning deep learning, wireless communication optimization, image processing, and intelligent sensing systems. Her technical proficiency covers a wide spectrum of tools and programming environments, including Python, MATLAB, LATEX, and advanced libraries such as TensorFlow, PyTorch, Scikit-learn, NumPy, SciPy, Pandas, and Matplotlib. With a strong theoretical foundation in data telecommunication networks, convex optimization, communication theory, and signal and image processing, she integrates computational intelligence with modern communication challenges. In her role as a Postdoctoral Researcher (2024–2025) at the Iran National Science Foundation, Dr. Mirbolouk focuses on cutting-edge topics in graph learning and federated learning, particularly designing machine learning approaches for predictive beamforming in Reconfigurable Intelligent Surface (RIS)-aided Integrated Sensing and Communication (ISAC) systems. Her work aims to improve efficiency, adaptability, and intelligence in next-generation wireless communication networks. Previously, she served as a Visiting Researcher (2022) at the University of Oulu in Finland, where she explored advanced deep reinforcement learning methods to enhance ISAC designs. These research experiences have positioned her at the frontier of combining AI with communication technologies. During her doctoral studies at the University of Urmia (2018–2021), Dr. Mirbolouk contributed significantly to satellite–UAV cooperative network optimization. She developed innovative solutions involving UAV selection and power allocation for CoMP-NOMA transmissions, introducing both Lagrangian and heuristic algorithms that advanced energy-efficient communication frameworks. Alongside communications research, she proposed image processing solutions such as fuzzy histogram weighting methods and contrast enhancement techniques. Her academic involvement includes teaching core engineering subjects—Digital Communication, Probability and Statistics, and Signals and Systems—and assisting courses on Stochastic Processes and Digital Signal Processing. Her work at the National Elite Foundation (2020–2022) expanded her portfolio into biomedical machine learning applications, where she designed systems for automatic breast cancer detection using histopathology images and cardiac arrhythmia recognition using ECG signals through deep learning approaches. Dr. Mirbolouk holds a Ph.D. in Electrical Engineering, with earlier B.Sc. and M.Sc. degrees from the University of Guilan, where she studied SAR radar Doppler ambiguity for moving targets. Her scholarly contributions include high-impact publications in journals such as IEEE Transactions on Vehicular Technology, Physical Communication, and Multimedia Tools and Applications. Collectively, her research reflects an outstanding integration of machine learning, optimization, sensing, and communication technologies.

Profile: Google Scholar

Featured Publications

Mirbolouk, S., Valizadeh, M., Amirani, M. C., & Ali, S. (2022). Relay selection and power allocation for energy efficiency maximization in hybrid satellite-UAV networks with CoMP-NOMA transmission. IEEE Transactions on Vehicular Technology, 71(5), 5087–5100.

Mirbolouk, S., Valizadeh, M., Amirani, M. C., & Choukali, M. A. (2021). A fuzzy histogram weighting method for efficient image contrast enhancement. Multimedia Tools and Applications, 80(2), 2221–2241.

Mirbolouk, S., Choukali, M. A., Valizadeh, M., & Amirani, M. C. (2020). Relay selection for CoMP-NOMA transmission in satellite and UAV cooperative networks. 2020 28th Iranian Conference on Electrical Engineering (ICEE), 1–5.

Choukali, M. A., Valizadeh, M., Amirani, M. C., & Mirbolouk, S. (2023). A desired histogram estimation accompanied with an exact histogram matching method for image contrast enhancement. Multimedia Tools and Applications, 82(18), 28345–28365.

Hussein, A. A., Valizadeh, M., Amirani, M. C., & Mirbolouk, S. (2025). Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework. Scientific Reports, 15(1), 25071.

Choukali, M. A., Mirbolouk, S., Valizadeh, M., & Amirani, M. C. (2024). Deep contextual bandits-based energy-efficient beamforming for integrated sensing and communication. Physical Communication, 68, 102576.

Ning Chen | Engineering | Best Researcher Award | 13558

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Mr. Ning Chen | Engineering | Best Researcher Award

Mr. Ning Chen, Shandong University of Science and Technology, China

Mr. Ning Chen, Lecturer at Shandong University of Science and Technology, China, is an emerging researcher in high-precision mechatronic systems. With a Ph.D. in mechanical engineering and prior industry experience, he has developed innovative piezoelectric galvanometers, stiffness-adjustable servo systems, and micro-nano motion platforms. His work is shaping the future of laser positioning, scanning, and ultra-precision control technologies. Backed by prestigious national and provincial research grants, Mr. Chen exemplifies academic excellence and practical innovation in mechanical and precision engineering.

Author Profile

Orcid

Education

Dr. Weijian Wang embarked on his academic journey with a solid foundation in chemical sciences. He earned his Bachelor’s degree in Chemical Engineering and Technology from the China University of Petroleum (East China)—an institution known for producing talent in energy and chemical sectors. His academic excellence and growing passion for applied chemical research led him to pursue a Master’s degree in Chemical Engineering at the China University of Mining and Technology, where he deepened his understanding of reaction engineering, process modeling, and advanced materials.

Eager to contribute to cutting-edge innovation in the energy sector, Dr. Wang pursued his Ph.D. in Chemical Technology at the Research Institute of Petroleum Processing (RIPP), Sinopec, one of China’s leading industrial research institutions. His doctoral training provided him with hands-on experience in industrial-scale research, advanced materials development, and interdisciplinary collaboration. To further strengthen his academic and research profile, Dr. Wang completed a postdoctoral fellowship at Zhejiang University, where he explored emerging materials and device applications, preparing him for a career at the intersection of academia and applied science.

Experience

In 2022, Dr. Wang joined Beibu Gulf University as an Associate Professor, where he has since led a promising research group focusing on halide perovskite materials. As a faculty member, he has embraced both teaching and research, mentoring students while pursuing innovative solutions to modern energy and optoelectronic challenges.

One of his key professional milestones includes leading the Guangxi Science and Technology Major Program (GuikeAA23062016). This ambitious research initiative demonstrates his leadership and technical capability in managing multi-disciplinary projects aligned with regional and national scientific goals. With no industry consultancies yet, Dr. Wang remains fully invested in academic research, pushing boundaries in materials science through both simulations and experimental designs.

Research Focus

Dr. Weijian Wang’s research is centered on the green synthesis and application of halide perovskite materials, a rapidly evolving class of compounds celebrated for their extraordinary optoelectronic properties. These materials are particularly promising in fields such as solar energy conversion, light-emitting diodes (LEDs), and medical bioimaging. At the heart of Dr. Wang’s innovation is the drive for sustainability. He has developed eco-friendly synthesis techniques that minimize environmental harm while maintaining material performance, advancing the goal of sustainable science. 🌱

In the field of perovskite solar cells, Dr. Wang employs simulation-assisted design methodologies to enhance energy conversion efficiency. His designs have led to devices with superior performance characteristics, addressing one of the key challenges in renewable energy technology. 🌞 Beyond energy, his research also extends to optoelectronic devices, including perovskite-based LEDs and imaging systems with applications in healthcare diagnostics and bioimaging. 💡

Dr. Wang’s robust scientific output includes 11 peer-reviewed publications in internationally recognized SCI-indexed journals, with eight authored as first or corresponding author. Additionally, he has secured 15 authorized invention patents as the primary inventor, underscoring his capacity to translate theoretical research into tangible technological innovations.

Award and Recognition

Despite being in the early stages of his academic journey, Dr. Wang has already built a strong research profile distinguished by originality, technical rigor, and innovation. His contributions have earned him 11 published articles in high-impact SCI-indexed journals, demonstrating both quality and consistency in scientific communication. 📚

Dr. Wang also holds 15 authorized invention patents, a notable achievement that reflects his focus on applied research and technology transfer. 🧾 These patents not only reinforce his expertise in halide perovskite materials but also highlight his dedication to practical solutions for global energy and environmental challenges.

Further elevating his academic standing, Dr. Wang currently leads a major government-funded research program, indicating trust in his leadership and vision at the national level. 💼 His H-index of 5 signifies an increasing impact within the scholarly community, with a trajectory that suggests sustained and growing influence in the years to come.

Although he does not yet hold editorial roles or memberships in professional societies, his impressive publication and patent record mark him as a promising figure in materials science. His career is on a path toward broader recognition, leadership roles, and continued contributions to the scientific community.

Publications

📖 A Semi-analytical Method for Vibro-Acoustic Properties of Functionally Graded Porous Piezoelectric Annular Plates with Cavity – Journal of Vibration Engineering and Technologies (2025).
📖 Enhancing the motion performance of 3-DOF micro/nano-manipulators facing thermo-piezoelectric-mechanical coupling effects – Sensors and Actuators A Physical (2025)
📖 Robust control of uncertain asymmetric hysteretic nonlinear systems with adaptive neural network disturbance observer – Applied Soft Computing (2024)
📖 Low thermal budget lead zirconate titanate thick films integrated on Si for piezo-MEMS applications – Microelectronic Engineering (2020)