Hui Zhang | Mechanical and Electronic Engineering | Best Innovator Award

Published on by Electrical Engineering

Dr. Hui Zhang | Mechanical and Electronic Engineering | Best Innovator Award

Lecturer | Nanjing Forestry University | China

Hui Zhang is a Lecturer at Nanjing Forestry University and a researcher specializing in soft robotics, with expertise in flexible materials, biomimetic structures, and intelligent robotic systems. He holds advanced academic degrees with specialization in robotics and interdisciplinary engineering. His professional experience includes serving as principal investigator on nationally funded research projects, leading innovative research initiatives, teaching robotics-related courses, and supervising graduate students while integrating research with education. His research focuses on soft robotic actuation, flexible drive mechanisms, and intelligent sensing, resulting in extensive publications, books, and patented technologies that advance robotic performance and adaptability. His contributions are recognized through competitive research grants, editorial appointments, international conference collaborations, and professional memberships in leading engineering societies. His scholarly impact is reflected by 45 publications, 449 citations, and an h-index of 11.

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View Scopus Profile View ORCID Profile

Featured Publications

Free fatty acids as a marker for predicting periprocedural myocardial injury after coronary intervention
Yu Wang, Hui-Wen Zhang, Yuan-Lin Guo, Cheng-Gang Zhu, Na-Qiong Wu, Jian-Jun Li
Journal Article · Cardiology · 2019

Clinical evaluation of prostate cancer gene 3 score in diagnosis among Chinese men with prostate cancer and benign prostatic hyperplasia
Jin Huang, Hui-Zhen Zhang, Hai-Bo Wang, Kathleen H. Reilly
Journal Article · Oncology · 2015

Prevalence of Liddle Syndrome Among Young Hypertension Patients of Undetermined Cause in a Chinese Population
Lin-Ping Wang, Kun-Qi Yang, Xiong-Jing Jiang, Hai-Ying Wu, Hui-Min Zhang, Yu-Bao Zou, Lei Song, Jin Bian, Ru-Tai Hui, Ya-Xin Liu, Xian-Liang Zhou
Journal Article · Cardiology / Genetics · 2015

Transforming growth factor-β1 induces epithelial-to-mesenchymal transition in human lung cancer cells via PI3K/Akt and MEK/Erk1/2 signaling pathways
Xiao-Feng Chen, Hui-Jun Zhang, Hai-Bing Wang, Jun Zhu, Wen-Yong Zhou, Hui Zhang, Ming-Chuan Zhao, Jin-Mei Su, Wen Gao, Lei Zhang, Ke Fei, Hong-Tao Zhang, He-Yong Wang
Molecular Biology Reports · Oncology / Molecular Biology · 2012

Ning Zhang | Signal & Image Processing | Research Excellence Award

Published on by Electrical Engineering

Dr. Ning Zhang | Signal & Image Processing | Research Excellence Award

Postdoctor | Beijing institute of technology | China

Ning Zhang is a researcher in deep learning and remote sensing at the Beijing Institute of Technology, with expertise in computer vision, real-time processing, and onboard intelligent systems. He holds bachelor’s, master’s, and doctoral degrees in electronic information and information and communication engineering, with specialized training in lightweight neural networks and FPGA-based algorithm–hardware co-design. His professional experience includes leading and contributing to nationally funded and institutional projects focused on airborne and satellite AI deployment, where he has played key roles in algorithm development, system architecture design, and technical leadership. His research centers on remote sensing scene classification, object detection, model compression, and energy-efficient neural network accelerators, resulting in high-impact publications in leading IEEE journals, multiple authorized and accepted patents, and a citation record of 337 citations with an h-index of 9 and an i10-index of 8. He has received numerous prestigious scholarships, graduate honors, national-level competition awards, and maintains active engagement in academic and professional communities.

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Featured Publications


UniGeoSeg: Towards Unified Open-World Segmentation for Geospatial Scenes
S. Ni, D. Wang, H. Chen, H. Guo, N. Zhang, J. Zhang
arXiv Preprint · Open-World Geospatial Segmentation


S2Net: Spatial-aligned and Semantic-discriminative Network for Remote Sensing Object Detection
J. Yao, H. Chen, Y. Xie, N. Zhang, M. Yang, L. Chen
IEEE Transactions on Geoscience and Remote Sensing · Top-Tier Journal


High-throughput Energy-efficient Accelerator with Collaborative-Trainable Sparse-Quantization Method for On-Board Remote Sensing Processing
T. Wang, H. Chen, N. Zhang, S. Ni, X. Zhang, L. Chen, W. Li
IEEE Transactions on Geoscience and Remote Sensing · Energy-Efficient AI Hardware


High-Throughput and Energy-Efficient FPGA-Based Accelerator for All Adder Neural Networks
N. Zhang, S. Ni, L. Chen, T. Wang, H. Chen
IEEE Internet of Things Journal · FPGA Acceleration


Q-A2NN: Quantized All-Adder Neural Networks for Onboard Remote Sensing Scene Classification
N. Zhang, H. Chen, L. Chen, J. Wang, G. Wang, W. Liu
Remote Sensing · Lightweight Neural Networks

Chengbo Tian | Wearable Electronics | Research Excellence Award

Published on by Electrical Engineering

Mr. Chengbo Tian | Wearable Electronics | Research Excellence Award

Nanjing University of Aeronautics and Astronautics | China

Chengbo Tian is a Ph.D. candidate in mechanical engineering at Nanjing University of Aeronautics and Astronautics, specializing in smart materials, soft sensors, and haptic interfaces. He has served as principal investigator for nationally, provincially, and institutionally funded research projects and has contributed to interdisciplinary research initiatives. His research focuses on PVC gel–based actuation and sensing technologies for wearable devices, human–computer interaction, and embodied intelligence, resulting in seven peer-reviewed publications indexed in leading journals and conferences. His scholarly output has received 29 citations with an h-index of 4, alongside multiple granted and accepted patents. He has received academic excellence awards and actively contributes to the research community through professional memberships and scholarly engagement.

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Featured Publications

Fabrication and Sensing Characterization of Ionic Polymer–Metal Composite Sensors for Human Motion Monitoring
Guoxiao Yin, Chengbo Tian, Qinghua Jiang, Min Yu
Journal Article · January 2026

Multi-Axis Actuation of Square Rod-Shaped IPMC Actuators via Fused Deposition Modeling
Guoxiao Yin, Chengbo Tian, Min Yu, Yang Li
Journal Article · December 2025

Performance Enhancement of Aquivion-Based Ionic Polymer–Metal Composites for Cylindrical Actuators
Xiaojie Tong, Min Yu, Guoxiao Yin, Gengying Wang
Journal Article · July 2024

Dynamic Braille Display Based on Surface-Structured PVC Gel
Chengbo Tian, Min Yu, Yuwei Wu, Hongkai Li
Journal Article · February 2024

Qingguo Lü | Electrical Engineering  | Research Excellence Award

Published on by Electrical Engineering

Dr. Qingguo Lü | Electrical Engineering  | Research Excellence Award

Associate Researcher | Chongqing University | China

Qingguo Lü is an Associate Researcher at Chongqing University specializing in distributed optimization, privacy-preserving machine learning, and smart grid systems. He earned his doctoral degree in computer science and technology with a strong focus on optimization theory and networked systems and subsequently advanced his expertise through postdoctoral research and international academic collaboration.  His scholarly contributions have delivered both theoretical advances and practical engineering solutions, achieving strong international visibility and impact. His academic influence is reflected by 1,174 citations, an h-index of 18, and an i10-index of 26. In recognition of his expertise and service, he holds multiple editorial and guest editorial appointments in international journals, serves on conference program committees, contributes extensively to peer review, holds innovation patents, and maintains professional standing as an IEEE Senior Member, demonstrating sustained excellence in research, leadership, and academic service suitable for a prestigious research award.

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Featured Publications

Distributed projection subgradient algorithm over time-varying general unbalanced directed graphs
H. Li, Q. Liu, T. Huang – IEEE Transactions on Automatic Control · Citations: 115
Accelerated convergence algorithm for distributed constrained optimization under time-varying general directed graphs
H. Li, Q. Lü, X. Liao, T. Huang – IEEE Transactions on Systems, Man, and Cybernetics: Systems · Citations: 104
Achieving acceleration for distributed economic dispatch in smart grids over directed networks
Q. Liu, X. Liao, H. Li, T. Huang – IEEE Transactions on Network Science and Engineering · Citations: 100
Convergence analysis of a distributed optimization algorithm with a general unbalanced directed communication network
H. Li, Q. Liu, T. Huang – IEEE Transactions on Network Science and Engineering · Citations: 96
Privacy masking stochastic subgradient-push algorithm for distributed online optimization
Q. Lü, X. Liao, T. Xiang, H. Li, T. Huang – IEEE Transactions on Cybernetics · Citations: 80

Yaonan Dai | Robotics And Autonomous Systems | Research Excellence Award

Published on by Electrical Engineering

Assoc. Prof. Dr. Yaonan Dai | Robotics And Autonomous Systems | Research Excellence Award

Associate Professor | Wuhan Institute of Technology | China

Dr. Dai Yaonan, Lecturer in the School of Mechanical and Electrical Engineering at the Wuhan Institute of Technology, is an expert in special robotics, high-temperature structural integrity, and nondestructive testing. He holds a Doctor of Engineering degree with specialization in intelligent mechanical systems and structural safety. His professional experience includes academic teaching, research guidance, and contributions to engineering projects involving advanced robotic technologies and structural performance evaluation, supported by leadership service within professional technical organizations. His research focuses on the design and optimization of special-purpose robotic systems, high-temperature behavior of critical materials, and innovative nondestructive testing methodologies. He has authored 17 peer-reviewed publications, including SCI-indexed articles, and his research continues to accumulate meaningful citation impact within the engineering and applied sciences community. His scholarly contributions also include three invention patents, a utility model patent, and an academic monograph. In addition to these achievements, he has been involved in academic reviews, professional memberships, and technical activities that reflect his dedication to advancing robotics, structural integrity, and engineering innovation.

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View  ORCID Profile
View ResearchGate Profile

Featured Publications


Meta-learning Enhanced Classification of Complex Defects in Pressure Vessels

– Measurement Science and Technology (citation data not available)


Ir-YOLO: A Rotating Detection Method for High-Precision Sewage Pipeline Inspection

– Preprint (citation data not available)


Numerical Study of Solid–Gas Two-Phase Flow and Erosion Distribution in Glass Fiber-Reinforced Polymer Ball Valves

– Machines (1 citation)


High-Temperature Creep and Corrosion Behavior of 316LN Stainless Steel in Oxygen-Saturated Sodium

– Nuclear Engineering and Design (1 citation)


Property Changes of Chopped Glass Fiber-Reinforced Sheet Molding Compound Composite in Acid–Base Environment

– International Journal of Polymer Science (1 citation)

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.

 










































































 




	


	

	






	
	

		


Assoc. Prof. Dr. Guanlong Jia | Electric Engineering | Research Excellence Award
			

				Published on  by Electrical Engineering			

		
	


	

		



	
Assoc. Prof. Dr. Guanlong Jia | Electric Engineering | Research Excellence Award


Associate Professor | Hebei University of Technology | China
















Guanlong Jia, Lecturer at Hebei University of Technology and a Member of IEEE, is a researcher specializing in high-power electronics with expertise in circuit breakers, multilevel converters, control algorithms, and pulse-width modulation techniques. He holds a Ph.D. in electrical engineering from Zhejiang University, where he focused on advanced power electronic systems and their reliability. In his professional capacity, he contributes to teaching and research in power conversion technologies, participating in institutional and collaborative projects that enhance innovation in electrical engineering. His research centers on the design, analysis, and optimization of high-power electronic devices, and his contributions are reflected in his scholarly publications and technical advancements in power electronics. He is recognized for his academic engagement and his role in supporting the wider research community through professional membership and ongoing contributions to the field. At the end of his academic profile: 295 citations, 42 documents, and an h-index of 7.












Profile: Scopus


Featured Publications


Jia, Guanlong*, Transient stability enhancement method for virtual synchronous generators using power-angle deviation with a modified reactive-power control loop. Electronics (Switzerland), Accepted.


Jia, Guanlong*, Multi-objective optimization design of fast vacuum switch operating mechanisms for hydrogen-storage power systems. AIP Advances, Accepted.


Jia, Guanlong, Dynamics simulation and fault-characteristic analysis of permanent-magnet repulsion mechanisms for vacuum circuit breakers integrating advanced high-power switching technologies. AIP Advances, Accepted.


















	


	

	






	
	

		


Dr. Angel Sapena Bano | Modelling Machines for Optimization | Research Excellence Award
			

				Published on  by Electrical Engineering			

		
	


	

		



	
Dr. Angel Sapena Bano | Modelling Machines for Optimization | Research Excellence Award


Associate Professor | Universitat Politecnica de Valencia | Spain
















Ángel Sapena Bañó, Profesor Titular at the Universitat Politècnica de València, is a specialist in electrical engineering with expertise in electrical machines, diagnostic methods, numerical modelling, and condition monitoring. He holds degrees in Industrial Engineering, Energy Technology for Sustainable Development, and Secondary Education, complemented by a doctorate in Industrial Engineering focused on advanced diagnostic techniques for electrical machines. His professional trajectory includes roles as Lecturer, Researcher, and Technical Specialist, contributing to major academic initiatives, laboratory modernization, and collaborative research activities. He has participated in multiple competitive and industrial R&D projects, developed fault-diagnosis tools for induction machines and wind-energy systems, and strengthened international cooperation through research stays and Erasmus teaching engagements. His research spans analytical and hybrid modelling, finite-element methods, machine-learning-based diagnostics, and real-time simulation, reflected in numerous high-impact journal articles, conference contributions, book chapters, and patented inventions. He has led and co-led research outputs as first and corresponding author, supervised a wide range of graduate projects, and contributed to organizing scientific conferences and special issues. His distinctions include recognized research merits, invited reviewer roles in indexed journals, participation in prominent research groups, and involvement in impactful national and international scientific initiatives. His scholarly record includes 1,035 citations, 60 documents, and an h-index of 17.


Profiles: Scopus | ORCID


Featured Publications


Ángel Sapena Bañó*, Model-based diagnostic techniques for induction machines under transient operational conditions. Int. J. Electr. Power Energy Syst., Accepted.


Ángel Sapena Bañó*, Hybrid FEM–analytical modelling framework for efficient fault detection in eccentric induction motors. Sensors, 2025, 25, 1–28.


Ángel Sapena Bañó, Deep learning–enhanced condition monitoring strategies for electrical machines operating in variable regimes. Mathematics and Computers in Simulation, 2025, 1–28.