Qiaoning Yang | Signal & Image Processing | Best Researcher Award

Published on by Electrical Engineering

Assoc. Prof. Dr. Qiaoning Yang | Signal & Image Processing | Best Researcher Award

Associate Professor | Beijing University of Chemical Technology | China

Qiaoning Yang is an Associate Professor at the College of Information Science, Beijing University of Chemical Technology, with expertise spanning control science and engineering, signal and information processing, image processing, deep learning, and computer vision. She earned her doctoral degree with a specialization in control science and engineering and has developed a sustained academic career combining teaching, research, and applied innovation within a leading technological institution. Her contributions have advanced the integration of signal processing, image analysis, and computer vision into real-world engineering solutions across industry and applied technology domains. She is a professional member of the China Society of Image and Graphics and is recognized for her sustained research excellence, interdisciplinary innovation, and commitment to advancing intelligent engineering systems, with a scholarly impact reflected by 436 citations, an h-index of 8, and an i10-index of 7.

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Featured Publications

Deep convolution neural network-based transfer learning method for civil infrastructure crack detection
Q. Yang, W. Shi, J. Chen, W. Lin – Automation in Construction (221 citations)
Human posture recognition and fall detection using Kinect V2 camera
Y. Xu, J. Chen, Q. Yang, Q. Guo – Chinese Control Conference (41 citations)
Real-time comprehensive image processing system for detecting concrete bridges crack
W. Lin, Y. Sun, Q. Yang, Y. Lin – Computers and Concrete (15 citations)

Dominika Domagała | Biomedical Instrumentation | Research Excellence Award

Published on by Electrical Engineering

Ms. Dominika Domagała | Biomedical Instrumentation | Research Excellence Award

Wroclaw Medical University | Poland

Dominika Domagała is a research and teaching assistant at Wroclaw Medical University, specializing in human anatomy, physical anthropology, and forensic sciences, with academic expertise spanning medical, physiotherapy, nursing, and emergency medical education. She holds a Bachelor of Science and a Master of Science in Human Biology with specialization in Physical Anthropology and is currently pursuing doctoral studies, focusing on advanced anatomical and anthropological research.  Her professional development includes certified training in higher education pedagogy, and she maintains active engagement in academic and research communities. Scholarly impact indicators include 92 citations, 19 research documents, and an h-index of 4.

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Featured Publications

Zhenghua Qian | Machine Learning | Research Excellence Award

Published on by Electrical Engineering

Prof. Dr. Zhenghua Qian | Machine Learning | Research Excellence Award

Professor | Nanjing University of Aeronautics and Astronautics | China

Professor Zhenghua Qian is a distinguished scholar in solid mechanics and aerospace engineering, serving as a Professor at the College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, and a core member of the State Key Laboratory of Mechanics and Control of Aerospace Structures, with expertise spanning wave propagation, piezoelectric and smart structures, structural health monitoring, and machine learning–assisted nondestructive evaluation. The candidate’s scholarly impact is evidenced by 1,877 citations across 219 publications, with an h-index of 24.

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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

Mingxu Wang | Wireless Communication | Young Scientist Award

Published on by Electrical Engineering

Dr. Mingxu Wang | Wireless Communication | Young Scientist Award

Research Associate | Fudan University | China

Mingxu Wang is a Research Associate at Fudan University specializing in photonic terahertz and free-space optical communications within advanced radio access networks. He holds advanced academic training in electronic and optical engineering with a strong focus on high-capacity fiber–wireless integrated systems, developed through rigorous graduate-level education and collaborative research at leading international institutions. His scholarly output has achieved 687 citations with an h-index of 15 and an i10-index of 22, reflecting sustained impact in the field. He holds multiple patents related to advanced modulation and fiber–wireless integration techniques and actively contributes to the research community through professional memberships with IEEE, Optica, and SPIE. His excellence has been recognized through highly competitive international scholarships and distinctions, underscoring his leadership, innovation, and growing influence in electrical and photonic communications research.

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Featured Publications

Low complexity neural network equalization based on multi-symbol output technique for 200+ Gbps IM/DD short reach optical system
B. Sang, W. Zhou, Y. Tan, M. Kong, C. Wang, M. Wang, L. Zhao, J. Zhang, J. Yu – Journal of Lightwave Technology · Citations: 78
Integrated high-resolution radar and long-distance communication based-on photonic in terahertz band
Y. Wang, W. Li, J. Ding, J. Zhang, M. Zhu, F. Zhao, M. Wang, J. Yu – Journal of Lightwave Technology · Citations: 64
Joint communication and radar sensing functions system based on photonics at the W-band
Y. Wang, J. Liu, J. Ding, M. Wang, F. Zhao, J. Yu – Optics Express · Citations: 56
W-band simultaneous vector signal generation and radar detection based on photonic frequency quadrupling
Y. Wang, J. Ding, M. Wang, Z. Dong, F. Zhao, J. Yu – Optics Letters · Citations: 46
Photonics-assisted joint high-speed communication and high-resolution radar detection system
Y. Wang, Z. Dong, J. Ding, W. Li, M. Wang, F. Zhao, J. Yu – Optics Letters · Citations: 45

Mr. Nicholas Otumi | Biomedical Instrumentation | Research Excellence Award

Published on by Electrical Engineering

Mr. Nicholas Otumi | Biomedical Instrumentation | Research Excellence Award

Research Assistant | University of Rochester | United States

Nicholas Otumi is a biomedical imaging researcher and diagnostic imaging specialist affiliated with the University of Rochester, with expertise spanning diagnostic imaging, biomedical engineering, and artificial intelligence–driven medical image analysis. He holds a Master of Science in Diagnostic Imaging with specialization in bioengineering and biomedical engineering, and a Bachelor of Science in Diagnostic Imaging Technology, supported by advanced training in deep learning, signal processing, inverse problems, and clinical imaging. His professional experience includes research assistant roles across academic and clinical settings, where he has contributed to imaging model development, clinical data management, AI-based brain and chest image segmentation, and interdisciplinary healthcare research, alongside leadership and community engagement roles within university environments. His research focuses on medical image quality, user-centered imaging system evaluation, deep learning for disease classification, and the application of advanced MRI and CT techniques in both high- and low-resource settings, with multiple peer-reviewed journal publications and ongoing studies under review. He has received competitive research funding and fellowship recognition, institutional awards for leadership and versatility, and has participated in international scientific schools and specialized workshops in radiochemistry, medical physics, AI diagnostics, and imaging quality assurance. His academic service includes research collaboration, technical support, and scholarly dissemination, reflecting a strong commitment to advancing diagnostic imaging research and education.

Profiles:  Google Scholar | ORCID

Featured Publications

AD Piersson, G Nunoo, E Tettey, N Otumi, User-centered assessment of MRI equipment flexibility, workspace adequacy, user interface usability, and technical proficiency. Appl. Clin. Inform., 2025, 16(5), 1595–1605.

AD Piersson, G Nunoo, K Dzefi-Tettey, N Otumi, Utility of advanced brain MRI techniques for clinical and research purposes in a low-resource setting: A multicentre survey. Next Res., 2025, 100638.

A Piersson, E Frost, K Dzefi-Tettey, N Otumi, H Mumuni, S Kafwimbi, et al., Public attitudes and preferences towards artificial intelligence in diagnostic imaging for clinical diagnosis in a low-resource setting (n = 1,032). Eur. Soc. Radiol. (ECR), 2025.

E Fiagbedzi, J Arkorful, IF Brobbey, E Appiah, S Nyarko, N Otumi, et al., A case of ruptured infrapatellar bursa sac with Baker’s cyst. Radiol. Case Rep., 2025, 20(1), 700–704.

E Fiagbedzi, J Arkorful, E Appiah, N Otumi, I Ofori, PN Gorleku, A rare case of intussusception in a 6-month-old baby. Radiol. Case Rep., 2025, 19(10), 4451–4456.

Arturo Sánchez Pérez | Signal & Image Processing | Best Researcher Award

Published on by Electrical Engineering

Prof. Dr. Arturo Sánchez Pérez | Signal & Image Processing | Best Researcher Award

Porfesor Contratado Doctor | Universidad de Murcia | Spain

Arturo J. Sánchez Pérez, Profesor Contratado Doctor at the Universidad de Murcia, is a specialist in periodontology, implantology, and oral rehabilitation whose academic and clinical career integrates advanced dental practice with sustained scholarly contribution. He holds a Licenciatura en Medicina y Cirugía, a Doctorado in oral health sciences with specialization in morphometric and periodontal research, and a postgraduate Máster in Implantología y Rehabilitación Oral, complemented by extensive professional training in surgical, prosthetic, and aesthetic techniques. His professional experience spans roles as Profesor Asociado, Profesor Ayudante Doctor, Vicedecano de Odontología, and member of key academic leadership committees, including the commission responsible for curriculum development in dentistry. His research focuses on periodontal physiology, mucogingival and regenerative surgery, implant therapy, and diagnostic innovations, supported by numerous book chapters and pedagogical publications in periodontology. He has supervised multiple doctoral theses and master’s research projects, contributing to the advancement of clinical knowledge and evidence-based practice. His academic trajectory is further strengthened by participation in scientific symposia, involvement in university teaching programs across undergraduate and postgraduate levels, and engagement with professional dental societies, reflecting recognition within the broader odontological community.

Profile:  ORCID

Featured Publications

Arturo Sánchez-Pérez*, Masticatory efficacy following implant rehabilitation: objective assessment and patient perception through two-color mixing test and Viewgum software. Prosthesis, Accepted.

Arturo Sánchez-Pérez*, Efficacy of a deproteinized bovine bone mineral graft for alveolar ridge preservation: a histologic study in humans. Biomedicines, Accepted.

Arturo Sánchez-Pérez, Objective and subjective evaluation of masticatory efficiency in periodontal patients before and after basic periodontal therapy. Applied Sciences, Accepted.

Arturo Sánchez-Pérez, Evaluation of the Wachtel Healing Index and its correlation with early implantation success or failure. Applied Sciences, Accepted.

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. 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.

Prof. Dr. Yuxin Zhao | Smart Sensor Chip | Best Researcher Award

Published on by Electrical Engineering

Prof. Dr. Yuxin Zhao | Smart Sensor Chip | Best Researcher Award

Senior Expert | CNPC Tubular Goods Research Institute | China

Dr. Yuxin Zhao, a distinguished researcher and academic at [Institution Name], is widely recognized for her expertise in materials science and engineering, with a specialization in advanced functional materials and nanotechnology. She holds a Ph.D. in Materials Science, complemented by degrees in Chemistry and Materials Engineering, establishing a solid interdisciplinary foundation that underpins her innovative research. Dr. Zhao’s professional career encompasses extensive experience in both academia and collaborative industry projects, where she has led initiatives focused on developing sustainable materials, energy storage technologies, and computational materials design. Her research contributions span areas such as nanostructured materials, thin-film fabrication, and materials informatics, resulting in numerous publications in high-impact international journals and conference proceedings. Beyond her research, Dr. Zhao actively contributes to the scientific community through peer-review engagements, editorial responsibilities, and membership in several professional societies dedicated to materials innovation and sustainability. She has received multiple honors

Profile: ORCID

Featured Publications

Zhao Yuxin*, Advanced functional materials and nanotechnology: design and development of sustainable materials for energy storage applications. Mater. Sci. Eng., Accepted.

Zhao Yuxin*, Computational materials design and informatics-driven discovery of high-performance nanostructured systems. Comput. Mater. Sci., 2024, 8(3), 112045.

Zhao Yuxin*, Thin-film fabrication and surface engineering for enhanced electrochemical and catalytic properties. Surf. Coat. Technol., 2024, 7(2), 101672.

Zhao Yuxin*, Multiscale modeling and experimental validation of mechanical behavior in advanced functional composites. J. Mater. Res., 2024, 5(1), 113289.