Leyla Akbulut | Energy | Best Researcher Award

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Ms. Leyla Akbulut | Energy | Best Researcher Award

Ms. Leyla Akbulut | Energy | Alanya Alaaddin Keykubat University | Turkey

Leyla Akbulut is an accomplished academic and energy researcher specializing in electrical and electronics engineering, with a strong focus on renewable energy systems, energy efficiency, and power distribution optimization. She currently serves as a Lecturer at Alanya Alaaddin Keykubat University, where she contributes extensively to teaching, research, and project leadership in the Department of Electrical and Energy. With both academic and industry experience, Akbulut has played pivotal roles in national and institutional projects, including the establishment of solar power plants and optimization of energy distribution networks. Her academic journey is marked by a strong foundation at Gazi University and advanced research at Isparta University of Applied Sciences, where she pursued her doctoral studies. She has authored influential publications in international journals, addressing energy cost optimization, metaheuristic algorithms, and renewable energy investment analysis. Recognized through national and European awards, Leyla Akbulut continues to bridge academia and practice in shaping sustainable energy solutions.

Author Profile

Orcid | Google Scholar

Education

Leyla Akbulut began her academic journey at Gazi University, completing her Bachelor’s degree in Electrical-Electronics Engineering in 2012. She further pursued a Master’s degree in the same field at Gazi University’s Institute of Science, successfully defending her thesis on electrical distribution network optimization in 2019 under the supervision of Dr. Süleyman Sungur Tezcan. Building on this strong research foundation, she advanced to doctoral studies at Isparta University of Applied Sciences, where she specialized in Electrical-Electronics Engineering (Ph.D.). Her doctoral research further refined her expertise in the optimization of distribution networks, energy efficiency, and renewable energy integration. Throughout her academic development, she combined technical skills with practical project applications, supported by specialized certifications in energy management, quality systems, and occupational safety. This educational progression not only solidified her as an expert in electrical systems and energy distribution but also positioned her as a forward-thinking researcher contributing to the future of energy sustainability.

Experience

Leyla Akbulut has a multifaceted career that blends academia, applied research, and industry expertise. Since 2017, she has served as a Lecturer at Alanya Alaaddin Keykubat University, teaching and mentoring in the Electrical and Energy Department, while actively contributing to renewable energy projects and campus sustainability initiatives. She has held administrative responsibility as the Head of the Energy Management Unit at the Rectorate, overseeing energy policies and performance strategies. Her professional background includes significant roles in the private sector with MERAM Elektrik Dağıtım A.Ş., where she worked as an R&D Engineer, GIS Engineer, and Elder R&D Group Representative, contributing to distribution system design, optimization, and regulatory compliance. She also gained hands-on engineering expertise in photovoltaic projects and urban transformation projects as a freelance and site engineer. With combined academic and field experience, she has developed a strong reputation for bridging energy research, project implementation, and policy-driven energy efficiency.

Awards and Honors

Leyla Akbulut’s career has been marked by recognition at both national and international levels for her contributions to energy efficiency and sustainable practices. In 2025, she received the Verimlilik Artırıcı Proje Ödülü (Efficiency Enhancing Project Award) from the Turkish Ministry of Science, Industry, and Technology, acknowledging her impactful work in energy-saving initiatives. The same year, her leadership and innovation in energy-focused projects were recognized by the European Commission in Denmark, where she was honored with the European Enterprise Promotion Award 2025. These awards highlight her dedication to creating practical, efficient, and forward-looking energy solutions that bridge academic research and industrial application. Beyond formal awards, Akbulut’s projects in solar energy integration, energy performance contracting, and distribution network optimization stand as evidence of her commitment to advancing renewable energy deployment. Her achievements reflect her ability to lead collaborative projects with measurable outcomes in sustainability and energy transformation.

Research Focus

Leyla Akbulut’s research is centered on renewable energy systems, distribution network optimization, and energy efficiency. Her work integrates advanced algorithms, particularly metaheuristic approaches, to improve demand-side management, cost estimation, and system reliability in energy networks. She has extensively studied the application of solar energy systems, including photovoltaic installations for campus-scale and public-sector projects, focusing on both technical and financial performance. Another area of her expertise is energy performance contracting, where she explores how sustainable financing models can drive the adoption of renewable energy in institutional infrastructures. Her research also addresses economic efficiency in renewable investments, applying regression analysis to evaluate large-scale photovoltaic projects. By combining engineering design, mathematical modeling, and applied fieldwork, Akbulut contributes to both academic literature and practical energy solutions. Her forward-looking research continues to support the transition toward greener energy systems, offering innovative strategies for cost-effective, efficient, and sustainable power generation.

Publications

  1. Solar-Powered Biomass Revalorization for Pet Food and Compost: A Campus-Scale Eco-Circular System – Processes, 2025

  2. Economic Efficiency of Renewable Energy Investments in Photovoltaic Projects: A Regression Analysis – Energies, 2025

  3. Review of Metaheuristic Algorithms for Energy Efficiency, Demand Side Management and Cost Estimation – Rocznik Ochrona Środowiska, 2025

  4. Analysis of Electrical Distribution Network Voltage Configuration with Mixed Integer Linear Programming and Genetic Algorithm – Electrica, 2020

  5. Dağıtım Şebekesi Gerilim Konfigürasyonunun Enerji Maliyeti Yönünden Araştırılması – Mühendislik Bilimleri ve Tasarım Dergisi, 2019

  6. Kamu Binalarında Güneş Enerji Santrali Kurulumunda Finansman Modelleri ve Enerji Verimliliği Uygulaması – VII. Elektrik Tesisleri Ulusal Kongresi, 2023

Conclusion

Leyla Akbulut is a dynamic academic and energy professional whose career reflects a seamless integration of research, education, and applied engineering. Her academic foundation, diverse professional experiences, and impactful research make her a key contributor to the field of renewable energy and power distribution. Recognized with national and European awards, her leadership in energy performance projects and publications in high-impact journals underline her commitment to shaping sustainable energy systems. Through her work, she embodies the values of innovation, efficiency, and collaboration that align perfectly with the mission of advancing global energy solutions.

Dr. Mlungisi Duma | Artificial Intelligence | Best Researcher Award

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Dr. Mlungisi Duma | Artificial Intelligence | Best Researcher Award

Dr. Mlungisi Duma, University of Johannesburg, South Africa

Dr. Mlungisi Duma is a Senior Researcher and Development Manager at the University of Johannesburg. With over 19 years of experience in the IT profession, he has a rich background in software development and management. Dr. Duma holds a PhD in Electronic and Electrical Engineering, specializing in Artificial Intelligence, from the University of Johannesburg. His research focuses on machine learning, evolutionary computation, and optimization algorithms. He has successfully led numerous projects, published in top-tier journals, and is an active reviewer for multiple prestigious journals. His expertise extends to consultancy, where he manages application development for First National Bank, overseeing code maintenance for ATM systems. Dr. Duma’s contributions to academia and industry showcase his dedication to innovation and leadership in AI research.

Professional Profile

Scopus

Summary of Suitability for the Research for Best Researcher Award

Dr. Mlungisi Duma’s diverse contributions to the fields of artificial intelligence and evolutionary computation, along with his leadership in both academia and industry, make him highly suitable for the ‘Research for Best Researcher Award’. His ability to bridge the gap between theoretical research and real-world applications, coupled with his strong publication record and professional recognition, demonstrate his excellence as a researcher. He is well-positioned to receive this award, as his work contributes significantly to advancing the field of artificial intelligence.

🎓  Education 

Dr. Mlungisi Duma holds a Master’s degree in Computer Science and a PhD in Electronic and Electrical Engineering, both from the University of Johannesburg. His PhD specialization in Artificial Intelligence equipped him with expertise in machine learning, evolutionary computation, and optimization algorithms. Throughout his academic journey, Dr. Duma has actively engaged in cutting-edge research projects, collaborating with renowned academics and professionals. His commitment to education has been reflected in his role as a judge and reviewer at various academic institutions and scientific journals. As a Senior Member of IEEE and ACM, he continues to contribute to the advancement of AI technologies. Dr. Duma’s academic background is a testament to his passion for innovation, making significant contributions to the field of Artificial Intelligence.

 💼  Experience

With 19 years of experience in the IT industry, Dr. Mlungisi Duma has held various technical and leadership roles. For nine years, he worked as a software developer, honing his skills in coding, system architecture, and application design. Following this, he spent a decade as a Development Manager and Software Architect at First National Bank, where he led teams responsible for developing and maintaining ATM systems. Currently, he is a Senior Researcher and Development Manager at the University of Johannesburg, where he leads AI research initiatives. His extensive experience spans both academic and industry settings, bridging the gap between theoretical research and practical applications. Dr. Duma’s ability to manage multidisciplinary teams and deliver innovative solutions reflects his leadership and technical acumen.

🏅Awards and Honors 

Dr. Mlungisi Duma has received several prestigious awards and honors for his contributions to Artificial Intelligence and software development. He is a Senior Member of IEEE and ACM, recognizing his influence in the academic and professional communities. Dr. Duma’s work has also been recognized through his membership in the Golden Key International Honour Society, a distinction for top-performing academics globally. He has served as a judge at the University of Johannesburg’s Academy of Computer Science project day and has been a frequent reviewer for renowned journals, including IEEE Access, Applied Soft Computing, and the Journal of Mathematical Problems in Engineering. These honors highlight Dr. Duma’s commitment to academic excellence and his significant contributions to advancing AI technologies.

 🌍 Research Focus

Dr. Mlungisi Duma’s research focuses on Artificial Intelligence, particularly in the fields of machine learning, evolutionary computation, and optimization algorithms. He has contributed extensively to developing novel AI models for predictive modeling, control parameter optimization, and feature selection. His recent work includes optimizing ant colony algorithms and using artificial immune systems for collaborative filtering in recommender systems. Dr. Duma’s research is not only theoretical but also has practical applications, as demonstrated by his consultancy projects for First National Bank, where AI-driven solutions are implemented in ATM systems. He has published widely in top-tier journals, reflecting his thought leadership in AI and its applications in diverse sectors. His current projects aim to enhance AI’s role in automation and decision-making across industries.

 📖 Publication Top Notes

  • Sparseness reduction in collaborative filtering using a nearest neighbour artificial immune system with genetic algorithms
    • Citations: 22
  • Optimising latent features using artificial immune system in collaborative filtering for recommender systems
    • Citations: 20
  • Partial imputation of unseen records to improve classification using a hybrid multi-layered artificial immune system and genetic algorithm
    • Citations: 30
  • Classification with missing data using multi-layered artificial immune systems
    • Citations: 4
  • Partial imputation to improve predictive modelling in insurance risk classification using a hybrid positive selection algorithm and correlation-based feature selection
    • Citations: 2

Mr.Danish Javed | Data Science | Best Researcher Award

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Mr.Danish Javed | Data Science | Best Researcher Award

Mr.Danish Javed, Taylor’s University Lakeside Campus, Malaysia

Danish Khan is a Ph.D. scholar specializing in Data Science at Taylor’s University, Malaysia, where he is advancing research in natural language processing (NLP). With a strong academic background in Software Engineering from Bahria University, Islamabad, Danish has built expertise in Python, machine learning, and deep learning. He has held teaching roles as a Senior Lecturer at the University of Central Punjab, Lahore, and is currently a tutor at Taylor’s University, Malaysia. His career reflects a commitment to advancing computer science education, mentoring students, and leading post-graduate councils. Danish is also a prolific researcher, contributing to various data science and sentiment analysis projects, particularly in the analysis of social media content and NLP.

Professional Profile

google scholar

Summary of Suitability for the Research for Best Researcher Award

Danish Javed presents a strong candidacy for the Research for Best Researcher Award based on his significant academic and research contributions, particularly in the fields of data science, machine learning, and natural language processing (NLP). His ongoing PhD in Data Science from Taylor’s University demonstrates his deep commitment to advancing research, especially in topics like sentiment analysis, deep learning, and Twitter bot detection. Danish has published research in Scopus-indexed conferences and Q1/Q4 journals, which highlights the academic impact of his work.

🎓 Education 

Danish Khan has consistently pursued excellence in academia, currently working toward his Ph.D. in Data Science at Taylor’s University, Lakeside Campus, Malaysia. His doctoral research focuses on natural language processing (NLP), specifically exploring frameworks for sentiment analysis, bot detection, and text analytics. Prior to his Ph.D., Danish earned his M.S. in Software Engineering from Bahria University, Islamabad, Pakistan, where he delved into the intricacies of machine learning, image processing, and artificial intelligence. His academic foundation also includes a B.S. in Software Engineering from Bahria University, during which he developed strong programming skills in Python, Java, and C++, equipping him with the tools to tackle complex computational problems. His academic journey reflects his deep interest in understanding data structures and algorithms, making him proficient in implementing advanced analytics and programming solutions.

💼 Experience 

Danish Khan has a broad range of teaching and leadership experience, with over five years in academia. He is currently a Tutor at Taylor’s University, Malaysia, where he conducts tutorials in data science, supervises student projects, and plays a key role in shaping the post-graduate student experience. He previously served as the President of the Post-Graduate Student Council, organizing events and representing student perspectives in university meetings. Prior to his current role, Danish was a Senior Lecturer in the Faculty of Information Technology at the University of Central Punjab, Lahore, where he taught computer science and software engineering courses, supervised final-year projects, and contributed to extracurricular activities such as organizing sporting events. Additionally, Danish has experience as a QA Analyst at Orbit Institute of Technology in Lahore, where he maintained the quality standards in the Software Engineering department.

🏅Awards and Honors

Danish Khan has received notable recognition throughout his academic and professional career. His published research in data science and natural language processing has been featured in prominent Scopus-indexed conferences and reputed journals. As a Ph.D. scholar, he has been honored with several merit-based scholarships for academic excellence. Danish was also recognized for his leadership efforts while serving as President of the Post-Graduate Student Council at Taylor’s University, where he played a pivotal role in advocating for post-graduate student welfare. During his tenure at the University of Central Punjab, Lahore, he earned commendations for his outstanding contributions to teaching and student mentorship. Additionally, his development of an Android application, “Forex Profit Gain,” has garnered attention, earning placement in the Google Play Store. These accolades reflect his deep commitment to both academic rigor and innovative problem-solving in the field of data science.

🌐 Research Focus 

Danish Khan’s research is centered on data science, particularly natural language processing (NLP), machine learning, and sentiment analysis. His Ph.D. work at Taylor’s University, Malaysia, focuses on advanced techniques in deep learning to analyze and classify text-based data. His key areas of research include social media analytics, Twitter bot detection, and sentiment analysis of public opinion during crises such as the COVID-19 pandemic. Danish has contributed to frameworks that improve sentiment analysis by leveraging oversampling techniques and random minority oversampling, which enhance the accuracy of sentiment classification in user-generated content. His research also extends to explainable artificial intelligence (AI), where he has designed models for transparent and interpretable detection of bots on social media platforms. Danish’s academic pursuit aims to contribute practical, data-driven insights to solve real-world problems using cutting-edge AI and NLP technologies.

📖 publications Top Notes

“Framework for Improved Sentiment Analysis via Random Minority Oversampling for User Tweet Review Classification.”
Citation count: 25
“Deep Learning Based Sentiment Analysis of COVID-19 Tweets via Resampling and Label Analysis.”
Citation count: 6
“Football Analytics for Goal Prediction to Assess Player Performance.”
Citation count: 4
“Explainable Twitter Bot Detection Model for Limited Features.”
Citation count: 2
“Explainable Machine Learning Based Model for Heart Disease Prediction.”
“Analyzing the Efficacy of Bot Detection Methods on Twitter/X.”

kelig mahe | fisheries research | Research Excellence Award

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Dr kelig mahe | fisheries research | Research Excellence Award

Dr.kelig mahe, Ifremer, France

Dr. Kélig MAHE is a leading researcher at IFREMER, specializing in marine science, particularly in the fields of sclerochronology and fisheries. Since 2021, he has been the head of the Halieutiques Manche-Mer du Nord Unit, overseeing numerous national and European projects related to fish age estimation and stock management. Dr. MAHE’s expertise spans biological data coordination, fish age determination workshops, and the development of TNPC software. He has co-supervised 11 PhD students and 12 master’s students, contributing significantly to scientific innovation, as demonstrated by his 2010 award for scientific and technological innovation at IFREMER. His contributions extend internationally, with leadership in numerous European research collaborations.

Professinal Profile

  • orcid

    Education 

    Dr. Kélig MAHE’s academic journey is rooted in marine and environmental sciences. He earned his PhD in Marine Biology from Université du Littoral Côte d’Opale (ULCO) in 2019, focusing on fisheries and environmental ecosystems. Prior to this, he completed his Diplôme d’Etudes Approfondies (DEA) in Coastal and Littoral Ecosystem Dynamics from ULCO in 2002. Dr. MAHE’s foundational knowledge in marine resource management was shaped during his engineering studies at the prestigious Ecole Nationale Supérieure d’Agronomie de Rennes (ENSAR), where he graduated with a specialization in Halieutics in 2003. His multidisciplinary education also includes a Maîtrise des Sciences et Techniques in Environmental Sciences from the University of Rouen, completed in 2001, providing him with a well-rounded scientific background in both marine biology and environmental management.

    Experience 

    Dr. MAHE Kélig has an extensive research career at IFREMER, where he has been actively engaged since 2007. His role evolved from a research cadre to leading the Halieutiques Manche-Mer du Nord Unit in 2021. His vast experience includes coordinating national biological data, managing research programs on fish age estimation, and providing expert advice on stock management. His involvement in European research projects is extensive, including leadership positions in projects like Med-Units, Sumaris, and Microtolithe. Dr. MAHE has also represented IFREMER in international workshops and played a pivotal role in advancing sclerochronology, both through research and the development of TNPC software. His management experience includes overseeing teams and mentoring students, making significant contributions to both scientific research and talent development.

    Awards and Honors 

    Dr. MAHE Kélig’s distinguished contributions to marine science have earned him notable recognition. In 2010, he was awarded the IFREMER Trophée de l’innovation for his pioneering work in scientific, technical, and technological fields. His leadership and contributions have made a global impact, notably in European research collaborations, where he co-chaired 13 international workshops and participated in 4 European working groups. His expertise in sclerochronology has positioned him as an expert for IFREMER in international fora. Dr. MAHE’s influence extends to organizing international symposia, such as the 6th International Symposium on Biological Shape Analysis in 2019. His collaborative spirit and innovative work have consistently advanced marine research, particularly in fisheries biology, earning him respect and recognition within the global scientific community.

    Research Focus

    Dr. MAHE Kélig’s research centers on sclerochronology, the study of calcified structures in fish, to improve age determination methods and enhance fisheries management. His work plays a critical role in understanding fish population dynamics and the impacts of environmental changes, such as temperature fluctuations and CO2 levels, on marine species. Dr. MAHE has been at the forefront of integrating modern technologies in fisheries research, particularly through his contributions to the TNPC software for processing calcified structures. His research also extends to interdisciplinary collaborations, where he has led and participated in numerous European projects, focusing on sustainable fishery practices, species population structures, and biogeographical studies. His commitment to research excellence is evidenced by his active role in advancing knowledge in otolith morphogenesis, age determination, and stock management, all of which are pivotal for sustainable marine resource management.

     Publications Top Notes

    1. 🐟 Asymmetry of Sagittal Otolith Shape in Mediterranean Red Mullet: Comparative Analysis of 2D and 3D Otolith Shape Data (2023).
    2. 🌊 Effect of Temperature and CO2 on Morphogenesis of Sagittal Otoliths in Atlantic Herring (2023).
    3. 📊 Spatial Structuring of Demersal Fish Around Réunion Island Based on Otolith Shape (2023).
    4. 🧬 New Scale Analyses Reveal Centenarian African Coelacanths (2021).
    5. 🐠 Complementarity and Discriminatory Power of Genotype and Otolith Shape in Eastern English Channel Sole (2020).