Lecturer | Osun State University | Nigeria

Dr. Oluwatobi Adedamola Ayilara-Adewale is a computer science researcher specializing in machine learning, AI-driven cybersecurity and intelligent systems, serving as an academic and research contributor in these domains. With advanced degrees in computer science and a strong foundation in computational methods and digital systems, he has gained professional experience through participation in national and international research projects involving digital resilience, smart agriculture, climate-focused data analytics and secure digital infrastructures, often providing technical leadership in multidisciplinary teams. His research focuses on artificial intelligence, IoT security, intrusion detection, blockchain security, predictive analytics and cyber-resilient architectures, supported by numerous peer-reviewed publications spanning journals, conference outputs and book chapters. He has contributed to the development of machine learning models for security, intelligent decision-support systems and emerging frameworks for digital trust. Dr. Ayilara-Adewale has received recognition for innovative research and holds professional certifications in cloud computing, cybersecurity and penetration testing. He is an active member of multiple professional bodies, reflecting his commitment to advancing knowledge in computing and cybersecurity, and he has engaged in collaborative initiatives that strengthen the ecosystem of applied AI research. His growing scholarly profile, technical versatility and dedication to secure and intelligent systems position him as a valuable contributor to contemporary research and a strong candidate for excellence awards.

Profiles: Google Scholar

Featured Publications

1. Jimoh, K., Ajayi, A., & Ayilara, O. (2014). Intelligent model for manual sorting of plastic wastes. International Journal of Computer Applications, 101(7), 20–26.

2. Jimoh, K. O., Adepoju, T. M., Sobowale, A. A., & Ayilara, O. A. (2018). Offline gesture recognition system for Yorùbá numeral counting. Asian Journal of Research in Computer Science, 1(4), 1–11.

3. Ajayi, A. O., Jimoh, K. A., & Ayilara, O. A. (2016). Evaluation of plastic waste classification systems. British Journal of Mathematics & Computer Science, 16(3), 1–11.

4. Ayilara, M. S., Fasusi, S. A., Ajakwe, S. O., Akinola, S. A., Ayilara-Adewale, O. A., … (2025). Impact of climate change on agricultural ecosystem. In Climate change, food security, and land management: Strategies for a sustainable future.

5. Olanrewaju, A., & Ayilara, O. A. (2024). The effect of data compromises on internet users: A review on financial implication of the elderly in the United States. African Journal of Social Sciences and Humanities Research, 1, 28–37.

Dr. Oluwatobi Adedamola Ayilara-Adewale’s work advances secure and intelligent digital ecosystems by integrating artificial intelligence with resilient cybersecurity frameworks. His research contributes to safer technologies, sustainable data-driven solutions and innovative systems that support societal development, industry transformation and global digital trust.

Hiyam Farhat | Digital twins | Best Researcher Award

Published on 18/11/202518/11/2025 by World Top Scientists

Dr. Hiyam Farhat | Digital twins | Best Researcher Award

Lecturer | Tennessee Tech University | United States

Dr. Hiyam Farhat, a Lecturer and Assistant Director at the DOE Industrial Assessment Center in the Department of Mechanical and Nuclear Engineering at Tennessee Technological University, is a materials and mechanical engineering specialist whose work integrates advanced materials, manufacturing technologies, turbomachinery performance, and energy-efficiency research. She holds a PhD in Mechanical and Industrial Engineering, an MS in Mechanical and Materials Engineering, and a BS in Mechanical Engineering, underpinning a career that spans academic, research, and leadership roles across major engineering organizations. Her professional experience includes directing industrial assessment initiatives, managing engineering programs in the turbomachinery sector, contributing to quality and inspection systems, and teaching a broad range of engineering courses with demonstrated excellence. Her research focuses on AI-driven modeling, digital-twin development, materials degradation prediction, and clean-energy technologies, resulting in influential publications in areas such as hybrid digital-twin frameworks, gas turbine performance, flexible operation lifing criteria, and energy-storage applications. She has delivered invited presentations and contributed chapters to leading technical references, with her work supported by collaborations with national and international partners. Her recognitions include awards for technical presentations, and she maintains active engagement through memberships in professional societies such as ASME, KEEN, and the European Turbine Network. She also holds certifications in research ethics, nondestructive testing, welding inspection, quality auditing, and safety oversight. Dr. Farhat’s record reflects sustained innovation, cross-disciplinary expertise, and impactful contributions to advancing energy sustainability and intelligent engineering systems.

Profiles: Google Scholar | Scopus

Featured Publications

1. Farhat, H., & Salvini, C. (2022). Novel gas turbine challenges to support the clean energy transition. Energies, 15(15), 5474.

2. Farhat, H. (2021). Operation, maintenance, and repair of land-based gas turbines.

3. Farhat, H. (2021). Materials and coating technologies. In Operation, maintenance, and repair of land-based gas turbines (pp. 63–87).

4. Farhat, H., & Salvini, C. (2022). New lifing criterion for land-based gas turbines in flexible operation mode. Energy Reports, 8, 379–385.

5. Farhat, H. (2021). Lifetime extension: Assessment and considerations. In Operation, maintenance, and repair of land-based gas turbines (pp. 175–196).

Dr. Hiyam Farhat’s work advances intelligent energy systems by integrating AI-driven modeling, digital-twin technologies, and materials degradation analytics to enhance performance, reliability, and sustainability in turbomachinery and clean-energy applications. Her contributions support industry and national energy goals by improving efficiency, reducing emissions, and enabling data-informed lifecycle management for next-generation power systems.

Shafeeq Ur Rahaman | Data Analytics | Best Researcher Award

Published on 22/08/202522/08/2025 by World Top Scientists

Mr. Shafeeq Ur Rahaman | Data Analytics | Best Researcher Award

Associate Director Analytics at Monks San Francisco, United States

Mr. Shafeeq Ur Rahaman is an accomplished researcher and analytics leader with extensive expertise in data analytics, cloud solutions, and digital transformation. He has a strong record of publishing research in high-impact journals and has ongoing work in areas such as predictive modeling, financial market forecasting, and sustainable supply chain management. His innovative contributions include patents and advanced frameworks that improve operational efficiency and decision-making. Beyond technical expertise, he has demonstrated thought leadership as a keynote speaker and conference presenter, mentoring teams and fostering cross-functional collaboration. Mr. Rahaman has received multiple prestigious awards for innovation and performance, reflecting his commitment to excellence. With a combination of scholarly rigor, practical impact, and leadership in both research and industry, he consistently advances the frontiers of analytics, creating meaningful contributions that influence both academic and professional communities.

Professional Profile

Scopus Profile | ORCID Profile

Education

Mr. Shafeeq Ur Rahaman holds a Master of Science in Management Information Systems, building a strong foundation in both technology and business intelligence. His academic journey began with a Bachelor of Engineering in Electrical and Electronics Engineering, which provided him with rigorous analytical and problem-solving skills. Throughout his education, he complemented his degrees with specialized graduate certificates in Business Intelligence, Business Process Management, and Project Management, demonstrating a commitment to continuous learning and practical application of knowledge. His scholastic achievements were recognized through honors such as Beta Gamma Sigma, highlighting academic excellence. This educational background equips him with a unique blend of technical expertise, strategic insight, and research acumen, enabling him to navigate complex data-driven challenges and drive innovation across multiple domains, including analytics, finance, and supply chain management.

Experience

With over a decade of professional experience, Mr. Rahaman has led analytics and digital transformation initiatives for global enterprises. As an Associate Director in Analytics, he has driven scalable solutions in cloud computing, automation, and advanced data modeling, delivering measurable business impact. His experience spans managing high-budget campaigns, optimizing workflows, and implementing capacity models that enhance team productivity and strategic outcomes. Mr. Rahaman has collaborated with cross-functional teams across finance, marketing, and operations, aligning data strategies with organizational objectives. Beyond industry application, he has demonstrated leadership in mentoring teams, redefining analytics frameworks, and fostering innovation. His professional journey reflects a balance of technical expertise, strategic vision, and leadership, positioning him as an influential figure capable of bridging research insights with real-world business solutions.

Research Focus

Mr. Rahaman’s research focuses on advanced analytics, predictive modeling, econometrics, and machine learning applications in finance, supply chain, and sustainability. His work encompasses forecasting financial market volatility, quantifying uncertainty in economic policies, and applying IoT for sustainable energy management. He explores novel approaches such as CNN-LSTM networks, dynamic neuroplastic models, and non-linear econometric frameworks to address complex decision-making challenges. By integrating data-driven methods with practical applications, his research delivers actionable insights that enhance operational efficiency and strategic planning. He has published numerous research papers in high-impact journals and continues to contribute cutting-edge studies under peer review. His focus on both theoretical rigor and practical relevance positions him as a thought leader capable of advancing knowledge while creating measurable real-world impact.

Award and Honor

Mr. Rahaman has received multiple prestigious awards recognizing his innovation, leadership, and research excellence. His accolades include Gold, Silver, and Platinum awards from global digital and innovation competitions, reflecting outstanding performance in analytics and technological advancement. He has also earned the “On Fire” award twice, highlighting exceptional contribution to team success. Beyond accolades, he holds fellowships and senior memberships in esteemed professional societies such as IEEE, RSA, INNS, and Sigma Xi, affirming his recognition within the global research and engineering community. His patents in AI, machine learning, and business analytics further underscore his originality and impact. Collectively, these honors demonstrate both his academic distinction and industry influence, positioning him as a highly respected figure in the domains of analytics, research, and innovation.

Publication Top Notes

Title: Dynamic Neuroplastic Networks for Financial Decision Making: A Self-Adaptive Approach for Mitigating Catastrophic Forgetting in Continual Learning
Authors: Shafeeq Ur Rahaman
Year: 2025

Title: Quantifying Uncertainty in Economic Policy Predictions: A Bayesian & Monte Carlo Based Data-Driven Approach
Authors: Shafeeq Ur Rahaman, Mahe Jabeen Abdul
Year: 2025

Title: Forecasting Cryptocurrency Markets: Predictive Modelling Using Statistical and Machine Learning Approaches
Authors: Shafeeq Ur Rahaman, Patchipulusu Sudheer, Mahe Jabeen Abdul
Year: 2024

Title: Real-Time Customer Journey Mapping: Combining AI and Big Data for Precision Marketing
Authors: Shafeeq Ur Rahaman
Year: 2024

Title: The Rise of Explainable AI in Data Analytics: Making Complex Models Transparent for Business Insights
Authors: Shafeeq Ur Rahaman
Year: 2024

Title: Real-Time Campaign Optimization: Using Analytics to Adapt Marketing Strategies on the Fly
Authors: Shafeeq Ur Rahaman
Year: 2023

Title: AI-Driven Empathy in UX Design: Enhancing Personalization and User Experience Through Predictive Analytics
Authors: Shafeeq Ur Rahaman
Year: 2023

Title: Precision Healthcare Meets DevOps: Secure Data Science Pipelines for Scalable Machine Learning
Authors: Rishitha Kokku, Shafeeq Ur Rahaman
Year: 2023

Title: An Explainable AI Model in Fintech Risk Management in Small and Medium Companies
Authors: Shafeeq Ur Rahaman
Year: 2023

Title: Explainable AI and Interpretable Machine Learning in Financial Industry Banking
Authors: Shafeeq Ur Rahaman
Year: 2023

Conclusion

Mr. Shafeeq Ur Rahaman exemplifies a rare combination of research excellence, technical expertise, and practical impact. His extensive publication record, spanning high-impact journals and diverse domains such as financial analytics, predictive modeling, AI, and sustainable technologies, reflects both innovation and scholarly rigor. Beyond research, his patents, leadership in conferences, and contributions to industry-scale analytics demonstrate the tangible application of his knowledge to real-world challenges. His mentorship, collaboration across domains, and recognition through prestigious awards and professional fellowships further highlight his influence in both academic and professional communities. Collectively, these accomplishments establish him as a thought leader whose work advances knowledge, drives innovation, and shapes future directions in analytics, AI, and computational research. He is clearly a strong candidate for recognition as a Best Researcher, with a proven track record of impactful contributions and continued potential for transformative work.

Md Minhajul Amin | Business Data Analysis | Best Researcher Award

Published on 13/08/202513/08/2025 by World Top Scientists

Mr. Md Minhajul Amin | Business Data Analysis | Best Researcher Award

Assistant General Manager and Data Analyst at Days Inn & Suites by Wyndham Warren, United States

Md Minhajul Amin is an accomplished researcher and professional with expertise spanning healthcare analytics, artificial intelligence, big data, and digital systems. Holding advanced degrees in information systems and business administration, he combines strong analytical skills with practical experience in data analysis, project management, and operational optimization. His research portfolio includes impactful studies on machine learning for cancer detection, AI in project management, and telemedicine solutions, demonstrating a commitment to solving real-world challenges. Professionally, he has led initiatives to improve efficiency, enhance service quality, and drive community engagement. Recognized through awards, scholarships, and leadership roles, he has shown the ability to integrate academic rigor with practical results. Active in academic and professional communities, his memberships and leadership positions reflect a collaborative and forward-thinking approach. With a continued focus on research specialization and scholarly contributions, he is well-positioned to make significant contributions to his field and beyond.

Professional Profile

Google Scholar

Education

Md Minhajul Amin holds a Master of Science in Information Systems from Central Michigan University, specializing in business data analytics and project management, complemented by a Master of Business Administration and a Bachelor of Business Administration from Premier University, Bangladesh. His education reflects a strong interdisciplinary foundation, blending technical expertise with strategic business insight. Through his academic journey, he has engaged in diverse research and project work, from healthcare system development to marketing analysis, demonstrating the ability to bridge data-driven decision-making with organizational objectives. He has also completed multiple professional training programs in areas such as process mining, supply chain management, robotics process automation, and food safety, enhancing his technical and operational competencies. His academic background is marked by consistent achievement, supported by scholarships and recognition for both academic and extracurricular contributions, positioning him as a well-rounded professional equipped for impactful research and leadership roles.

Experience

Md Minhajul Amin has gained extensive professional experience across data analytics, project management, operations, and leadership roles in both the United States and Bangladesh. As Assistant General Manager and Data Analyst at Monroe Inns Inc., he has implemented data-driven strategies to optimize operations, improve efficiency, and enhance customer satisfaction. His prior role as Senior Executive at Rigel Shipping Services involved managing a large team, overseeing projects for port authorities, and driving operational excellence. At Central Michigan University, he served as a Student Coordinator and Student Assistant, conducting research on community engagement, service optimization, and library accessibility. His roles consistently demonstrate the ability to apply research insights to practical challenges, collaborate across teams, and lead initiatives that produce measurable results. Combining technical knowledge with organizational leadership, he has developed a reputation for innovation, adaptability, and the capacity to deliver high-impact outcomes across diverse sectors.

Research Focus

Md Minhajul Amin’s research centers on applying advanced analytics, artificial intelligence, and data-driven methodologies to address practical challenges in healthcare, project management, and digital systems. His projects have explored machine learning for cancer stage classification, AI-powered project portfolio management, telemedicine accessibility, fraud detection using multivariate analysis, and customer segmentation for personalized marketing. He is particularly interested in the intersection of technology and business strategy, focusing on how big data and AI can enhance decision-making, operational efficiency, and service delivery. His work demonstrates a balance between technical sophistication and applicability, emphasizing solutions that bridge the gap between research theory and real-world implementation. Through interdisciplinary approaches, he aims to contribute to the evolution of data-centric systems that not only improve organizational performance but also generate meaningful social impact, especially in areas like healthcare accessibility and digital transformation in developing regions.

Award and Honor

Md Minhajul Amin has been recognized for his academic excellence, professional contributions, and leadership achievements through multiple awards and honors. He received the Libraries Student Employee Scholarship Award for his dedication and performance at Central Michigan University, along with appreciation from the Mary Ellen Brandell Volunteer Center for his community engagement efforts. Professionally, he earned the Best Employee Performance Award at Rigel Shipping Services for exceptional service and innovation. He is a Lean Six Sigma Green Belt certified professional, demonstrating his expertise in process improvement and operational efficiency. His competitive spirit and problem-solving skills were highlighted when he became champion in the Game of 10 Business Logic competition by Southeast Bank Ltd. His consistent recognition across academic, professional, and extracurricular domains reflects his commitment to excellence, leadership, and impactful contributions, reinforcing his profile as a well-rounded and high-achieving individual in both research and professional settings.

Publications Top Notes

Title: Developing a Project Management Dashboard for Telehealth Implementation
Authors: MM Amin, ZS Munmun, J Atayeva, SW Ahmed, I Shamim, MH Akter
Year: 2025
Citations: 12
Title: Telemedicine and Remote Healthcare: Bridging the Digital Divide
Authors: MNM Sunny, U Sumaiya, MH Akter, F Kabir, ZS Munmun, B Nurani, MM Amin
Year: 2024
Citations: 4
Title: Numerical Analysis of Multivariate Data for Fraud Detection
Authors: MNM Sunny, KMS Hossain, MM Amin, SN Sadmani
Year: 2024
Citations: 3
Title: Classification of Cancer Stages Using Machine Learning on Numerical Biomarker Data
Authors: MNM Sunny, MM Amin, MH Akter, KMS Hossain, A Al Nahian, J Atayeva
Year: 2024
Citations: 3
Title: Ethical Challenges in Business Analytics: Balancing Data Privacy and Profit
Authors: T Hossan, BMT Haque, MS Sakib, N Chowdhury, MM Amin
Year: 2025
Citations: 1
Title: Business Analytics in the Era of Big Data: Driving Informed Decision-Making
Authors: ME Hoque, B Nurani, N Chowdhury, MS Rahaman, MM Amin
Year: 2025
Citations: 1

Conclusion

Md Minhajul Amin’s publication record reflects a strong engagement with emerging and impactful research areas such as telehealth implementation, digital healthcare accessibility, fraud detection, cancer stage classification, business analytics, and ethical considerations in data-driven decision-making. His works demonstrate both technical depth and practical relevance, addressing critical challenges in healthcare, business, and technology. The diversity of topics highlights his interdisciplinary approach and adaptability in applying advanced analytical techniques across multiple domains. While still early in his research career, the growing citation count indicates that his work is gaining recognition within the academic community. With continued focus on high-impact research and strategic dissemination through reputed journals and conferences, he is well-positioned to further enhance his scholarly influence and contribute meaningfully to both academia and industry.

Regent Retrospect Musekwa | Statistics | Best Researcher Award

Published on 08/10/202408/10/2024 by World Top Scientists

Mr. Regent Retrospect Musekwa | Statistics | Best Researcher Award

Research Assistant, Botswana International University of Science and Technology, Botswana

Musekwa Regent is a passionate and skilled statistician currently pursuing a PhD in Statistics at Botswana International University of Science and Technology (BIUST). With a strong foundation in applied statistics, he has excelled in diverse fields such as finance, environmental science, and education, demonstrating a remarkable ability to convert complex data into actionable insights. 📊✨

Publication Profile

Google Scholar

Education

Musekwa holds an MSc in Statistics from BIUST (2023) and a BSc in Statistics from Midlands State University, Zimbabwe (2020). He is currently working towards his PhD, further enhancing his expertise in statistical theory and applications. 🎓📚

Experience

As a Teaching Assistant at BIUST since August 2021, Musekwa has contributed to various courses including Statistics for Non-Mathematicians and Multivariate Analysis. He also serves as an Examination Administrator, ensuring compliance with examination regulations. Previously, he worked as a Statistician at Simbisa Brands, where he optimized operational efficiency and analyzed customer preferences. 👩‍🏫📈

Research Focus

Musekwa’s research primarily revolves around statistical modeling, data analysis, and the development of new statistical distributions. He is particularly interested in applying innovative techniques to real-world problems, contributing to both theoretical and applied statistics. 🔍📖

Awards and Honors

Throughout his academic career, Musekwa has received recognition for his contributions to statistical research. His ongoing PhD research has garnered attention, and he has co-authored several publications in esteemed journals, showcasing his commitment to advancing statistical knowledge. 🏆📜

Publication Top Notes

Musekwa, R. R., & Makubate, B. (2023). Statistical analysis of Saudi Arabia and UK Covid-19 data using a new generalized distribution. Scientific African, 22, e01958. Link
Nyamajiwa, V. Z, Musekwa, R. R., & Makubate, B. (2024). Application of the New Extended Topp-Leone Distribution to Complete and Censored Data. Revista Colombiana de Estadística, 47. Link
Musekwa, R. R., & Makubate, B. (2024). A flexible generalized XLindley distribution with application to engineering. Scientific African, 24, e02192. Link
Musekwa, R. R., Gabaitiri, L., & Makubate, B. (2024). A new technique of creating families of continuous distributions. Revista Colombiana de Estadística. Link
Makubate, B., & Musekwa, R. R. (2024). A novel technique for generating families of distributions. Statistics, Optimization & Information Computing. Link

Shailendra Kumar | Mathematical Modelling | Best Researcher Award

Published on 31/08/202431/08/2024 by World Top Scientists

Mr. Shailendra Kumar | Mathematical Modelling | Best Researcher Award

Assistant Professor, Kutir Post Graduate College Chakkey Jaunpur, India

📘 Shailendra Kumar is an Assistant Professor in the Department of Mathematics at Kutir P. G. College, Chakkey, Jaunpur. With a deep commitment to education and research, Shailendra is currently pursuing his Ph.D. in Mathematics at the University of Allahabad. His academic journey is marked by a strong focus on mathematical modeling, which he applies to address complex environmental issues.

Profile

Google Scholar

Analysis for “Best Researcher Award” – Shailendra Kumar

Strengths for the Award:

Shailendra Kumar has demonstrated a strong academic background in Mathematics, having completed his postgraduate studies and currently pursuing a Ph.D. at a reputable institution, the University of Allahabad. His commitment to research is evident through his position as an Assistant Professor at Kutir Post Graduate College. Notably, he has published a research paper in the “International mper Journal of Modelling and Simulation,” focusing on the effects of energy sectors on carbon dioxide emissions and environmental temperature. This publication, indexed in ESCI, indicates his capability to contribute to his field. His research interest in mathematical modeling aligns with current global concerns about climate change, showcasing his ability to apply mathematical concepts to real-world problems.

Areas for Improvement:

While Shailendra Kumar has a solid academic foundation, his research portfolio could benefit from more diversification and depth. He currently lacks completed or ongoing research projects, consultancy or industry projects, books, patents, and professional memberships, which could enhance his professional profile and impact. Additionally, his publication record is limited to one journal indexed in ESCI, with no SCI or Scopus publications listed. Expanding his research outputs, gaining editorial experience, and collaborating with other researchers or institutions could further strengthen his candidacy for the “Best Researcher Award.”

Education:

🎓 Shailendra Kumar completed his postgraduate studies in Mathematics from the University of Allahabad in 2017. He is presently enrolled as a Ph.D. scholar at the same university, where he continues to expand his expertise and contribute to the field of mathematics.

Experience:

👨‍🏫 As an Assistant Professor at Kutir Post Graduate College, Shailendra Kumar brings his passion for mathematics to the classroom, inspiring students to explore and understand complex mathematical concepts. His role involves not only teaching but also mentoring students in their academic pursuits.

Research Interest:

🔍 Shailendra’s primary area of research is mathematical modeling. His work focuses on developing models that analyze the impacts of various factors, such as energy sectors, on environmental issues like carbon dioxide emissions and climate change. This research is crucial in providing insights into sustainable practices and policies.

Publications:

📝 Shailendra has recently published a research paper titled “Effects of Energy Sectors on the Emission of Carbon Dioxide Gas and Environmental Temperature” in the International Mper Journal of Modelling and Simulation (2024). DOI: 10.1080/02286203.2024.2389010. This work is indexed in ESCI and contributes to the understanding of environmental impacts related to energy production and usage.

Conclusion:

Shailendra Kumar has made commendable strides in his academic and research journey, particularly with his recent publication on environmental issues. However, to be a stronger contender for the “Best Researcher Award,” he would need to expand his research activities and collaborations and build a more robust portfolio of publications and professional contributions. With focused efforts on these areas, he could significantly enhance his research impact and standing in the academic community.