Mr. Leiwei Zhu | Power Electronics Involves | Research Excellence Award

Published on by Electrical Engineering

Mr. Leiwei Zhu | Power Electronics Involves | Research Excellence Award

Senior Engineer | CRRC QINGDAO SIFANG CO., LTD | China

Zhu Leiwei, a Senior Engineer at CRRC Qingdao Sifang, specializes in vibration and noise control for rail transportation systems, applying his expertise to enhance the acoustic performance and reliability of high-speed rolling stock. Holding a master’s degree with specialization in vibration and noise control, he has developed strong technical competence in designing and optimizing noise-reduction structures and diagnosing abnormal acoustic behaviors in advanced rail vehicles. His professional experience spans high-speed EMUs and maglev systems, where he has contributed to major engineering projects focused on reducing vehicle noise, improving passenger comfort, and ensuring system safety. He has led work on integrated acoustic-material-electrical solutions for EMU motor noise control, achieving notable reductions in operational noise levels and contributing to improved system stability. His research includes publications and multiple patented innovations, reflecting his contributions to rail-vehicle vibration mitigation and structural acoustic optimization. He has participated in collaborative technical evaluations, supported engineering standardization efforts, and engaged with professional communities connected to rail technology and noise control engineering. His work has been acknowledged through institutional recognition and involvement in scholarly review activities, demonstrating his commitment to advancing high-performance, sustainable rail transit technologies. 30 Citations, 12 Documents, 3 h-index, View h-index button is disabled in preview mode

Profile: Scopus 

Featured Publications

Zhu Leiwei, Study on noise control and safety assessment of an EMU motor. High Speed Railway, Accepted.*

Zhu Leiwei, Vibration and noise control strategies for high-speed EMU systems. Rail Vehicle Dynamics, Under Review.

Zhu Leiwei, Acoustic–electromechanical coupling analysis for rail-vehicle motor noise optimization. J. Rail Transit Eng., In Preparation.

Mr. Qiaosheng Pan | Piezoelectric Precision Drive | Research Excellence Award

Published on by Electrical Engineering

Mr. Qiaosheng Pan | Piezoelectric Precision Drive | Research Excellence Award

Professor | Institute of Instrumentation Science and Optoelectronic Engineering, Hefei University of Technology | China

Qiaosheng Pan, an Associate Professor at the Institute of Instrumentation Science and Optoelectronic Engineering, Hefei University of Technology, is a specialist in precision mechanical design, piezoelectric transducers, sensors, and actuators. He holds a B.E. in mechanical engineering and automation from the University of Jinan and a Ph.D. in instrumentation and optoelectronic engineering from the University of Science and Technology of China. His professional experience includes leading numerous national and provincial research projects, authoring a technical monograph, and contributing extensively to the development of advanced piezoelectric motors, pumps, and actuators. He has published widely in SCI and Scopus-indexed journals, with research spanning resonant piezoelectric systems, high-precision displacement mechanisms, and novel actuator architectures, supported by multiple granted patents that advance intelligent detection and precision instrumentation. He has served as a young editor for an academic journal, contributed to major national research collaborations, and holds senior membership in the Chinese Society for Mechanical Engineering. His work integrates design innovation, structural optimization, and experimental validation, significantly shaping next-generation high-precision devices while supporting talent development and engineering practice. 834 citations, 90 documents, 15 h-index.

Profiles: Scopus

Featured Publications

Pan, Qiaosheng*, Development of a type of cross-scale piezoelectric screw motor operating in quasi-static and resonant states. Mechatronics, 2025.

Pan, Qiaosheng*, Design method and error analysis of 3D measurement system in accordance with the Abbe principle. Measurement, 2025.

Pan, Qiaosheng*, Array-structured microcapsule fibers for efficient fire extinguishing in confined spaces. Lab on A Chip, 2025.

Pan, Qiaosheng*, Development of a low-stiffness and high-dynamic micro–nano probe utilizing the eddy current damper. IEEE Sensors Journal, 2025.

Pan, Qiaosheng*, Advancements in manufacturing and applications of multi-dimensional micro-nano materials through interface shearing. (Review, Open Access).

Prof. Fazhi Song | Control Systems | Research Excellence Award

Published on by Electrical Engineering

Prof. Fazhi Song | Control Systems | Research Excellence Award

Professor | Harbin Institute of Technology | China

Dr. Fazhi Song, a Professor at the Harbin Institute of Technology specializing in control science, motion control, and precision engineering, is an accomplished researcher whose work advances high-end manufacturing and ultra-precision motion systems. He holds advanced degrees culminating in a Ph.D. in Control Science and Engineering, with academic training focused on system identification, learning control, and precision motion technologies. Throughout his professional career, he has led major research initiatives in motion generation, performance control, and accuracy retentivity for advanced manufacturing equipment, contributing to national and provincial projects and collaborating with leading industrial partners on precision motion systems. His research centers on high-precision mechanical servo systems, uncertainty-robust learning control, multi-DOF motion coordination, and advanced control strategies for lithography-level equipment, supported by a strong record of publications, patents, and technical innovations. He has authored numerous peer-reviewed articles, contributed to an academic monograph, and advanced methodologies widely cited in the fields of precision engineering and automation, reflected through 45 citations, 9 documents, and an h-index of the candidate. His achievements include significant awards from national academic societies recognizing technological innovation, along with contributions as a guest editor for respected journals, session chair for international conferences, and active membership in IEEE and major professional automation and instrumentation societies. Dr. Song’s leadership in research, editorial service, and professional engagement underscores his commitment to advancing ultra-precision control technologies and cultivating scientific excellence in the global engineering community.

Profiles: Scopus | ORCID

Featured Publications

Song, Fazhi, A compensation method for electromagnetic hysteresis: Application in linear reluctance actuator. J. Magn. Magn. Mater., 2025.*

Song, Fazhi, Crest factor minimization of multisine signals based on the Chebyshev norm approximation method: With application to wafer stage FRF identification. Results Eng., 2025.*

Song, Fazhi, Identification for Precision Mechatronics: An Auxiliary Model-Based Hierarchical Refined Instrumental Variable Algorithm. Int. J. Robust Nonlinear Control., 2025.*

Song, Fazhi, Beyond Performance of Learning Control Subject to Uncertainties and Noise: A Frequency-Domain Approach Applied to Wafer Stages. IEEE/CAA J. Autom. Sinica., 2025, 5 citations.*

 

Dr. Yong Bai | Photonic & Optoelectronic Devices | Innovative Research Award

Published on by Electrical Engineering

Dr. Yong Bai | Photonic & Optoelectronic Devices | Innovative Research Award

Assistant researcher | Aerospace Information Research Institute | China

Yong Bai, an Assistant Researcher at the Aerospace Information Research Institute of the Chinese Academy of Sciences, is a specialist in high-power laser parametric testing technology with a strong academic foundation supported by a PhD in Mechanical Engineering. He has developed significant expertise through his work on high-energy, continuous, and pulsed laser damage testers, contributing to the advancement of precision laser measurement systems and leading the development of a high-energy laser micro-spot dynamic characteristics measurement instrument. His professional experience includes multiple research projects, industry-related consultancy activities, and the creation of several patented or patent-pending technologies, reflecting both technical capability and a commitment to innovation. His research focuses on high-power laser diagnostic methods, emphasizing accuracy, anti-damage probe design, and solutions to nonlinear distortion challenges in complex laser environments. He has authored numerous publications in reputable indexed journals and serves as an editorial reviewer, demonstrating active engagement with the scientific community. His notable contribution includes proposing a highly anti-damage probe based on a micro-porous cavity structure combined with high-precision scattered-light sampling technology, significantly improving the reliability of high-energy laser testing. Through his scholarly work, technical achievements, and professional service, he has established a strong profile as a researcher dedicated to advancing laser measurement and diagnostics in support of scientific and engineering progress.

Profiles: Scopus | ORCID

Featured Publications

Yong Bai*, Innovative rotating hollow needle design for accurate measurement of high-power laser microspots. Optics and Laser Technology, Accepted.

Yong Bai*, Innovative rotating hollow needle design for accurate measurement of high-power laser microspots. Optics and Laser Technology, 2025, 1(1), Article ID pending.

Yong Bai*, Innovative rotating hollow needle design for accurate measurement of high-power laser microspots. Optics and Laser Technology, In Press.

Assoc. Prof. Dr. Jinpeng Guo | Power System Stability | Research Excellence Award

Published on by Electrical Engineering

Assoc. Prof. Dr. Jinpeng Guo | Power System Stability | Research Excellence Award

Associate Professor | Hohai University | China

Dr. Jinpeng Guo, an Associate Professor at the School of Electrical and Power Engineering at Hohai University, is a specialist in new energy power systems with expertise in renewable energy grid integration, stability analysis, and advanced control strategies for converter-dominated networks. He holds a doctoral degree in Electrical and Computer Engineering from McGill University, a graduate degree in Electrical Engineering from Southeast University, and a bachelor’s degree in Electrical Engineering and Automation from Chongqing University, further enriched by an academic exchange in electrical engineering at Tsinghua University. His professional experience includes leading and contributing to major research initiatives on frequency characteristics, rotor-angle stability, offshore wind power integration through VSC-HVDC systems, synchronous condenser optimization, and wide-area damping control, serving as both project leader and technical director in national and industry-supported programs. Dr. Guo’s research focuses on data-driven modeling, inertia estimation, dynamic stability enhancement, and coordinated active–reactive power control, supported by publications in reputable journals and international conferences. His scholarly contributions advance power system resilience, renewable energy operational security, and the development of intelligent control methods for modern electric grids. He has been recognized through competitive research funding and active participation in collaborative international projects, professional networks, and academic communities. His academic profile includes 3 citations, 8 documents, and an h-index of 1.

Profiles: Scopus | ORCID

Featured Publications

Guo, Jinpeng*, Quantitative evaluation and sensitivity analysis of carbon emission reduction costs based on optimal scheduling of electric-thermal integrated energy systems. Electric Power Systems Research, 2026, Article in press.

Guo, Jinpeng*, Improved vector current control for the VSC-HVDC converter connected to a very weak AC grid. IEEE Transactions on Circuits and Systems I: Regular Papers.

Guo, Jinpeng*, Data-driven methods in modern power system stability and security. Smart Cyber-Physical Power Systems.

Assoc. Prof. Dr. Huibin Jia | Smart Grids and Microgrids | Research Excellence Award

Published on by Electrical Engineering

Assoc. Prof. Dr. Huibin Jia | Smart Grids and Microgrids | Research Excellence Award

Associate Professor | North China Electric Power University | China

Huibin Jia, an Associate Professor in the Department of Electronic and Communication Engineering at North China Electric Power University, is a specialist in smart grid communication and intelligent power system technologies whose academic background includes advanced degrees in electronic engineering with a focus on communication systems and data‐driven power applications. His professional experience spans leading roles in research and industry-linked projects involving fault traveling wave location, cyber-physical system security, power grid risk prevention, and simulation analysis under extreme operating conditions, complemented by active participation in national and provincial research initiatives. He has contributed extensively to the advancement of smart grid big data analytics, Internet of Things integration, artificial intelligence applications in power systems, and high-precision fault location techniques, resulting in more than fifty publications, a technical book, and numerous patented innovations. His scholarly contributions are further strengthened by professional membership in IEEE, collaborative engagements across funded research programs, and recognized expertise that supports both academic progress and practical advancements in power system reliability. 652 Citations, 75 Documents, 13 h-index, View h-index button is disabled in preview mode.

Profiles: Scopus | ORCID

Featured Publications

Huibin Jia, Smart grid communication enhancement through integrated IoT architectures and AI-driven data analytics. Int. J. Electr. Power Syst., Accepted.


Huibin Jia, Fault traveling wave location and cyber-physical security protection models for intelligent power grids. Electr. Power Syst. Res., In Press.


Huibin Jia, Big data-assisted fault diagnosis and operational reliability optimization in modern smart grid environments. J. Mod. Power Eng., Publication Ongoing.**

Prof. Dr. Zhi-Hua Yang | Wearable Electronics | Research Excellence Award

Published on by Electrical Engineering

Prof. Dr. Zhi-Hua Yang | Wearable Electronics | Research Excellence Award

Professor | Harbin institute of technology | China

Professor Zhihua Yang, a leading scholar at the Harbin Institute of Technology, is recognized for his expertise in advanced ceramics and composite materials within the School of Materials Science and Engineering, where he contributes to both foundational research and high-impact industrial innovation. With advanced degrees in materials science and specialization in ceramic and composite systems, he has developed a strong professional portfolio encompassing major research projects on structural-functional integrated ceramics, additive manufacturing, and ceramic–metal integration technologies for semiconductor packaging and electronic circuits. His experience includes directing significant research initiatives, providing specialized consulting for semiconductor equipment component development, and fostering academic collaborations with prominent institutions. Professor Yang has authored influential monographs, contributed to national-level publications, published more than 250 peer-reviewed papers, and secured 70 authorized national invention patents, demonstrating his leadership in translating materials research into technological applications. His professional recognitions are strengthened by his service as Associate Editor of the Journal of Applied Ceramic Technology, Editorial Board Member of the Journal of Advanced Ceramics, and council member in key committees of the Chinese Ceramic Society and the Chinese Mechanical Engineering Society, reflecting his commitment to advancing the field through scholarly excellence, professional service, and sustained research contributions.

Profile: ORCID

Featured Publications

Zhihua*, Review activity for ACS Applied Electronic Materials. ACS Appl. Electron. Mater., Review, American Chemical Society.

Zhihua*, Review activity for ACS Applied Electronic Materials. ACS Appl. Electron. Mater., Review, American Chemical Society.

Zhihua*, Review activity for Tribology International. Tribol. Int., Review, Elsevier Editorial.

Ms. Xiaohua Li | Machine Learning | Excellence in Research Award

Published on by Electrical Engineering

Ms. Xiaohua Li | Machine Learning | Excellence in Research Award

Associate Professor | Shanghai Electric Power University | China

Dr. Li Xiaohua, a distinguished Professor at Sichuan University and leading expert in materials science and structural engineering, is renowned for advancing high-performance composite materials and sustainable structural systems. She holds advanced degrees in materials engineering with specialization in composite behavior and structural performance, complemented by extensive experience in academic leadership, project supervision, and collaborative research initiatives. Her professional portfolio includes directing major institutional projects, mentoring interdisciplinary teams, and contributing to engineering innovations that strengthen the reliability and resilience of modern structures. Dr. Li’s research focuses on composite structures, fire-resistant materials, mechanical behavior, and performance optimization, supported by 297 citations, 34 scholarly documents, and an h-index of 11, reflecting her growing global impact. She has authored influential publications, contributed to high-level research panels, and advanced knowledge dissemination through editorial responsibilities and membership in professional engineering societies. Recognized for excellence in research, innovation, and service, she also holds relevant professional certifications that underscore her commitment to scientific rigor and continued advancement in the engineering sciences.

Profile: Scopus

Featured Publications

Li Xiaohua*, Probabilistic forecasting of coal consumption for power plants under deep peak shaving conditions using Informer with DDPM-based uncertainty modeling. Int. J. Electr. Power Energy Syst., 2025.

Li Xiaohua*, Electromagnetic vibration characteristics of permanent magnet synchronous motors with segmented grain-oriented electrical steel teeth–yoke.

Li Xiaohua, Research on core loss prediction of low-frequency transformer based on Grey Wolf optimisation algorithm optimised Back Propagation neural network. IET Electr. Power Appl., 2025.

 










































































 




	


	

	






	
	

		


Dr. Salam Bani Hani | Nursing and Medical Feilds | Best Researcher Award
			

				Published on  by Electrical Engineering			

		
	


	

		



	
Dr. Salam Bani Hani | Nursing and Medical Feilds | Best Researcher Award


Assisstant Professor | Irbid National University | Jordan
















Dr. Salam Bani Hani is an Assistant Professor and Head of the Nursing Department at Irbid National University, recognized for her expertise in nursing research, healthcare quality, digital health, and clinical education. She holds a PhD in Nursing Philosophy with a specialization in large-scale data applications for predicting cardiovascular conditions, an MSc in Nursing Service Administration, and a BSc in Nursing. Her professional experience includes academic leadership, clinical instruction across diverse nursing specialties, patient and family education, and clinical practice in emergency and critical care settings. Dr. Bani Hani’s research focuses on cardiovascular disease prediction using artificial intelligence, nursing education, digital health literacy, patient safety, chronic disease management, and public health issues affecting vulnerable communities. She has an extensive record of publications across reputable Scopus-indexed journals, contributing empirical studies, systematic reviews, and interdisciplinary collaborations. She has delivered multiple professional workshops on life support, documentation, pain management, and clinical communication, and has actively participated in scientific conferences as a speaker, trainer, and rapporteur. Her professional service includes reviewing for peer-reviewed journals, contributing to academic committees, and supporting program development and training initiatives. She has received national recognition, including a distinguished nursing shield, and has earned certifications that enhance her clinical and academic proficiency. Dr. Bani Hani’s scholarly impact is reflected in 333 citations, 63 published documents, and an h-index of 8.


Profile: Scopus | ORCID


Featured Publications


Bani Hani, Salam, Jordanian nursing students’ perceptions of the compassionate actions of their clinical instructors: a mixed-methods study. BMC Nursing, 2025.


Bani Hani, Salam, Barriers affecting safe practice of oxygen administration to critical ill children. Journal of Pediatric Nursing, 2025.


Bani Hani, Salam, Preoperative anxiety, postoperative pain tolerance and analgesia consumption: A prospective cohort study. Journal of Perioperative Practice, 2025.


Bani Hani, Salam, Knowledge and practices of Jordanian university students regarding food safety and handling. Nutrition and Food Science, 2025.


Bani Hani, Salam, Depression and Anxiety among Adolescents with Type 1 Diabetes Mellitus: Systematic Review of Literature. The Open Nursing Journal, 2025.


























	


	

	






	
	

		


Prof. Xianglong Xu | Artificial Intelligence Prediction Tools | Research Excellence Award
			

				Published on  by Electrical Engineering			

		
	


	

		



	
Prof. Xianglong Xu | Artificial Intelligence Prediction Tools | Research Excellence Award


Research Professor | Shanghai University of Traditional Chinese Medicine | China
















Dr. Xianglong Xu, a Research Professor at Shanghai University of Traditional Chinese Medicine specializing in AI-enabled epidemiology and predictive health analytics, holds a Ph.D. in Epidemiology with advanced expertise in chronic disease modelling and public health informatics. His professional experience spans roles as a young researcher, master’s supervisor, and project leader, contributing to multidisciplinary initiatives that integrate artificial intelligence with clinical practice and community health systems. Dr. Xu has led the development of innovative digital health tools, large-scale preventive health databases, and collaborative programs with hospitals and public health centers, strengthening data-driven decision-making across diverse populations. His research focuses on chronic disease risk assessment, AI-driven health prediction models, digital health evaluation, and the integration of Traditional Chinese Medicine concepts into modern epidemiology, supported by significant scholarly output and impactful scientific contributions. He has published extensively in peer-reviewed journals, contributed to theoretical and applied advancements in intelligent health analytics, and served on editorial boards while reviewing for leading international journals. His professional affiliations include membership in the International Epidemiological Association, IEEE and EMBS, national rehabilitation committees, and multiple scientific societies, complemented by recognitions across national and international platforms. 1,441 Citations, 71 Documents, 21 h-index.


Profiles: Scopus 


Featured Publications


Xu, Xianglong*, Urban and rural disparities in stroke prediction using machine learning among Chinese older adults. Scientific Reports, 2025.


Xu, Xianglong*, External validation of a web- and artificial intelligence-based HIV/STI risk assessment tool: performance evaluation using data from Sydney sexual health centre. BMC Infectious Diseases, 2025.


Xu, Xianglong*, Anxiety responses and testing intentions among gay and bisexual men using an AI-powered HIV/STI risk assessment tool: a quasi-experimental study. BMC Public Health, 2025.


Xu, Xianglong, Comparative analysis of cardiometabolic multimorbidity predictors in China and the USA: A machine learning approach. Diabetes Research and Clinical Practice, 2025.


Xu, Xianglong, Development of a web-based tool using machine learning algorithms to improve adherence to diagnostic colonoscopy among middle-aged and elderly adults in colorectal cancer screening program. Annals of Epidemiology, 2025.


Xu, Xianglong, Determinants and geographical variations in oral traditional Chinese medicine use among middle-aged and elderly chronic adults in China: A cross-sectional study. European Journal of Integrative Medicine, 2025.


Xu, Xianglong, Geographical distribution disparities and prediction of health satisfaction among middle-aged and elderly adults in China: An analysis based on national data. Annals of Epidemiology, 2025.