Abdul Barik | Sensor Characterization | Best Academic Researcher Award

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

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.

Mr. Duo Wang | Applied Sensor | Research Excellence Award

Mr. Duo Wang | Applied Sensor | Research Excellence Award 

Mr. Duo Wang | Applied Sensor | Beijing University of Aeronautics and Astronautics | China

Mr. Duo Wang is a dedicated Ph.D. Candidate at the School of Energy and Power Engineering, Beijing University of Aeronautics and Astronautics, Beijing, China, recognized for his significant contributions to the field of aero-engine combustor design and computational combustion. He received his advanced education in energy and power engineering, developing a solid foundation in fluid dynamics, combustion mechanisms, and aero-engine systems. Professionally, Mr. Duo Wang has been actively involved in multiple high-impact national projects focusing on zoned combustion organization under high fuel-air ratio conditions, low-emissions staged and zoned combustion mechanisms for natural gas gas turbines, and dynamic flow and combustion characterization in main combustors, demonstrating both technical leadership and collaborative project management skills. His research interests include sensitive parameter analysis, computational combustion modeling, low-emission combustor design, and performance optimization of aero-engines. Mr. Duo Wang has produced 7 Scopus-indexed publications with 31 citations from 28 citing documents and an h-index of 4, demonstrating a growing academic impact in high-quality journals such as Physics of Fluids.

Citation Metrics (Scopus)

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