Kirill Poletkin | Engineering | Best Research Article Award

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Prof. Kirill Poletkin | Engineering | Best Research Article Award

Hefei University of Technology | China

Professor Kirill V. Poletkin is a distinguished researcher and academic specializing in micro- and nano-scale electromechanical systems, contactless levitation micro-actuators, MEMS inertial sensors, and precision instrumentation. He currently serves as a Professor (Talents Programme) at the School of Instrument Science and Optoelectronics Engineering, Hefei University of Technology, China. Prof. Poletkin earned his Ph.D. in Control Systems, Informatics, and Electrical Engineering from the Moscow Aviation Institute in 2007, where his doctoral research focused on closed-loop rotor vibratory gyroscopes. He obtained his M.Eng. with honors from Nizhny Novgorod State Technical University, with award-winning research in vibration theory and dynamically tuned gyroscopes recognized by the Ministry of Education and Science of the Russian Federation. With over two decades of international research experience, he has held academic and research positions at leading institutions including the Karlsruhe Institute of Technology, University of Freiburg, Nanyang Technological University, Innopolis University, and New Uzbekistan University. He is a former Alexander von Humboldt Research Fellow and has served as Principal Investigator on multiple competitively funded projects supported by the German Research Foundation (DFG) and Chinese provincial agencies. Prof. Poletkin has authored over 86 scientific publications, including 37 peer-reviewed journal articles, book chapters, and a Springer monograph titled Levitation Micro-Systems: Applications to Sensors and Actuators. His pioneering contributions to zero–spring-constant contactless suspensions, hybrid inductive–electrostatic levitation systems, and semi-analytical electromagnetic modeling have enabled new generations of high-precision sensors, actuators, and micro-transport technologies.

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Featured Publications

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.