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

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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.

Mlungisi Ntombela | Internet of Things (IoT) | Innovative Research Award

Posted on by Global Sensor Awards

Innovative Research Award

Mlungisi Ntombela
Durban University of Technology (DUT), South Africa

Mlungisi Ntombela
Affiliation Durban University of Technology (DUT)
Country South Africa
Scopus ID 57558503600
Documents 14
Citations 194
h-index 5
Subject Area Electrical Engineering, Artificial Intelligence, Smart Grids, Electric Vehicles, Internet of Things
Event Global Sensor Awards
ORCID 0000-0001-6428-0257

Mlungisi Ntombela is a South African electrical engineer, academic researcher, lecturer, and certified engineering professional whose work bridges industrial engineering practice and advanced academic research. His expertise spans electrical power systems, artificial intelligence applications in smart grids, power system optimization, distributed generation integration, electric vehicles, reliability engineering, and project management. Through a combination of engineering leadership, research innovation, and higher education contributions, he has established a multidisciplinary profile that supports both technological advancement and engineering education.[1]

Abstract

This academic recognition article presents the professional achievements, research contributions, and engineering leadership of Dr. Mlungisi Eric Ntombela. His work integrates industrial engineering practice with advanced research in electrical power systems, smart grids, distributed generation, artificial intelligence optimization algorithms, and electric vehicle integration. His contributions include peer-reviewed publications, project engineering leadership, higher education teaching, and the development of innovative methodologies for power loss reduction and voltage profile enhancement in modern electrical networks.[2]

Keywords

Electrical Engineering, Smart Grids, Artificial Intelligence, Optimization Algorithms, Distributed Generation, Electric Vehicles, Power Systems, Reliability Engineering, Power Quality, Energy Systems, Research Innovation, Engineering Education, Project Engineering, Sustainable Energy.

Introduction

Dr. Ntombela’s career demonstrates a balanced integration of industrial engineering experience and academic scholarship. Holding a Doctor of Engineering in Electrical Engineering and a Government Certificate of Competency (Factories), he has contributed significantly to both utility-scale engineering operations and university-level education. His professional experience includes maintenance engineering, reliability management, risk assessment, project execution, research supervision, and curriculum development. These combined experiences have enabled him to address practical engineering challenges while advancing scientific knowledge in electrical power systems.[1]

Research Profile

The research activities of Dr. Ntombela focus primarily on electrical power system optimization, artificial intelligence applications in smart grids, distributed generation placement, electric vehicle integration, power quality improvement, and sustainable energy management. His academic work has investigated advanced hybrid optimization algorithms capable of minimizing network losses while improving voltage stability and operational efficiency in electrical distribution systems.[3]

Beyond research, he actively contributes to engineering education through lecturing, laboratory instruction, curriculum modernization aligned with Fourth Industrial Revolution (4IR) technologies, and mentoring of engineering students. His interdisciplinary perspective supports the integration of industry-driven solutions within academic environments.[4]

Research Contributions

  • Development and evaluation of optimization techniques for power network reconfiguration.
  • Research on distributed generation sizing and placement for power loss minimization.
  • Application of artificial intelligence hybrid algorithms in smart grid optimization.
  • Comprehensive studies on electric vehicle integration into modern power systems.
  • Voltage profile improvement methodologies for sustainable electricity networks.
  • Contributions to battery electric vehicle drive circuit technologies and operational analysis.
  • Research on renewable energy distributed generation and smart grid interoperability.
  • Engineering project management and reliability-centered maintenance methodologies.

Publications

  • Review of Optimization Techniques for Power Network Reconfiguration (SAUPEC 2022).
  • Power Loss Minimization and Voltage Profile Improvement by Distributed Generation Sizing and Placement (PowerAfrica 2022).
  • Power Loss Minimization and Voltage Profile Improvement by System Reconfiguration, DG Sizing, and Placement. Computation, 2022.
  • Artificial Intelligent Hybrid Algorithm Used for System Reconfiguration to Minimize Power Losses in the Distribution System.
  • Load Profile and Load Flow Analysis for a Grid System with Electric Vehicles Using a Hybrid Optimization Algorithm. Sustainability, 2023.
  • Reduction of Power Losses and Voltage Profile Improvement in a Smart Grid Incorporated with Electric Vehicles. Sustainability, 2023.
  • A Comprehensive Review of the Incorporation of Electric Vehicles and Renewable Energy Distributed Generation Regarding Smart Grids. World Electric Vehicle Journal, 2023.
  • A Comprehensive Review for Battery Electric Vehicles (BEV) Drive Circuits Technology, Operations, and Challenges. World Electric Vehicle Journal, 2023.

Research Impact

The research contributions of Dr. Ntombela address critical challenges associated with energy efficiency, renewable energy integration, electrical network optimization, and transportation electrification. His published studies provide analytical frameworks and computational techniques that support the development of resilient and sustainable power systems. These contributions are particularly relevant to emerging smart grid infrastructures and the increasing adoption of electric mobility technologies worldwide.[5]

In addition to scholarly outputs, his industrial experience in project engineering, risk-based inspection, reliability-centered maintenance, and operational management provides practical relevance to his research, strengthening the applicability of his findings in real-world engineering environments.[1]

Award Suitability

Dr. Mlungisi Eric Ntombela demonstrates strong suitability for recognition within engineering, energy systems, smart grid technologies, and applied artificial intelligence award categories. His profile combines advanced academic qualifications, impactful scientific publications, industrial engineering leadership, teaching excellence, and interdisciplinary innovation. His contributions align closely with the objectives of awards recognizing research excellence, technological innovation, sustainability, engineering leadership, and emerging contributions to future energy systems.[2]

Conclusion

Dr. Mlungisi Eric Ntombela represents a new generation of engineering professionals whose expertise spans industry practice, academic scholarship, and technological innovation. Through his work in electrical engineering, artificial intelligence, smart grids, and electric vehicle integration, he has contributed to advancing knowledge while addressing practical challenges facing modern energy systems. His combination of research productivity, engineering leadership, and educational service positions him as a notable contributor within the fields of electrical engineering and sustainable energy development.

References

  1. Ntombela, M. E. Professional Curriculum Vitae and Academic Profile.
  2. Ntombela, M., Musasa, K., & Leoaneka, M.C. (2022). Review of Optimization Techniques for Power Network Reconfiguration.
    https://doi.org/10.1109/SAUPEC55179.2022.9730628
  3. Ntombela, M., Musasa, K., & Leoaneka, M.C. (2022). Power Loss Minimization and Voltage Profile Improvement by System Reconfiguration, DG Sizing, and Placement.
    https://doi.org/10.3390/computation10100180
  4. Durban University of Technology. Academic Teaching and Research Activities.
  5. Ntombela, M., Musasa, K., & Moloi, K. (2023). A Comprehensive Review of the Incorporation of Electric Vehicles and Renewable Energy Distributed Generation Regarding Smart Grids.
    https://doi.org/10.3390/wevj14070176

Hamza Abubakar | Body Area Network | Innovative Research Award

Posted on by Global Sensor Awards

Innovative Research Award

HAMZA ABUBAKAR, PhD
Department of Mathematics, Isa Kaita College of Education, Dutsin-Ma, Nigeria

HAMZA ABUBAKAR
Affiliation Isa Kaita College of Education
Country Nigeria
Scopus ID 57217009001
Documents 30
Citations 350
h-index 9
Subject Area Applied Mathematics, Financial Mathematics, Neural Networks, Body Area Network
Event Global Sensor Awards
ORCID
0000-0002-9451-0401

Hamza Abubakar is a Nigerian applied mathematician and academic researcher specializing in financial mathematics, optimization algorithms, neural networks, and statistical modelling. He has contributed extensively to interdisciplinary mathematical research through scholarly publications, conference presentations, academic leadership, and funded research initiatives. His work integrates advanced computational techniques with applied statistical frameworks for solving practical problems in finance, engineering, healthcare analytics, and artificial intelligence.[1]

Abstract

This academic article presents the scholarly profile and research achievements of Hamza Abubakar, an applied mathematician with expertise in financial mathematics, neural networks, optimization algorithms, and statistical modelling. Over a professional academic career spanning more than fifteen years, he has contributed to higher education, interdisciplinary research, curriculum development, and mathematical applications in finance and artificial intelligence. His publications and conference presentations demonstrate sustained contributions to optimization theory, stochastic modelling, and machine learning-based analytical systems. His work has received visibility through peer-reviewed international journals and collaborative research activities across Nigeria and Malaysia.[2]

Keywords

Applied Mathematics; Financial Mathematics; Neural Networks; Optimization Algorithms; Statistical Modelling; Machine Learning; Risk Assessment; Weibull Distribution; Hopfield Neural Networks; Artificial Intelligence; Computational Mathematics; Mathematical Modelling.

Introduction

Applied mathematics continues to play an essential role in solving real-world scientific and financial challenges through computational modelling and algorithmic optimization. Researchers working at the intersection of mathematics, artificial intelligence, and financial analytics contribute significantly to modern predictive systems and decision-making frameworks. Hamza Abubakar has developed a research portfolio focused on the application of mathematical optimization techniques and intelligent computational models to finance, risk prediction, healthcare classification systems, and statistical estimation problems.[3]

His academic progression from assistant lecturer to principal lecturer reflects sustained professional growth and commitment to mathematics education and research leadership. In addition to teaching and supervision responsibilities, he has participated actively in professional associations and interdisciplinary collaborations within computational mathematics and artificial intelligence.[4]

Research Profile

Hamza Abubakar obtained his Bachelor of Science in Mathematics Education from the University of Abuja in 2006, followed by a Master of Science degree in Financial Mathematics from the same institution in 2015. He later completed a Doctor of Philosophy degree in Applied Mathematics at Universiti Sains Malaysia in 2022.[5]

His academic and professional engagements include positions at Isa Kaita College of Education, Annahda International University, Universiti Sains Malaysia, and Universiti Utara Malaysia. These appointments enabled him to contribute to teaching, research mentoring, curriculum implementation, and international academic collaboration across mathematics and quantitative sciences disciplines.[6]

Research Contributions

The research contributions of Hamza Abubakar are concentrated on optimization algorithms, generalized linear models, neural network systems, and probabilistic modelling techniques. His studies on Weibull and Gamma distribution parameter estimation introduced optimization-based frameworks that integrate heuristic and artificial intelligence algorithms for statistical inference.[2]

His publications also investigate the application of Hopfield neural networks and satisfiability logic in intelligent classification systems. These studies contribute to computational intelligence by combining neural computation with optimization strategies for financial risk prediction and healthcare-related classification tasks.[3]

Publications

The publication profile of Hamza Abubakar includes peer-reviewed journal articles, conference proceedings, books, and book chapters addressing applied mathematics, computational intelligence, optimization theory, and financial analytics.[5]

  • Abubakar, H., & Sayed, A. A. I. (2025). Estimation of shifted Weibull distribution parameters using continuous Hopfield neural networks. Journal of Applied Statistics, 52(14), 1–33.
  • Abubakar, H. (2025). Random Satisfiability Logic-Driven Approach in Hopfield Neural Networks. International Journal of Applied and Computational Mathematics, 11(3), 117.
  • Ali, G. A., Abubakar, H., et al. (2023). Artificial dragonfly algorithm in the Hopfield neural network. PLOS ONE, 18(9), e0286874.
  • Abubakar, H., & Sabri, S. R. M. (2023). A Bayesian Approach to Weibull Distribution. Journal of Reliability and Statistical Studies, 16(01), 1–24.
  • Abubakar, H., & Madugu, A. (2025). Fundamentals of Mathematics in Finance: A Guide to Undergraduate Financial Mathematics. Ahmadu Bello University Press.

Research Impact

The research activities of Hamza Abubakar demonstrate interdisciplinary impact through the integration of mathematical theories with computational intelligence systems. His work contributes to broader developments in financial analytics, predictive modelling, and optimization-based machine learning approaches. Several of his studies have been indexed in internationally recognized journals and databases, increasing accessibility and scholarly visibility.[1]

In addition to research output, he has secured multiple institutional research grants under the TETFUND Institutional Based Research programme and contributed to academic administration and mentoring within the mathematics community in Nigeria.[1]

Award Suitability

Hamza Abubakar demonstrates suitability for recognition in applied mathematics and computational research due to his sustained academic contributions, interdisciplinary research portfolio, leadership in mathematics education, and involvement in international collaborations. His scholarly activities reflect a balance between theoretical mathematical development and practical computational applications.[2]

His publication record, funded projects, editorial roles, and conference participation collectively indicate active engagement in advancing quantitative sciences and intelligent computational systems. These contributions align with the objectives of international research excellence and innovation awards recognizing impactful academic scholarship.[3]

Conclusion

Hamza Abubakar has established a professional and scholarly profile grounded in applied mathematics, optimization techniques, financial modelling, and neural network systems. Through academic teaching, interdisciplinary research, conference engagement, and institutional leadership, he has contributed meaningfully to the advancement of quantitative sciences and computational methodologies. His body of work reflects ongoing dedication to mathematical innovation, research excellence, and higher education development within both regional and international academic communities.

References

  1. Elsevier. (n.d.). Scopus author details: HAMZA ABUBAKAR, Author ID 57217009001. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57217009001
  2. ORCID. (n.d.). HAMZA ABUBAKAR researcher profile.
    https://orcid.org/0000-0002-9451-0401
  3. Abubakar, H., & Sayed, A. A. I. (2025). Estimation of shifted Weibull distribution parameters using continuous Hopfield neural networks. Journal of Applied Statistics.
  4. Abubakar, H. (2025). Random Satisfiability Logic-Driven Approach in Hopfield Neural Networks. International Journal of Applied and Computational Mathematics.
  5. Universiti Sains Malaysia. (2022). Doctor of Philosophy in Applied Mathematic

Mrs. Inajara Rutyna | Online Monitoring | Best Researcher Award

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Mrs. Inajara Rutyna | Online Monitoring | Best Researcher Award

Mrs. Inajara Rutyna | Online Monitoring | Warsaw University of Technology | Poland

Mrs. Inajara Rutyna is a distinguished researcher in the field of Artificial Intelligence and Renewable Energy Systems, currently pursuing her Ph.D. in Automation, Electronics, and Electrical Engineering at the Warsaw University of Technology, Poland. Her academic foundation is built on a Master’s degree in Numerical Methods in Engineering and a Bachelor’s degree in Industrial Mathematics from the Universidade Federal do Paraná, Brazil. Throughout her academic and professional journey, Mrs. Inajara Rutyna has consistently demonstrated exceptional proficiency in mathematical modeling, computational intelligence, and optimization methods. Her professional experience encompasses diverse roles, including AI Development Specialist at IDEAS NCBR Sp. z o.o., where she developed intelligent algorithms and Python-based models for renewable energy forecasting, and Mathematical Modeller and Data Scientist at the National Centre for Nuclear Research, Poland, contributing to mathematical frameworks for sustainable power systems. Additionally, her earlier engagements as a Game Economy Designer at Rage Quit Games and as a Project and Process Analyst at Segula do Brasil Engenharia e Tecnologia reflect her versatility in applying data-driven modeling to industrial, gaming, and energy contexts. Mrs. Rutyna’s research interests lie primarily in Artificial Intelligence applications for renewable energy forecasting, computational fluid dynamics, optimization algorithms, and machine learning-based energy modeling. Her technical skills include advanced programming in Python, MATLAB, and Fortran, as well as expertise in numerical analysis, data science, and algorithmic development. She has authored and co-authored multiple IEEE and Scopus-indexed publications focusing on energy efficiency prediction, evaluation metrics for wind power, and AI-based forecasting. She is an active member of professional bodies such as the IEEE, contributing to international research collaborations and scientific discussions on sustainable technology innovation.

Professional Profiles: ORCID

Featured Publications 

  1. Rutyna, I. (n.d.). Gated lag and feature selection for day-ahead wind power forecasting using on-site SCADA data. IEEE. (Citations: 42)

  2. Rutyna, I. (n.d.). Efficiency analysis of k-nearest neighbors machine learning method for 10-minutes ahead forecasts of electric energy production at an onshore wind farm. Elsevier. (Citations: 38)

  3. Rutyna, I. (n.d.). Evaluation metrics for wind power forecasts: A comprehensive review and statistical analysis of errors. IEEE Access. (Citations: 57)

  4. Rutyna, I. (n.d.). Polynomial interpolation with repeated Richardson extrapolation to reduce discretization error in CFD. Springer. (Citations: 31)

  5. Rutyna, I. (n.d.). Stochastic hybrid optimization methods for renewable energy forecasting and grid stability. IEEE Transactions on Sustainable Energy. (Citations: 29)

Alhassan Shaibu | Smart Sensors | Excellence in Innovation Award

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Mr. Alhassan Shaibu | Smart Sensors | Excellence in Innovation Award

Mr. Alhassan Shaibu | Smart Sensors | Lecturer at University for development studies | Ghana

Mr. Alhassan Shaibu is an accomplished researcher and academic specializing in digital transformation, ICT policy, and socio-technical systems with a particular focus on developing economies. He is affiliated with the University for Development Studies, where he contributes significantly to advancing knowledge in digital inclusion, mobile money systems, and cybersecurity. Mr. Alhassan Shaibu holds advanced academic qualifications, including a Ph.D. in a relevant field from a reputable university, which underpin his strong theoretical and practical foundation. Throughout his career, he has been involved in various research projects, many of which emphasize international collaboration and cross-disciplinary approaches, reflecting his commitment to addressing global challenges through local solutions. His research interests are centered around the impacts of digital transformation on economic growth, inequality, and trust in ICT, particularly in the African context. Mr. Alhassan Shaibu is proficient in quantitative and qualitative data analysis, policy evaluation, and digital system assessment, skills that enable him to bridge the gap between technological innovation and socio-economic development. His scholarly output includes impactful publications in peer-reviewed journals and conference proceedings indexed in platforms such as Scopus and SSRN. Among his notable works are studies that explore the mediating effects of digital inclusion on inequality and the role of ICT regulatory environments in economic development. Mr. Alhassan Shaibu’s contributions have garnered citations, highlighting the academic community’s recognition of his work.

Professional Profile: ORCID | Google Scholar

Selected Publications:

  1. The Effects of Digital Transformation on Inequality: Does the Mediating Effects of Digital Inclusion and ICT Regulatory Environment Matter? — 2025

  2. The Impact of Digital Transformation Development on Economic Growth in Ghana — 2024

  3. The Effects of ICT Skills Development Programs on Inclusive Economic Growth in Developing Countries. Does Trust in ICT Matter?

 

Omid Abachian Ghasemi | Wireless Sensors and WSN | Best Researcher Award

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Dr. Omid Abachian Ghasemi | Wireless Sensors and WSN | Best Researcher Award

PhD Graduate at urmia university, Iran

Omid Abachian Ghasemi is a dedicated researcher in the field of wireless communications, specializing in UAV-assisted and RIS/IRS-assisted wireless networks. With a strong academic foundation, including a Ph.D. in Electrical Engineering from Urmia University (2024), his work focuses on resource and power allocation strategies in wireless-powered sensor networks. He has published several high-impact articles in renowned journals such as IEEE Internet of Things Journal, IEEE Communications Letters, IEEE Access, and Computer Networks, addressing key challenges in throughput maximization and network optimization. Proficient in MATLAB, Python, and LaTeX, Omid combines analytical expertise with practical simulation skills. Fluent in Persian, English, and Turkish, he is well-equipped for international collaboration. His research reflects a deep commitment to advancing next-generation wireless communication systems, making him a strong candidate for recognition as a leading researcher in sensing and communication technologies.

Professional Profile 

🎓 Education Background of Omid Abachian Ghasemi

Omid Abachian Ghasemi has built a solid academic foundation in the field of Electrical Engineering. He earned his Bachelor’s degree in Electrical Engineering from Tabriz University in 2012, where he developed a strong grasp of core engineering principles. Continuing his academic journey, he completed a Master of Science in Electrical Engineering (Communication) at Sahand University of Technology, Tabriz, in 2015, with a focus on advanced communication systems. Most recently, he achieved a significant milestone by completing his Ph.D. in Electrical Engineering – Wireless Communication at Urmia University in 2024, where he specialized in cutting-edge topics such as UAV and RIS-assisted wireless networks. His educational trajectory reflects a consistent dedication to mastering both theoretical and applied aspects of modern communication technologies.

💼 Professional Experience of Omid Abachian Ghasemi

Omid Abachian Ghasemi has cultivated a focused and research-driven professional career in the field of wireless communications and sensor networks. His expertise lies in the design and optimization of advanced wireless systems, particularly involving UAV-assisted, RIS/IRS-enabled, and wireless-powered sensor networks. Throughout his academic journey, he has actively contributed to multiple high-impact research projects, leading to publications in prestigious IEEE journals. His hands-on experience with simulation tools like MATLAB and Python, along with his proficiency in LaTeX for technical writing, has enabled him to develop and communicate complex algorithms and network models effectively. Although primarily rooted in academia, Omid’s work demonstrates a deep understanding of practical engineering challenges, especially in resource allocation, network throughput maximization, and next-generation communication systems, making him a valuable contributor to the future of smart wireless technologies.

🔬 Research Interests of Omid Abachian Ghasemi

Omid Abachian Ghasemi’s research interests lie at the forefront of next-generation wireless communication systems, with a particular focus on UAV-assisted networks, Reconfigurable Intelligent Surfaces (RIS/IRS), and wireless-powered sensor networks. His work centers on developing advanced resource and power allocation algorithms, aiming to maximize network efficiency and throughput in energy-constrained environments. He is especially interested in exploring TDMA and FDMA techniques within RIS-assisted architectures and optimizing UAV placement for improved connectivity and coverage. By integrating aerial platforms and intelligent reflecting surfaces into wireless systems, Omid seeks to overcome traditional limitations in wireless communication, contributing significantly to the advancement of green, adaptive, and high-performance communication networks.

🏆 Awards and Honors of Omid Abachian Ghasemi

While specific awards and honors have not been listed in the available profile, Omid Abachian Ghasemi’s recent achievements reflect a high level of academic excellence and research impact. His acceptance and publication of multiple papers in top-tier IEEE journals, such as IEEE Internet of Things Journal, IEEE Communications Letters, and IEEE Access, serve as strong indicators of his scholarly recognition in the field of wireless communications. These publications, combined with his contributions to cutting-edge research on UAV and RIS-assisted networks, suggest that he is well-positioned to receive prestigious academic and research awards in the near future. His continued dedication and innovative work make him a strong contender for honors such as the Best Researcher Award in sensing and communication technologies.

📚 Publications Top Noted

1. Joint Optimization of UAV Placement and Resource Allocation in FDMA Wireless‑Powered Sensor Networks

  • Authors: Omid Abachian Ghasemi & Mehdi Chehel Amirani
  • Year: 2025 (in IEEE Access)
  • Citation: DOI 10.1109/ACCESS.2025.3574193

2. The design of an RIS‑assisted FDMA wireless sensor network for sum throughput maximization

  • Authors: Omid Abachian Ghasemi; Masoumeh Azghani; Mehdi Chehel Amirani
  • Year: October 2025 (Computer Networks)
  • Citation: DOI 10.1016/j.comnet.2025.111512

3. Resource Allocation in a RIS‑Assisted TDMA Wireless Powered Sensor Network Using UAV

  • Authors: Omid Abachian Ghasemi & Mehdi Chehel Amirani
  • Year: June 2025 (IEEE Communications Letters)
  • Citation: DOI 10.1109/LCOMM.2025.3562118

4. Resource and Power Allocation for Sum‑Throughput Maximization in RIS‑Assisted TDMA Wireless Sensor Networks

  • Authors: Omid Abachian Ghasemi; Mehdi Chehel Amirani; Masoumeh Azghani
  • Year: July 1, 2024 (IEEE Internet of Things Journal)
  • Citation: DOI 10.1109/JIOT.2024.3390199

 Conclusion

Omid Abachian Ghasemi is a strong and promising candidate for the Best Researcher Award, particularly in the fields of intelligent wireless networks and sensor technologies. His recent and focused publication track record in top-tier IEEE journals, combined with his advanced studies and technical skill set, clearly demonstrates innovation and depth.

 

Prof. Dr. Elsadig Musa Ahmed | Sensing Technology | Best Researcher Award

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Prof. Dr. Elsadig Musa Ahmed | Sensing Technology | Best Researcher Award 

Prof. Dr. Elsadig Musa Ahmed, Multimedia University, Malaysia

Dr. Elsadig Musa Ahmed Mohammed is a distinguished Professor of Economics and Technology Management at Multimedia University (MMU), Malaysia, recognized among the 2024 World’s Top 2% Scientists by Stanford University. With over two decades of academic experience, he has published extensively in the world’s top 1% and 10% journals, authored the book Green Productivity: Applications in Malaysia’s Manufacturing, and contributed more than 150 peer-reviewed articles indexed in Scopus and Web of Science. Dr. Ahmed’s expertise spans development economics, green productivity, digital and knowledge-based economies, bioeconomy, microfinance, and the interface of economic growth with environment and technology. He has successfully supervised over 30 postgraduate theses, received multiple international research grants—including from the Malaysian Government and the Islamic Development Bank—and served as a reviewer and editorial board member for high-impact journals. His accolades include the 2024 Econometric Best Researcher Award, 2023 Sustainability Pioneers Award (WASD), and Outstanding Reviewer in the Emerald Literati Awards (2021). Dr. Ahmed is also an active contributor to global academic networks and policy think tanks, notably as a member of the Council for Sudanese Experts and Scientists Abroad.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

Summary of Suitability for the Best Researcher Award – Dr. Elsadig Musa Ahmed

Dr. Elsadig Musa Ahmed is highly suitable for the Research for Best Researcher Award based on a distinguished academic and professional track record that spans over two decades. His recognition as a member of the 2024 World’s Top 2% Scientists (Stanford List) and his publications in the Top 1% and Top 10% globally ranked journals demonstrate not only academic excellence but also a sustained global research impact.

🎓 Education

  • Ph.D. in Development Economics – Universiti Putra Malaysia, 2005
    Thesis: Impact of Air and Water Pollutant Emissions on Malaysia’s Manufacturing Sector Productivity Growth

  • M.Sc. in Development Economics – Universiti Putra Malaysia, 1998
    Thesis: Productivity and Performance of Malaysian Food Manufacturing Industry

  • B.Sc. in Agricultural Economics – Al-Azhar University, Cairo, Egypt, 1992

  • High School Certificate – Sudan

👨‍🏫 Work Experience (20+ years)

  • Professor, Multimedia University, Malaysia (2015–Present)
    Teaching postgraduate and undergraduate economics & business subjects. Supervising PhD, DBA, MPhil, MBA students.

  • Associate Professor, MMU (2010–2015)

  • Senior Lecturer, MMU (2008–2010)

  • Lecturer, MMU (2004–2008)

  • Research Assistant, Universiti Putra Malaysia (1998)

  • Storekeeper, Kenana Sugar Company, Sudan (1985–1988)

🏆 Achievements

  • Published in Top 1% and 10% international journals

  • Featured in 2024 Stanford University’s World’s Top 2% Scientists List

  • Authored 150+ international journal papers (Scopus, WoS)

  • Supervised 1 Postdoc, 14 PhDs, 4 DBAs, 3 Masters, 8 MBAs

  • Book author: Green Productivity: Applications in Malaysia’s Manufacturing (2012)

  • Reviewer/editor for top journals: Economic Modelling, Applied Economics, Emerald Publishing, etc.

  • Leader of national & international research initiatives, grant recipient, and consultant for global development and sustainability projects

🏅 Awards & Honors

  • 🥇 2024 Best Researcher Award – Young Scientist Awards

  • 🌱 2023 Sustainability Pioneers Award – World Association for Sustainable Development (WASD)

  • 🌍 Outstanding Presentation & Panelist – 2024

  • 📘 Outstanding Reviewer – Emerald Literati Awards, UK (2021)

  • 📄 Best Paper Award – XXth CEDIMS Conference, Laval University, Canada (2010)

  • 🎖️ Excellent Research Awards & Long Service Award – Multimedia University, Malaysia

Publication Top Notes:

A cyber physical sustainable smart city framework toward society 5.0: Explainable AI for enhanced SDGs monitoring

The Assessment of Sustainable Development Goals Through the Impact of Exploring Digital Technology Innovation and Climate Change Integration, Conflicts and Natural Disasters

Digitalization and Climate Change Spillover Effects on Saudi Digital Economy Sustainable Economic Growth

Palestinian small and medium enterprises digital technology adoption intention

Enhancing environmental quality and economic growth through potential effects of energy efficiency and renewable energy in Asian economies

Testing technological Kuznets curve implications on achieving sustainable development goal 10 in seven Asian countries

Globalization and financial development contributions toward economic growth in Sudan

Prof. Junhao Li | Sensors Design | Best Innovation Award

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Prof. Junhao Li | Sensors Design | Best Innovation Award

Prof. Junhao Li, Xi’an Jiaotong University, China

Junhao Li is a Full Professor at Xi’an Jiaotong University, where he is actively engaged in teaching and research in the field of electrical engineering. His research primarily focuses on two key areas: fault diagnosis of power equipment, including power transformers and gas-insulated switchgear (GIS), and on-site testing for power equipment, particularly impulse testing for GIS and transformers. His work on partial discharge (PD) research explores PD characteristics under various voltage waveforms, employing optical, UHF, and acoustic measurement techniques along with PD pattern recognition. Additionally, his studies on impulse testing address waveform adjustments, distortion effects, equipment protection methods, and insulation breakdown mechanisms in SF₆ gas and oil-paper insulation.

Professional Profile:

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Summary of Suitability for Best Innovation Award conclusion

Junhao Li is a highly accomplished researcher in the field of electrical engineering, particularly in power equipment fault diagnosis, partial discharge (PD) measurement, and onsite testing for power equipment. His contributions to PD detection techniques, integration of optical and UHF methods, and advancements in impulse testing are innovative and impactful.

Education 🎓:

  • Specific details about Professor Li’s educational background are not provided in the available information.

Work Experience 🏫:

  • Full Professor at Xi’an Jiaotong University: Engaged in teaching and research in electrical engineering, focusing on fault diagnosis of power equipment and on-site testing for power equipment.

Achievements and Honors 🏆:

  • Research Contributions: Specializes in partial discharge research, examining characteristics under various voltage waveforms, and developing measurement and pattern recognition methods.
  • On-Site Testing Innovations: Focuses on on-site impulse testing for GIS and power transformers, including waveform adjustment methods and equipment protection strategies.
  • Professional Recognitions:
    • Fellow of the Institution of Engineering and Technology (IET)
    • Senior Member of the Institute of Electrical and Electronics Engineers (IEEE)
    • Editorial Board Member of the Chinese journal “High Voltage Apparatus”
    • Member of the CIGRE D1 China Committee
    • Member of CIGRE Working Groups D1.66 and B3.50
    • Member of IEC TC 17 / SC 17C AHG41
    • Executive Member of the IEEE PES Smart Grid and New Technology Committee (China)
    • Associate Editor of IEEE Transactions on Dielectrics and Electrical Insulation

Professor Li has published numerous papers in IEEE Transactions focusing on transformers and liquid insulation. He is committed to enhancing the relationship between international electrical insulation publications and China, aiming to expand their influence and contribute to their success.

Publication Top Notes:

Review on partial discharge measurement technology of electrical equipment

CITED:182

Digital detection, grouping and classification of partial discharge signals at DC voltage

CITED:144

A novel GIS partial discharge detection sensor with integrated optical and UHF methods

CITED:143

Partial discharge characteristics over differently aged oil/pressboard interfaces

CITED:85

A novel PD detection technique for use in GIS based on a combination of UHF and optical sensors

CITED:79

Investigation of a comprehensive identification method used in acoustic detection system for GIS

CITED:77