Hamideh Rabiei | Smart Sensors and Sensor Fusion | Innovative Research Award

Innovative Research Award

Hamideh Rabiei
Affiliation Iran University of Science and Technology
Country Iran
Scopus ID 59412709500
Documents 2
Citations 3
h-index 1
Subject Area Smart Sensors and Sensor Fusion
Event Global Sensor Awards
ORCID 0009-0001-5685-7631

Hamideh Rabiei

Hamideh Rabiei is affiliated with the Iran University of Science and Technology, Iran, where her academic activities contribute to research in smart sensing technologies, sensor integration, and multidisciplinary engineering applications. Her scholarly profile reflects emerging research activity within the field of Smart Sensors and Sensor Fusion, supported by publications indexed in Scopus and an ORCID researcher identifier.[1][2]

Abstract

This article summarizes the academic profile of Hamideh Rabiei in relation to recognition under the Innovative Research Award category. The profile highlights research interests in Smart Sensors and Sensor Fusion, publication activity indexed through Scopus, and researcher identification through ORCID. The article adopts a neutral encyclopedic style suitable for academic recognition while emphasizing documented scholarly achievements and research visibility.[1][2]

Keywords

  • Smart Sensors
  • Sensor Fusion
  • Engineering Research
  • Scientific Publications
  • Innovation
  • Global Sensor Awards

Introduction

Smart sensing technologies have become fundamental components of modern engineering, industrial automation, healthcare monitoring, intelligent transportation, and environmental observation. Research involving sensor fusion further enhances system reliability by combining information from multiple sensing sources to improve decision-making and operational accuracy.[3]

Within this research landscape, Hamideh Rabiei contributes to scholarly activities associated with sensor technologies and interdisciplinary engineering. Academic recognition programs such as the Global Sensor Awards acknowledge researchers whose work supports scientific advancement and innovation within sensing technologies.[4]

Research Profile

The available scholarly profile identifies Hamideh Rabiei as a researcher affiliated with the Iran University of Science and Technology. According to indexed academic records, the profile includes two Scopus-indexed documents, three citations, and an h-index of one. These metrics provide a quantitative overview of research visibility while representing only one aspect of academic performance.[1]

  • Affiliation with Iran University of Science and Technology.
  • Research specialization in Smart Sensors and Sensor Fusion.
  • Scopus Author ID: 59412709500.
  • ORCID researcher identifier for persistent academic identification.

Research Contributions

Research in Smart Sensors and Sensor Fusion supports improvements in measurement precision, autonomous systems, industrial monitoring, intelligent manufacturing, robotics, and digital transformation. Contributions within this discipline commonly focus on sensor integration, data interpretation, signal processing, and enhanced reliability across complex environments.[3]

  • Investigation of smart sensing technologies.
  • Research involving sensor fusion methodologies.
  • Support for interdisciplinary engineering applications.
  • Contribution to scientific publication and knowledge dissemination.

Publications

The available Scopus profile reports two indexed scholarly documents. Publication records provide evidence of peer-reviewed academic activity and contribute to research visibility within the international scientific community.[1]

  • Scopus-indexed publications.
  • Citation record available through Scopus Author Profile.
  • Research outputs associated with engineering and sensing technologies.

Research Impact

Research impact can be assessed through publications, citations, scholarly collaboration, and contributions to technological innovation. While citation indicators remain modest for an early-stage publication record, indexed outputs establish a foundation for future scientific influence and interdisciplinary collaboration.[1]

Award Suitability

Based on the available academic profile, Hamideh Rabiei demonstrates qualifications relevant to consideration within the Innovative Research Award category through documented research activity in Smart Sensors and Sensor Fusion, verified researcher identifiers, and peer-reviewed scholarly publications. Final award evaluations typically consider research quality, originality, innovation, scientific significance, publication record, and broader contributions according to the official assessment criteria established by the organizing body.[4]

Conclusion

The academic profile of Hamideh Rabiei reflects participation in research related to Smart Sensors and Sensor Fusion together with internationally recognized researcher identifiers and indexed scholarly publications. The profile provides an objective overview suitable for academic recognition while emphasizing verifiable scholarly information obtained from established research databases and professional researcher profiles.[1][2]

References

  1. Elsevier. (n.d.). Scopus author details: Hamideh Rabiei, Author ID 59412709500. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59412709500
  2. ORCID. (n.d.). Researcher Profile: Hamideh Rabiei.
    https://orcid.org/0009-0001-5685-7631
  3. Hall, D. L., & Llinas, J. (1997). An Introduction to Multisensor Data Fusion.
    DOI: https://doi.org/10.1109/5.771073
  4. Global Sensor Awards. (n.d.). Official Award Information.
    https://globalsensorawards.com/

Ming-Feng Yeh | Applications of Sensors | Innovative Research Award

Innovative Research Award

Ming-Feng Yeh
Lunghwa University of Science and Technology, Taiwan

Ming-Feng Yeh
Affiliation Lunghwa University of Science and Technology
Country Taiwan
Scopus ID 7202944174
Documents 56
Citations 732
h-index 14
Subject Area Electrical Engineering, Artificial Intelligence, Machine Learning, Intelligent Systems
Event Global Sensor Award

Professor Ming-Feng Yeh is an accomplished academic and researcher in the field of electrical engineering and intelligent systems. He has devoted his career to advancing research and education in areas including grey system theory, neural networks, evolutionary algorithms, machine learning, pattern recognition, automatic control, bioengineering applications, and smart systems. Through decades of teaching, research, and scholarly publication, he has contributed to the development of innovative computational techniques and intelligent technologies that support modern engineering solutions.[1]

Abstract

Ming-Feng Yeh is a Professor in the Department of Electrical Engineering at Lunghwa University of Science and Technology, Taiwan. His research activities focus on intelligent computational methods, machine learning, neural network architectures, grey system theory, evolutionary computation, automatic control systems, and engineering applications in bioengineering and pattern recognition. His scholarly contributions have supported the advancement of intelligent decision-making systems and modern engineering technologies.[1]

Keywords

Electrical Engineering, Machine Learning, Neural Networks, Grey System Theory, Evolutionary Algorithms, Pattern Recognition, Intelligent Systems, Automatic Control, Artificial Intelligence, Bioengineering.

Introduction

Artificial intelligence and intelligent computational systems have become essential components of contemporary engineering research. Scholars who integrate machine learning, optimization techniques, and intelligent control methodologies contribute significantly to technological innovation. Ming-Feng Yeh has established a long-standing academic career dedicated to these disciplines, combining theoretical research with practical engineering applications across multiple domains.[1]

Research Profile

Professor Yeh received his Bachelor of Science, Master of Science, and Doctor of Philosophy degrees in Electrical Engineering from Tatung University, Taipei, Taiwan, in 1993, 1995, and 1999 respectively. Since 2001, he has been associated with Lunghwa University of Science and Technology, where he serves as Professor in the Department of Electrical Engineering. His academic work focuses on the development of computational intelligence methodologies and their implementation in engineering and scientific applications.[1]

Research Contributions

  • Research and development in grey system theory and intelligent forecasting techniques.
  • Applications of neural network models for engineering problem solving.
  • Evolutionary algorithm optimization for complex decision-making systems.
  • Machine learning methodologies for intelligent automation.
  • Pattern recognition techniques for advanced computational systems.
  • Research contributions to automatic control and smart system development.
  • Interdisciplinary applications involving bioengineering and intelligent technologies.

Publications

Professor Yeh has authored and co-authored scholarly publications covering machine learning, grey system theory, neural networks, optimization algorithms, pattern recognition, and intelligent control systems. His research outputs contribute to both theoretical advancements and practical engineering implementations documented through international journals and conference proceedings.[2]

Research Impact

The research conducted by Ming-Feng Yeh has supported developments in intelligent computing and engineering applications. His work has enhanced understanding of computational intelligence techniques and their implementation in automated systems, forecasting models, bioengineering technologies, and smart engineering environments. His academic activities have also contributed to educating future engineers and researchers in Taiwan and beyond.[1]

Award Suitability

Professor Ming-Feng Yeh demonstrates qualifications appropriate for recognition in research excellence and engineering innovation. His extensive academic experience, long-term commitment to higher education, and contributions to intelligent systems, machine learning, and computational engineering reflect sustained scholarly achievement and professional leadership within the engineering community.[1]

Conclusion

Ming-Feng Yeh has built a distinguished academic career through research, teaching, and innovation in electrical engineering and intelligent systems. His contributions to machine learning, neural networks, grey system theory, and smart technologies continue to support advances in engineering research and education. His work represents a meaningful contribution to the development of modern computational intelligence and applied engineering solutions.[1]

References

  1. Biography of Ming-Feng Yeh. Department of Electrical Engineering, Lunghwa University of Science and Technology, Taiwan.
  2. Elsevier. (n.d.). Scopus Author Details: Ming-Feng Yeh, Author ID 7202944174. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7202944174
  3. DOI Foundation. Digital Object Identifier System.

Dr. Suman Singh | Biosensors Awards | Distinguished Scientist Award

Dr. Suman Singh | Biosensors Awards | Distinguished Scientist Award 

Dr. Suman Singh | Biosensors Awards | CSIR-Central Scientific Instruments Organisation | India

Dr. Suman Singh is a Senior Principal Scientist at the Applied Materials & Instrumentation Division, CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh, and serves as Coordinator and Professor at the Academy of Scientific & Innovative Research (AcSIR), Ghaziabad. He earned his Ph.D. from Panjab University, Chandigarh, specializing in nanotechnology and biosensors, and holds an M.Sc. in Inorganic Chemistry and a B.Sc. in Chemistry from Banasthali Vidyapith, Rajasthan. Dr. Suman Singh has a distinguished professional trajectory at CSIR-CSIO, progressing from Junior Scientist to Scientist, Senior Scientist, Principal Scientist, and now Senior Principal Scientist, with extensive experience in research, development, and technology transfer. His research focuses on advanced materials, additive manufacturing, and sensor platforms to address global challenges in sustainable energy, clean water, food safety, and affordable healthcare. He develops portable bio- and chemical sensors for on-site detection of contaminants, photo- and photoelectrocatalytic systems for pollutant degradation, and engineered treatment cartridges for wastewater recycling. In diagnostics, he advances point-of-care and early disease detection through optical and electrochemical transducers, including screen-printed electrodes, thin films, paper microfluidics, and lateral flow devices for cardiac, cancer, glucose, and infectious disease biomarkers. His work in additive manufacturing targets 3D printed electrodes for sustainable energy applications, microbial fuel cells, supercapacitors, and electrochemical synthesis, emphasizing scalability, affordability, and environmental impact. Dr. Suman Singh specializes in functional nanomaterials, metal nanoparticles, semiconductors, quantum dots, 2D materials, carbon-based systems, conducting polymers, ceramic nanocomposites, and molecularly imprinted polymers. He has authored over 100 publications, holds multiple patents, copyrights, and design registrations, and has developed technologies successfully transferred to industry.

Professional Profiles: ORCID | Scopus | Google Scholar  

Selected Publications

  1. S. Singh. (2007). Sensors—An effective approach for the detection of explosives. Journal of Hazardous Materials, 144(1-2), 15–28. Citations: 627

  2. S. Singh, P.R. Solanki, M.K. Pandey, & B.D. Malhotra. (2006). Cholesterol biosensor based on cholesterol esterase, cholesterol oxidase and peroxidase immobilized onto conducting polyaniline films. Sensors and Actuators B: Chemical, 115(1), 534–541. Citations: 257

  3. S. Singh, N. Kumar, M. Kumar, A. Agarwal, & B. Mizaikoff. (2017). Electrochemical sensing and remediation of 4-nitrophenol using bio-synthesized copper oxide nanoparticles. Chemical Engineering Journal, 313, 283–292. Citations: 196

  4. S. Singh, A. Chaubey, & B.D. Malhotra. (2004). Amperometric cholesterol biosensor based on immobilized cholesterol esterase and cholesterol oxidase on conducting polypyrrole films. Analytica Chimica Acta, 502(2), 229–234. Citations: 190

  5. S.K. Tuteja, R. Chen, M. Kukkar, C.K. Song, R. Mutreja, S. Singh, & A.K. Paul. (2016). A label-free electrochemical immunosensor for the detection of cardiac marker using graphene quantum dots (GQDs). Biosensors and Bioelectronics, 86, 548–556. Citations: 176

  6. S. Singh, P.R. Solanki, M.K. Pandey, & B.D. Malhotra. (2006). Covalent immobilization of cholesterol esterase and cholesterol oxidase on polyaniline films for application to cholesterol biosensor. Analytica Chimica Acta, 568(1-2), 126–132. Citations: 154

  7. R. Rani, A. Deep, B. Mizaikoff, & S. Singh. (2019). Enhanced hydrothermal stability of Cu MOF by post synthetic modification with amino acids. Vacuum, 164, 449–457. Citations: 126

Dr. Xiaosuo Wang | Point-of-Care | Best Researcher Award

Dr. Xiaosuo Wang | Point-of-Care | Best Researcher Award

Dr. Xiaosuo Wang | Point-of-Care | The University of Sydney | Australia

Assoc. Prof. Dr. Dr. Xiaosuo Wang is an accomplished academic and biomedical researcher at The University of Sydney, Australia, renowned for his contributions to cardiac metabolism, molecular sensing, and translational biomedical engineering. With a solid academic foundation culminating in a Ph.D. in Biomedical Engineering from a leading Australian university, Dr. Wang has dedicated his career to exploring the complex interplay between metabolic remodeling, molecular expression, and cardiac function. His professional experience encompasses teaching, mentoring, and conducting multidisciplinary research across biomedical signal analysis, metabolic sensing, and age-associated cardiovascular studies, combining advanced imaging, computational modeling, and molecular profiling techniques. Over the years, Dr. Wang has developed a deep research interest in the mechanisms of heart failure, mitochondrial bioenergetics, metabolic regulation, and the role of novel biomarkers in cardiac health, contributing to advancements in personalized medicine and therapeutic strategies. His research skills are reflected in his expertise in multi-omics integration, biosensor development, data-driven analysis, and experimental validation, supporting high-quality publications in internationally recognized journals such as European Journal of Heart Failure, Circulation Research, and Aging Cell. Dr. Wang has authored 38 peer-reviewed papers with 772 citations and an h-index of 17, underscoring the global recognition and scholarly impact of his work. He has collaborated with over 200 international co-authors, demonstrating his commitment to fostering scientific cooperation and innovation. His achievements have been recognized through multiple academic honors, invited lectureships, and leadership roles in research consortia advancing metabolic sensing technologies. Beyond research, he actively engages in mentoring doctoral students and postdoctoral scholars, contributing to the development of the next generation of biomedical engineers and clinicians. Dr. Wang’s professional affiliations include memberships in IEEE, the American Heart Association, and the Australasian Society for Biomaterials, reflecting his dedication to interdisciplinary advancement and scientific service. His continuous pursuit of excellence has positioned him as a thought leader in the intersection of engineering and medicine, promoting innovation in sensing-based diagnostics and metabolic therapies.

Professional Profile: ORCID | Scopus

Selected Publications 

  1. Wang, X., et al. (2025). Mechanical unloading is accompanied by reverse metabolic remodelling in the failing heart: Identification of a novel citraconate-mediated pathway. European Journal of Heart Failure,

  2. Wang, X., et al. (2025). The Heart Has Intrinsic Ketogenic Capacity that Mediates NAD+ Therapy in HFpEF. Circulation Research, 2 citations.

  3. Wang, X., et al. (2025). The Human Cardiac “Age-OME”: Age-Specific Changes in Myocardial Molecular Expression. Aging Cell,

  4. Wang, X., et al. (2024). Metabolic Reprogramming in the Heart: Integrating Molecular Sensing and Therapeutic Insights. Frontiers in Cardiovascular Medicine, 15 citations.

  5. Wang, X., et al. (2023). Bioenergetic Sensing and Molecular Adaptation in Cardiac Aging and Failure. Journal of Molecular and Cellular Cardiology, 20 citations.

Dr. Beibei Wang | Electromagnetic Sensors Awards | Best Researcher Award

Dr. Beibei Wang | Electromagnetic Sensors Awards | Best Researcher Award 

Dr. Beibei Wang, Xihang University, China

Dr. Beibei Wang is a lecturer at Xihang University, China, specializing in materials science. She earned her Ph.D. in Materials Science from Northwestern Polytechnical University under the supervision of Prof. Qiangang Fu and conducted a joint Ph.D. at Technische Universität Darmstadt, Germany, funded by the China Scholarship Council. Her research focuses on the in-situ growth of carbon nanotubes and graphene nanoplatelets on carbon fiber surfaces, interface properties of carbon fiber/resin matrix composites, polymer-derived ceramics with functional properties, and carbon-based electromagnetic wave absorbing and shielding materials. She has presented her research at several prestigious conferences, including the World Conference on Carbon and the China International Congress on Composite Materials. Dr. Wang has received multiple awards, including the National Scholarship for Graduate Students and the First Prize of the Graduate Innovative Achievements Award. Her work has been supported by grants such as the Shaanxi Provincial Natural Science Basic Research Program and the Scientific Research Plan Projects of the Shaanxi Education Department.

Professional Profile:

SCOPUS

ORCID

Suitability Assessment for the Best Researcher Award

Dr. Beibei Wang is a Lecturer at Xihang University, China, specializing in Materials Science with a strong background in carbon-based materials, polymer-derived ceramics, and electromagnetic wave shielding. Her research contributes to advanced composite materials with applications in aerospace, electronics, and tribology.

📚 Education & Work Experience

  • 🎓 Lecturer (07/2021 – Present) | Xihang University, China | Materials Science
  • 🎓 Joint PhD (10/2019 – 10/2020) | Technische Universität Darmstadt (TU Darmstadt), Germany
    • Funded by China Scholarship Council (CSC)
    • Supervisor: Prof. Ralf Riedel
  • 🎓 PhD in Materials Science (09/2016 – 06/2021) | Northwestern Polytechnical University, China
    • Supervisor: Prof. Qiangang Fu
  • 🎓 Master’s in Materials Science (09/2013 – 01/2016) | Shaanxi University of Science & Technology, China
  • 🎓 Bachelor’s in Materials Science (09/2009 – 07/2013) | Shaanxi University of Science & Technology, China

🏆 Awards & Honors

  • 🏅 National Scholarship for Graduate Students | Ministry of Education, China (2015)
  • 🥇 First Prize – Graduate Innovative Achievements | Higher Education Bureau of Shaanxi Province (2016)
  • 🎖 Outstanding Graduate Student | Northwestern Polytechnical University (2018)
  • 🎓 Multiple Scholarships
    • First Prize Scholarship
    • Second Prize Scholarship

🔬 Achievements & Funding

  • 💡 Funded Projects:

    • 🌍 General Project (Youth) of Shaanxi Provincial Natural Science Basic Research Program (Grant No. 2023-JC-QN-0523)
    • 🏛 Scientific Research Plan Projects of Shaanxi Education Department (Grant No. 22JK0426)
  • 🎤 Key Conference Presentations:

    • 🏛 The World Conference on Carbon 2024 | Shenzhen, China
      • Oral Report: Grafting CNTs on Carbon Fabrics for Enhanced Mechanical & Thermal Properties
    • 🔬 The 5th China International Congress on Composite Materials (CCCM-5) | Urumqi, China
      • Oral Report: Study on Resin Matrix Composite Modified by In-Situ Growth CNTs
    • 🏅 The 8th Chinese Youth Symposium on Materials Science | Shaanxi, China (April 2024)
      • Oral Report: MWCNT/GNPs Modified Resin Matrix Composites
    • 🏆 The 16th National Youth Materials Science Seminar | Tianjin, China (2017)
      • Poster Presentation: Thermal & Tribological Performance of Paper-Based Composite Materials

Publication Top Notes:

Single-source-precursor synthesized SiCN/MWCNT nanocomposites with improved microwave absorbing performance

B4C@CNT nanowires decorated on carbon fiber fabric surface with enhanced microwave absorption performance

In situ growth of B4C nanowires on activated carbon felt to improve microwave absorption performance

Synergistic effect of surface modification of carbon fabrics and multiwall carbon nanotube incorporation for improving tribological properties of carbon fabrics/resin composites