Ihsan Ullah | Neural Network | Best Researcher Award

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Mr. Ihsan Ullah | Neural Network | Best Researcher Award

Mr. Ihsan Ullah, Abdul Wali khan university Marden Kp Pakistan, Pakistan

Ihsan Ullah is a dedicated researcher in fuzzy systems and artificial intelligence, pursuing an M.Phil in Mathematics at Abdul Wali Khan University, Mardan, Pakistan. With a solid foundation from his BS in Mathematics (CGPA 3.48/4), his research interests include fuzzy decision-making, neural networks, IoT, and multi-criteria decision-making. Ihsan has authored impactful papers in high-impact journals, including IEEE Access and Artificial Intelligence Review. Skilled in MATLAB and Mathematica, he also reviews for prestigious journals like Expert Systems with Applications. Fluent in English, Urdu, and Pashto, Ihsan is passionate about advancing AI for complex decision-making challenges. 📚💻✈️

 

Publication Profile

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Google Scholar

Educational Background

Ihsan Ullah is pursuing an M.Phil in Mathematics at Abdul Wali Khan University, Mardan, Pakistan (2023–present), maintaining an impressive CGPA of 3.69/4 (coursework only; thesis ongoing) 📊. He holds a BS in Mathematics from the same institution (2019–2023), graduating with a CGPA of 3.48/4. His undergraduate project focused on “Double Hierarchy Hesitant Linguistic Term Set and Their Application to Decision-Making Problems” 🤖✨. Ihsan is affiliated with the Department of Mathematics at Abdul Wali Khan University 📍 and actively engages in academic platforms like ORCID, Google Scholar, and ResearchGate 🌐

Research Interests

Ihsan Ullah’s research is centered around innovative approaches to decision-making and optimization using advanced computational techniques. His interests include fuzzy decision-making systems 🤖, artificial neural networks 🌐, and fuzzy neural networks, with applications in multi-criteria decision-making and network selection. He explores fuzzy credibility neural networks and optimization techniques to enhance problem-solving. Ihsan also focuses on fuzzy graph theory 🕸️, graph neural networks, and three-way decision-making processes. His work extends to linguistic neural networks 🗣️, the Internet of Things (IoT) 🌐, and fuzzy control systems ⚙️, aiming to create intelligent systems for real-world applications.

 

Publication Top Notes

  • “A new approach to neural network via double hierarchy linguistic information: Application in robot selection” – Y Zhang, S Abdullah, I Ullah, F Ghani – Engineering Applications of Artificial Intelligence 129, 107581 (Cited by: 30) 📊, 2024 📅
  • “A new approach to artificial intelligent based three-way decision making and analyzing S-Box image encryption using TOPSIS method” – S Abdullah, AO Almagrabi, I Ullah – Mathematics 11(6), 1559 (Cited by: 12) 📚, 2023 📅
  • “Analyzing the deep learning techniques based on three way decision under double hierarchy linguistic information and application” – S Abdullah, I Ullah, F Khan – IEEE Access (Cited by: 5) 🧠, 2023 📅
  • “Using a fuzzy credibility neural network to select nanomaterials for nanosensors” – SS Abosuliman, S Abdullah, I Ullah – Engineering Applications of Artificial Intelligence 136, 108958 (Cited by: 3) 🔬, 2024 📅
  • “Heterogeneous wireless network selection using feed forward double hierarchy linguistic neural network” – S Abdullah, I Ullah, F Ghani – Artificial Intelligence Review 57(8), 191 (Cited by: 2) 🌐, 2024 📅
  • “An integrated fuzzy neural network model for surgical approach selection using double hierarchy linguistic information” – M Nawaz, S Abdullah, I Ullah – Computers in Biology and Medicine 186, 109606 (Cited by: 0) 🏥, 2025 📅

 

 

 

Orelien BOUPDA | Energy | Best Researcher Award

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Dr. Orelien BOUPDA | Energy | Best Researcher Award

Dr. Orelien BOUPDA, Université Douala/ENSPD, Cameroon

Born on April 9, 1993, in Douala, Cameroon, Dr. Orelien BOUPDA is a skilled Thermal and Energy Engineer. He holds a Master 2 in Mechanical Energy Research from ENSPD Douala (2021) and a Master 2 in Thermal Energy from ENSAI Ngaoudéré (2016). His expertise spans electromechanics, industrial electricity, refrigeration, air conditioning, and solar energy systems. Dr. BOUPDA is proficient in technical schematics, industrial automation, and photovoltaic installations. Fluent in French and intermediate in English, he thrives in cross-disciplinary environments. An avid traveler and reader 📚✈️, he combines technical prowess with a passion for cultural exploration. 🌟

 

Publication Profile

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Educational Journey

Dr. Orelien BOUPDA has a remarkable academic background in thermal and energy engineering. He earned a Master 2 in Mechanical Energy Research from ENSPD Douala (2020-2021) and a Master 2 in Thermal Energy Engineering from ENSAI Ngaoudéré (2015-2016). He also holds a professional license in Maintenance and Industrial Production (2013-2014) with a focus on Energy and Climate Engineering. Additionally, he completed a BTS in Refrigeration and Air Conditioning at IUG (2012-2013) and obtained his Baccalaureate F5 in Refrigeration and Air Conditioning from Lycée Technique de Nylon Douala (2010-2011). 🌍🔧⚡

 

Technical Expertise

Dr. Orelien BOUPDA demonstrates extensive expertise in various technical domains. His skills include industrial automation and electrotechnics, specializing in wiring, coupling, and maintaining electric circuits and motors. He excels in industrial and building electricity, handling design, dimensioning, wiring, and maintenance. Proficient in refrigeration and air conditioning ❄️, he designs, installs, and maintains cold storage systems and other cooling equipment. His electromechanical skills cover the installation and upkeep of generators. Dr. BOUPDA also specializes in solar energy 🌞, particularly in photovoltaic systems, and has advanced proficiency in technical schematics and computer tools. His knowledge reflects versatility and innovation. 🚀

 

Research Focus

Dr. Orelien BOUPDA’s research primarily focuses on sustainable energy systems, refrigeration technologies, and thermodynamic analysis. His notable work, Development and exergo-energetic analysis of an energy-efficient solar-assisted transcritical CO2 refrigeration system with two-phase ejector 🌍🔬, explores innovative solutions for improving energy efficiency in refrigeration systems using solar energy and advanced thermodynamic processes. This study highlights his expertise in energy conversion, CO2 refrigeration, and eco-friendly technologies aimed at reducing environmental impact. Dr. BOUPDA’s research aligns with global priorities in renewable energy integration and sustainable engineering, making significant contributions to green energy initiatives. ♻️🚀

 

Publication Top Notes

Development and exergo-energetic analysis of an energy-efficient solar-assisted transcritical CO2 refrigeration system with two-phase ejector

 

 

Samia Moulebhar | Energy Award | Best Researcher Award

Published on by Global Academic Awards

Ms. Samia Moulebhar | Energy Award | Best Researcher Award

Ms. Samia Moulebhar, universite mostaganem, Algeria

Ms. Samia Moulebhar is a dedicated researcher and PhD candidate in Embedded Electronic Systems at Université Mostaganem (2023). With a Master’s in Instrumentation from Université Belhadj Bouchaib Ain Temouchent, her work focuses on applying artificial intelligence to diagnostics and renewable energy solutions. Samia has presented at international conferences on the performance of organic solar cells and has contributed significantly to publications in advanced solar technology, including a paper on optimizing solar cell efficiency using multiobjective genetic algorithms. Proficient in tools like Matlab, SCAPS-1D, and Proteus, Samia also lectures in electronics and physics. 💻📈

 

Publication Profile

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Academic Background 

Ms. Samia Moulebhar is currently pursuing a PhD in embedded electronic systems (2023) and holds a Master’s in Instrumentation from Université Belhadj Bouchaib Ain Temouchent (2022). Her Bachelor’s in Electrical Engineering focused on electronics, and she has also earned a BTS in database informatics. Proficient in tools such as Matlab, SCAPS-1D, Proteus, and Arduino, she demonstrates strong technical capabilities essential for advanced research in electronics and renewable energy systems.

Research Contributions

Ms. Moulebhar has a solid record of research publications, particularly in the field of organic solar cell technology. She has presented at multiple notable conferences, such as the First National Conference on Material Sciences and Renewable Energy, where she discussed improvements in organic solar cell efficiency, and at the International Conference on Renewable Energies and Power Systems (ICREPS 2024). Her presentation on absorber layer effects in organic solar cells at the Workshop on Sustainability and Advanced Technologies is a testament to her commitment to advancing sustainable energy solutions.

Research Focus

Her published work includes an influential paper on optimizing organic solar cells using hybrid approaches, incorporating NSGA-II, SCAPS-1D simulation, and response surface methodology. This research, featured in physica status solidi (a), showcases her focus on cutting-edge optimization techniques, addressing both performance and efficiency in solar technology.

Professional Experience

With teaching experience at Université Belhadj Bouchaib and roles in instrumentation and computer services, Ms. Moulebhar combines academic research with practical application. This background enhances her capability to bridge theoretical knowledge with real-world applications, particularly in the sustainable energy sector.

Conclusion

Ms. Samia Moulebhar is a promising candidate for the Best Researcher Award due to her focused research on organic solar cell technologies, extensive conference participation, and a track record of published research. Her technical expertise and ongoing contributions to renewable energy systems demonstrate her potential as an innovative researcher in the field of electronics and sustainable technologies.

 

Publication Top Notes

Hybrid Optimization Approach Using Multiobjective Genetic Algorithm NSGA‐II, SCAPS‐1D Simulation, and Response Surface Methodology for Organic Solar Cell Analysis