Abdul Barik | Sensor Characterization | Best Academic Researcher Award

Posted on by Global Sensor Awards

Best Academic Researcher Award

Abdul Barik
Department of Textile Engineering, Southeast University, Bangladesh

Abdul Barik
Affiliation Southeast University
Country Bangladesh
Scopus ID 57222270795
Documents 8
Citations 109
h-index 4
Subject Area Sensor Characterization
Event Global Sensor Awards
ORCID 0009-0002-4657-2162

Abdul Barik is a Lecturer in the Department of Textile Engineering at Southeast University, Bangladesh. His academic career combines teaching, materials research, and scientific collaboration in condensed matter physics and engineering materials. His research emphasizes thin films, nanotechnology, functional oxide materials, perovskite materials, computational materials science, and optoelectronic applications. Through interdisciplinary research, undergraduate instruction, and collaborative projects, he contributes to the advancement of sustainable materials and sensor characterization technologies while promoting innovation in higher education and engineering research.[1]

Abstract

Abdul Barik is an academic researcher whose work integrates experimental and computational investigations of functional materials for sensor, energy, and optoelectronic applications. His research explores thin films, lead-free perovskites, nanostructured materials, and density functional theory (DFT) simulations to understand structural, electrical, and optical properties. His scholarly activities include peer-reviewed publications, editorial appointments, conference participation, and collaborative research, supporting the advancement of sustainable materials science and engineering.[2]

Keywords

Sensor Characterization; Thin Films; Nanotechnology; Functional Oxide Materials; Lead-Free Perovskites; Condensed Matter Physics; Computational Materials Science; Density Functional Theory; Optoelectronic Materials; X-ray Diffraction.

Introduction

Serving as a Lecturer at Southeast University, Abdul Barik combines engineering education with active scientific research. His professional interests span materials characterization, thin-film technology, functional oxide materials, nanotechnology, and computational modelling. Through teaching, curriculum development, and student supervision, he supports the development of future engineers while maintaining an active research profile focused on advanced materials and their technological applications.[2]

Research Profile

His ongoing research investigates calcium-substituted barium titanate thin films for optoelectronic devices, pressure-dependent electronic behaviour of lead-free perovskites using density functional theory, and functional oxide materials for energy applications. His expertise includes X-ray diffraction analysis, electrical and optical characterization, computational materials science, and experimental materials engineering. Collaborative research with Bangladesh University of Engineering and Technology, Southeast University, and international materials researchers has strengthened the interdisciplinary scope of his investigations.[2]

Research Contributions

  • Experimental characterization of functional oxide thin films.
  • Computational investigation of lead-free perovskite materials using density functional theory.
  • Research on structure–property relationships in advanced materials.
  • Studies of optical, structural, and electrical properties of nanostructured materials.
  • Promotion of interdisciplinary collaboration in condensed matter physics and materials science.
  • Academic mentoring, undergraduate teaching, and curriculum development.

Publications

The researcher has authored eight Scopus-indexed publications and a total of nine scholarly journal publications. His work has received over one hundred citations across academic databases and more than 4,420 ResearchGate reads. His publication portfolio focuses on condensed matter physics, sensor characterization, thin films, perovskite materials, and functional oxides, reflecting sustained engagement in advanced materials research.[1]

  • Scopus-indexed journal publications: 8
  • Total journal publications: 9
  • Editorial appointments: 2
  • ResearchGate citations: 135
  • ResearchGate reads: 4,420+

Research Impact

The available research indicators include eight Scopus-indexed documents, 109 Scopus citations, an h-index of 4, and broader academic visibility reflected by 135 Google Scholar and ResearchGate citations. His editorial responsibilities, collaborative research, and conference participation further demonstrate sustained scholarly engagement in materials science, computational modelling, and sensor-related characterization techniques.[1]

Award Suitability

Abdul Barik’s profile aligns with the objectives of the Best Academic Researcher Award presented at the Global Sensor Awards. His contributions to thin-film characterization, functional oxide materials, computational materials science, and optoelectronic research demonstrate scientific relevance within the field of sensor characterization. His academic leadership, collaborative research activities, and publication record support recognition for sustained contributions to engineering education and materials research.[2]

Conclusion

Abdul Barik has established a growing academic profile through interdisciplinary research, engineering education, and collaborative scientific investigations. His work in condensed matter physics, thin films, nanotechnology, and functional materials contributes to ongoing developments in advanced materials and sensor characterization. Continued research, publication, and academic engagement position him as an active contributor to emerging technologies and sustainable engineering applications.

References

  1. Elsevier. (n.d.). Scopus author details: Abdul Barik, Author ID 57222270795. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57222270795
  2. Abdul Barik. Academic and Professional Background, Research Projects, Research Contributions, Collaborations, Publication Metrics, and Professional Activities.

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

Posted on by Global Sensor Awards

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.

Mohammad Qtait | Sensors Phenomena and Modelling | Innovative Research Award

Posted on by Global Sensor Awards

Innovative Research Award

Mohammad Qtait, 
Palestine Polytechnic University, College of Nursing and Applied Sciences, Hebron, Palestine

Mohammad Qtait
Affiliation Palestine Polytechnic University
Country Palestine
Scopus ID 58184894200
Documents 48
Citations 301
h-index 9
Subject Area Nursing, Healthcare Leadership, Public Health, Sensors Phenomena and Modelling
Event Global Sensor Awards
ORCID 0000-0003-2414-7982

Mohammad Qtait is a Palestinian nurse educator, researcher, clinical instructor, and healthcare leader whose academic and professional contributions span more than two decades. His work integrates nursing management, leadership development, emergency and burn care, evidence-based practice, and public health research. Through extensive teaching, clinical leadership, curriculum development, and scholarly publication, Qtait has contributed significantly to advancing nursing education and healthcare quality within Palestine and the wider regional nursing community.[1]

Abstract

Mohammad Qtait has established a distinguished academic and clinical career through his contributions to nursing leadership, healthcare management, emergency care, burn care, and nursing education. His doctoral research on time management among intensive care unit nurses demonstrated measurable improvements in patient care quality and professional performance. Through more than fifty scholarly publications, educational leadership roles, and active involvement in healthcare training programs, Dr. Qtait has contributed to strengthening evidence-based nursing practice and healthcare service delivery. His multidisciplinary research portfolio reflects a commitment to improving patient outcomes, healthcare systems, and nursing workforce development.[2]

Keywords

Nursing Leadership, Nursing Management, Evidence-Based Practice, Public Health, Burn Care, Emergency Nursing, Time Management, Healthcare Quality, Nursing Education, Intensive Care Nursing, Clinical Research, Patient Safety, Healthcare Administration, Nursing Workforce Development.

Introduction

Healthcare systems increasingly depend on highly trained nurse leaders capable of integrating research evidence into clinical practice. Dr. Mohammad T. Qtait has emerged as a recognized academic and clinical figure in this field through his work in nursing management, leadership development, healthcare quality improvement, and emergency care. His educational contributions at Palestine Polytechnic University and Al-Quds University have helped prepare future nursing professionals while advancing nursing scholarship in Palestine.[3]

Research Profile

Qtait earned his Bachelor of Science in Nursing from Hebron University, completed a Master of Science in Nursing Management at Al-Quds University, and subsequently obtained a Doctor of Philosophy in Nursing from Arab American University. His doctoral dissertation examined the effectiveness of structured time management interventions among intensive care nurses and demonstrated positive outcomes related to quality of care delivery.[2]

His research interests encompass nursing management and leadership, adult health nursing, public health, emergency and burn care, healthcare education, quality improvement, workforce performance, evidence-based practice, and healthcare policy development. These themes are reflected throughout his publication record and research supervision activities.[3]

Research Contributions

  • Advanced understanding of time management practices among nurses and healthcare administrators.
  • Conducted influential studies on leadership styles and nursing performance.
  • Investigated emergency nursing challenges in conflict-affected healthcare settings.
  • Published systematic reviews addressing nursing leadership, burnout, and evidence-based practice.
  • Contributed to burn care epidemiology, prevention strategies, and patient quality-of-life research.
  • Supported nursing curriculum development and healthcare workforce training initiatives.
  • Supervised undergraduate and postgraduate nursing research projects leading to publications in internationally indexed journals.

Publications

Qtait has authored and co-authored more than fifty scholarly works covering nursing leadership, emergency nursing, public health, healthcare quality, burn care, mental health, infection prevention, evidence-based practice, nursing education, and healthcare administration. Representative publications include:

  • Factors Affecting Time Management and Nurses’ Performance in Hebron Hospitals (2014).
  • Knowledge and Compliance of Nursing Staff Towards Standard Precautions in Palestinian Hospitals (2015).
  • Time Management for Nurses (Book, 2017).
  • Barriers to Effective Nurse–Patient Communication in the Emergency Department (2020).
  • Head Nurses’ Leadership Styles and Nurses’ Performance: Systematic Review (2023).
  • Systematic Review of Time Management Practices Among Nurse Managers (2023).
  • Time Management Dimension for Nurses Intensive Care Unit: A Qualitative Study (2024).
  • Nurses’ Knowledge, Attitudes, and Implementation of Evidence-Based Practice Comparative Study (2025).
  • The Challenges of an Emergency Nurse Team Working in an Active Conflict Area (2025).
  • Impact of the October 7 Gaza War on Post-Traumatic Stress Symptoms and Quality of Life in Palestinian Nursing Students (2025).

Research Impact

The scholarly contributions of Qtait have influenced nursing education, workforce management, patient care quality, and healthcare policy discussions across Palestine and neighboring regions. His research has addressed critical challenges such as workforce burnout, communication barriers, leadership effectiveness, emergency preparedness, trauma-related mental health, and patient safety. Through teaching, clinical instruction, and professional training programs, he has directly contributed to healthcare capacity building and professional nursing development.[4]

Award Suitability

Mohammad T. Qtait demonstrates strong qualifications for recognition within nursing leadership, healthcare research, public health, and clinical education award categories. His combination of extensive clinical service, academic leadership, research productivity, healthcare training activities, and evidence-based practice advancement aligns with the standards typically associated with distinguished healthcare and nursing excellence awards. His sustained commitment to improving healthcare outcomes and strengthening nursing education further supports his suitability for international academic recognition.[5]

Conclusion

Mohammad T. Qtait has built a comprehensive career spanning nursing education, healthcare leadership, clinical service, and scholarly research. His work has contributed to the advancement of nursing knowledge, workforce development, healthcare quality improvement, and patient-centered care. Through sustained academic productivity, educational leadership, and clinical engagement, he continues to support the development of evidence-based nursing practice and healthcare excellence.

References

  1. Curriculum Vitae of Dr. Mohammad T. Qtait. Professional academic record including education, appointments, research activities, publications, and healthcare leadership contributions.
  2. Arab American University. Doctor of Philosophy in Nursing Dissertation: Effectiveness of Time Management Training Program on Patient Quality of Care Performed by Nurses Working in Intensive Care Units in the West Bank Government Hospitals.
  3. Palestine Polytechnic University, College of Nursing and Applied Sciences. Academic profile and teaching contributions of Dr. Mohammad T. Qtait.
  4. Qtait, M., et al. Selected peer-reviewed publications in nursing leadership, emergency nursing, public health, evidence-based practice, and healthcare quality improvement (2014–2025).
  5. Elsevier. (n.d.). Scopus Author Details: Mohammad T. Qtait, Author ID 58184894200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58184894200
  6. Qtait, M., Alqaissi, N., Farajalla, F., et al. (2025). Impact of the October 7 Gaza War on Post-Traumatic Stress Symptoms and Quality of Life in Palestinian Nursing.
    DOI: https://doi.org/10.1038/s41598-025-18039-1

Mutahar Ali | Sensor Signal Processing | Best Researcher Award

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Mr. Mutahar Ali | Sensor Signal Processing | Best Researcher Award

Shenzhen University | China

Mr. Mutahar Ali Amur is a Civil Engineer and academic currently serving as a Lecturer at Quaid-E-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Pakistan. He holds a Master of Engineering in Structural Engineering from Mehran University of Engineering and Technology (MUET), Jamshoro, where he graduated with a CGPA of 3.88/4, and a Bachelor of Engineering in Civil Engineering from QUEST, securing 3rd position in his graduating class. His academic and research expertise focuses on sustainable construction materials, geotechnical engineering, and structural engineering. Mutahar Ali Amur has contributed to several research publications addressing innovative materials such as jute fibre reinforced clay, wood waste ash in concrete, and recycled plastic reinforcement for soils. His research aims to develop cost-effective and environmentally sustainable solutions for construction and infrastructure. In addition to teaching subjects such as Fluid Mechanics, Surveying, and Strength of Materials, he actively participates in academic conferences and technical training programs, contributing to engineering education and sustainable civil engineering practices.

Citation Metrics (Scopus)

12
8
5
2

Citations
12

h-index
2

Documents
5

Citations

h-index

Documents

Featured Publications

Structural Behaviour of Large Size Compressed Earth Blocks Stabilized with Jute Fibre
Journal of Engineering Research · Journal Article

Experimental Study of Physical, Fresh-State and Strength Parameters of Concrete Incorporating Wood Waste Ash as a Cementitious Material
Journal of Materials and Engineering Structures · Journal Article

Potential of Waste Plastic (PET) Bottle Strips as Reinforcement Material for Clayey Soil
Second International Conference on Sustainable Development in Civil Engineering, MUET, Pakistan · Conference Paper

Mr. Chunhui Xu | Sensor Integration Awards | Best Researcher Award

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Mr. Chunhui Xu | Sensor Integration Awards | Best Researcher Award

Mr. Chunhui Xu, Shenyang Institute of Automation, Chinese Academy of Sciences, China

Xu Chunhui is a distinguished male researcher and Master Supervisor at the Shenyang Institute of Automation, part of the Chinese Academy of Sciences. He holds a Master of Engineering and a Bachelor of Engineering from Harbin Engineering University. Xu has extensive experience in autonomous underwater vehicles (AUVs), specializing in areas such as software architecture, path planning, navigation control, and fault diagnosis. His professional journey includes roles as an Assistant Researcher and Research Intern at the Shenyang Institute, where he has made significant contributions to the field, earning several awards including the Special Prize for the Science and Technology Promotion Award of the Chinese Academy of Sciences. Xu has a robust patent portfolio with numerous inventions related to underwater robotics, including collision avoidance technologies and navigation methods. His research continues to advance the capabilities of AUVs, with a focus on applications in deep-sea exploration and resource management.

Professional Profile:

SCOPUS

Xu Chunhui for the Best Researcher Award

Xu Chunhui is a distinguished male Master Supervisor at the Shenyang Institute of Automation, Chinese Academy of Sciences. His expertise lies in autonomous underwater vehicle (AUV) technologies, particularly in software architecture, path planning, navigation control, and fault diagnosis. His extensive educational background includes a Master of Engineering and a Bachelor of Engineering from Harbin Engineering University.

Education 🎓

  • Master of Engineering
    Harbin Engineering University
    September 2005 – March 2008
  • Bachelor of Engineering
    Harbin Engineering University
    September 2001 – August 2005

Work Experience 💼

  • Associate Researcher
    Shenyang Institute of Automation, Chinese Academy of Sciences
    April 2016 – Present
  • Assistant Researcher
    Shenyang Institute of Automation, Chinese Academy of Sciences
    October 2010 – March 2016
  • Research Intern
    Shenyang Institute of Automation, Chinese Academy of Sciences
    April 2008 – September 2010

Achievements 🏆

  • Science and Technology Promotion Award of the Chinese Academy of Sciences
    Special Prize, 2021
  • 3D Real-time Collision Avoidance Technology of Autonomous Underwater Robot
    Second Prize, Provincial Level, 2019
  • Research and Application of Key Technologies for Autonomous Exploration System of Deep-sea Resources
    First Prize, Ministry Level, 2018

Publication Top Notes:

Applications of Autonomous Underwater Vehicle in Submarine Hydrothermal Fields: A Review

Guided Trajectory Filtering for Challenging Long-Range AUV Navigation

A fault diagnosis method with multi-source data fusion based on hierarchical attention for AUV

Ocean Temperature Prediction Based on Stereo Spatial and Temporal 4-D Convolution Model

Accurate two-step filtering for AUV navigation in large deep-sea environment

A fault diagnosis method based on attention mechanism with application in Qianlong-2 autonomous underwater vehicle