Fuat Türk | Optimization | Best Researcher Award

Published on by Math Scientist

Assist. Prof. Dr. Fuat Türk | Optimization | Best Researcher Award

Researcher| Gazi University | Turkey

Assist. Prof. Dr. Fuat Türk is a researcher in artificial intelligence, medical image analysis, and machine learning, currently affiliated with Gazi University, Turkey. His research focuses on developing intelligent diagnostic and segmentation models for healthcare applications, including kidney and renal tumor detection, lung opacity analysis, heart disease prediction, and cancer diagnosis. He has contributed to advancing hybrid deep-learning architectures, CNN-based image fusion models, machine learning–driven feature selection, and optimization techniques for clinical decision support systems. Dr. Türk’s work integrates computational modeling with real-world medical datasets, aiming to improve diagnostic accuracy, automate radiological workflows, and support early disease detection. His published works demonstrate a strong interdisciplinary approach bridging mathematics, computer vision, and biomedical engineering, and his studies have been cited widely in the fields of medical imaging and machine learning.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

  1. Türk, F., Lüy, M., & Barışçı, N. (2020). Kidney and renal tumor segmentation using a hybrid V-Net-based model. Mathematics, 8(10), 1772. Citations: 98

  2. Türk, F. (2023). Analysis of intrusion detection systems in UNSW-NB15 and NSL-KDD datasets with machine learning algorithms. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 12(2), 465–477. Citations: 59

  3. Türk, F., & Kökver, Y. (2023). Detection of lung opacity and treatment planning with three-channel fusion CNN model. Arabian Journal for Science and Engineering, 49, 2973–2985. Citations: 17

  4. Türk, F. (2024). Investigation of machine learning algorithms on heart disease through dominant feature detection and feature selection. Signal, Image and Video Processing. Citations: 15

  5. Akkur, O. E. E., & Türk, F. (2022). Breast cancer diagnosis using feature selection approaches and Bayesian optimization. Computer Systems Science and Engineering, 45(2), 1017–1031. Citations: 13

Oluwaseun Akinte | Optimization | Best Researcher Award

Published on by Math Scientist

Dr. Oluwaseun Akinte | Optimization | Best Researcher Award

Oluwaseun Akinte | Rajamangala University of Technology Thanyaburi | Thailand

Dr. Oluwaseun Olanrewaju Akinte is a Postdoctoral Researcher in Energy and Materials Engineering at Rajamangala University of Technology Thanyaburi, specializing in renewable energy systems, hybrid microgrids, and advanced storage technologies. He earned his Ph.D. in Energy and Materials Engineering from Rajamangala University of Technology Thanyaburi, an M.Sc. in Electrical and Electronic Engineering from Coventry University, United Kingdom, and a B.Sc. in Electrical and Electronic Engineering from Olabisi Onabanjo University, Nigeria. His professional journey spans academia and industry, including roles as Research Assistant at RMUTT, Academic Tutor in Nigeria, Project/Site Engineer with Electromechanical Integrators Inc., and voluntary postgraduate lecturer at the University of the People, USA. His research contributions focus on energy storage optimization, hybrid renewable energy networks, and techno-econometric analysis of integrated microgrids, producing impactful publications in high-ranking journals such as IEEE Access, Energies, Sustainability, and Franklin Open, alongside international conference presentations. Dr. Akinte has co-authored over 16 journal and conference papers with 18 citations across 18 documents, reflecting his growing scholarly influence. His leadership extends to collaborative projects with industrial partners, addressing energy efficiency and sustainability challenges, while his invited talks at international congresses highlight his recognition in the global research community. He has been honored with the E-CUBE-I RMUTT Scholarship and the Best Oral Presentation Award at the Energy Society and Sustainability Conference. In addition, he is an active member of the International Association of Engineers (IAENG), contributing to knowledge exchange in the field of electrical and energy engineering. With strong expertise in power system modeling, microgrid optimization, and renewable integration, Dr. Akinte continues to advance innovative energy solutions with global impact. Citations: 18, Documents: 5, h-index: 2.

Profiles: Google Scholar | Scopus | ORCID

Featured Publications

1. Akinte O.O.*, Plangklang B., Prasartkaew B., Aina T.S., Energy storage management of a solar photovoltaic–biomass hybrid power system. Energies, 2023, 16(13), 5122.

2. Aina T.S.*, Akinte O.O., Awelewa A.J., Adelakun D.O., Critical evaluation of waterfall project management methodology: A case study of digital management conference project. Int. J. Adv. Multidiscip. Res. Stud., 2022, 2, 1–10.

3. Akinte O.O.*, Aina T.S., HVAC vs HVDC power system: Contemporary development in HVAC and HVDC power transmission system. Int. J. Sci. Technol. Res., 2021, 19, 252–261.

4. Aina T.S.*, Akinte O.O., Iyaomolere B.A., Investigation on performance of microstrip patch antenna for a practical wireless local area network (WLAN) application. Int. J. Res. Appl. Sci. Eng. Technol. (IJRASET), 2022, 10, 221–226.

5. Aina T.S.*, Akinte O.O., Iyaomolere B., Tosin A.E., Abode I.I., Awelewa A.J., Implementation of an intelligent motion detector. Int. Res. J. Eng. Technol. (IRJET), 2022, 9(1), 1148–1165.

Faïçal Ndaïrou | Optimization | Best Researcher Award

Published on by Math Scientist

Dr. Faïçal Ndaïrou | Optimization | Best Researcher Award

Researcher at University of Aveiro | Portugal

Dr. Faïcal Ndaïrou is an accomplished researcher in applied mathematics, fractional calculus, and mathematical epidemiology, recognized for his expertise in optimization theory and infectious disease modeling, with a career that reflects both academic excellence and international research impact. He began his higher education at the African Institute for Mathematical Sciences (AIMS) in Cameroon, where he earned a Master’s in Mathematical Sciences in 2015 with Distinction, focusing on mathematical epidemiology, computational science, and bioinformatics. He went on to complete two doctoral programs that highlight his interdisciplinary strengths: in 2020, he earned a Ph.D. in Water Sustainability and Development from the University of Vigo, Spain, with Outstanding Cum Laude honors, focusing on mathematical modeling of water-related infectious diseases, and in 2022, he completed a Ph.D. in Applied Mathematics at the Universities of Aveiro, Porto, and Minho, Portugal, with Distinction, specializing in optimization subject to fractional dynamics with applications to disease modeling. Professionally, Dr. Ndaïrou has contributed as a researcher at the Center for Research and Development in Mathematics and Applications (CIDMA), Portugal, and more recently as a postdoctoral researcher at the Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, supported by the prestigious PIKOM fellowship. His research interests lie in fractional calculus, optimization, computational mathematics, and epidemiological modeling, and his skills include proficiency in Python, R, Matlab, Julia, Maple, Sage, and LaTeX. He has published in leading journals such as Applied Mathematics and Computation, Chaos, Solitons & Fractals, and Mathematics, while serving as Guest Editor and on editorial boards for MDPI Mathematics and Frontiers in Applied Mathematics and Statistics. A recipient of highly competitive scholarships from FCT Portugal, the Bulgarian Ministry of Education, and AIMS Cameroon, Dr. Ndaïrou continues to build a reputation as a rising leader whose research bridges theoretical innovation with urgent societal challenges in health and sustainability.

Profiles: Scopus | Google Scholar | ORCID

Publications

1. Ndaïrou, F., Area, I., Nieto, J. J., & Torres, D. F. M. (2020). Mathematical modeling of COVID-19 transmission dnamics with a case study of Wuhan. Chaos, Solitons & Fractals, 135, 109846. Citations: 885

2. Ndaïrou, F., Area, I., Nieto, J. J., Silva, C. J., & Torres, D. F. M. (2021). Fractional model of COVID-19 applied to Galicia, Spain and Portugal. Chaos, Solitons & Fractals, 144, 110652. Citations: 106

3. Area, I., Ndairou, F., Nieto, J. J., Silva, C. J., & Torres, D. F. M. (2017). Ebola model and optimal control with vaccination constraints. arXiv preprint arXiv:1703.01368. Citations: 102

4. Ndaïrou, F., Area, I., Nieto, J. J., Silva, C. J., & Torres, D. F. M. (2018). Mathematical modeling of Zika disease in pregnant women and newborns with microcephaly in Brazil. Mathematical Methods in the Applied Sciences, 41(18), 8929–8941. Citations: 63

5. Area, I., Losada, J., Ndairou, F., Nieto, J. J., & Tcheutia, D. D. (2017). Mathematical modeling of 2014 Ebola outbreak. Mathematical Methods in the Applied Sciences, 40(17), 6114–6122. Citations: 40

Seyed Mehdi Tavakkoli | Optimization | Best Researcher Award

Published on by Math Scientist

Assoc. Prof. Dr. Seyed Mehdi Tavakkoli | Optimization | Best Researcher Award

Associate Professor at Shahrood University of Technology, Iran

Dr. Seyed Mehdi Tavakkoli is a distinguished scholar in structural and computational engineering 🏗️📊, serving as Associate Professor at Shahrood University of Technology, Iran. With a Ph.D. in Civil Engineering – Structures from Iran University of Science & Technology 🎓, he has pioneered research in isogeometric analysis, structural topology optimization, and continuum mechanics. His prolific academic career includes over 30 peer-reviewed journal publications 📝, mentorship of MSc and Ph.D. students, and international collaboration at the University of Bath, UK 🌍. Dr. Tavakkoli is highly skilled in MATLAB, Python, and leading structural software tools 💻, blending theory with practical applications. His innovative contributions to damage detection, shape optimization, and smart materials position him as a leading voice in modern civil engineering 🔍🏅. He is deeply committed to advancing research, education, and global knowledge exchange.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

🎓 Education

Dr. Seyed Mehdi Tavakkoli holds a Ph.D. in Civil Engineering – Structures from Iran University of Science & Technology 🎓, where he specialized in isogeometric analysis and topology optimization using NURBS basis functions. Guided by renowned experts like Prof. Behrooz Hassani and Prof. Ali Kaveh, his dissertation laid the foundation for integrating computational geometry with structural optimization. His education blends strong mathematical rigor, numerical methods, and engineering design 🧠📐. Earlier degrees were equally grounded in high academic achievement, with a consistent focus on advanced mechanics and structural systems. His academic journey demonstrates a fusion of innovation and precision, making him an expert in structural modeling, finite elements, and smart structural systems. Dr. Tavakkoli’s education has positioned him as a forward-thinking engineer capable of solving complex multi-scale problems 🏗️🔍.

📊Professional Experience

Dr. Tavakkoli has over 15 years of academic and international research experience. He currently serves as an Associate Professor in the Civil Engineering Department at Shahrood University of Technology 🏛️, where he teaches undergraduate and postgraduate courses in structural analysis, finite element methods, and optimization. From 2013–2014, he worked as a Research Associate at the University of Bath, UK 🇬🇧, where he developed nonlinear models of piezoelectric-bistable laminates for energy harvesting. His teaching record is distinguished by the design of curricula focused on mechanics, computational methods, and structural systems. He has supervised numerous MSc and PhD theses, bringing theoretical insight into practical applications 📘👨‍🔧. His professional journey reflects a balanced commitment to academic excellence, innovation, and global collaboration 🌍📊.

🔬 Research Interests

Dr. Tavakkoli’s research lies at the intersection of computational mechanics, structural optimization, and smart materials. He specializes in isogeometric analysis, finite element modeling, and topology optimization of structures, particularly for energy-efficient and damage-tolerant design systems 🧮⚙️. His recent studies include multiscale modeling, couple stress theory, level-set methods, and elastoplastic material behavior in structural systems. He has also contributed to damage detection using time-domain responses and modal expansion methods. His work is regularly published in high-impact journals like Engineering with Computers, Computer-Aided Design, and Finite Elements in Analysis and Design 📑📈. Passionate about integrating theory and real-world solutions, his research advances fields such as additive manufacturing, structural health monitoring, and sustainable civil engineering systems 🌱🏗️.

🏅 Awards and Honors

Dr. Tavakkoli’s sustained contributions to civil and structural engineering have earned him recognition as a prolific researcher in computational design and optimization. While formal award titles are not explicitly listed, his continuous publication in top-tier international journals and collaborations with leading institutions, including the University of Bath, reflect his scholarly impact 🏆🌍. His research papers—cited widely in structural optimization and computational mechanics—have influenced both academia and industry. His role as a supervisor and project leader in complex optimization frameworks also underlines his academic leadership. The innovative nature of his work in isogeometric topology optimization is gaining increasing recognition across structural engineering circles, positioning him as a thought leader in the evolving landscape of smart and sustainable design systems 🧠🛠️.

🛠️ Research Skills

Dr. Tavakkoli possesses deep expertise in structural modeling, numerical methods, and advanced optimization techniques. He is proficient in programming languages such as MATLAB, Python, Visual Fortran, and Visual Basic 👨‍💻. His computational skillset includes structural analysis software like ETABS, SAP2000, and SAFE, alongside core platforms like AutoCAD and MS Office. His research utilizes isogeometric and finite element methods, multiscale modeling, and optimization algorithms including ant colony and level-set techniques 🔄📊. His capabilities also extend to damage detection and nonlinear modeling of smart materials. This combination of practical software fluency and high-level theoretical modeling makes him highly adaptable for modern engineering challenges—especially in the development of smart, safe, and efficient structural systems ⚡🏗️.

📝Publications Top Note

  • Title: Structural topology optimization using ant colony methodology
    Authors: A. Kaveh, B. Hassani, S. Shojaee, S.M. Tavakkoli
    Year: 2008
    Citations: 210
    Source: Engineering Structures, 30(9), 2559–2565

  • Title: An isogeometrical approach to structural topology optimization by optimality criteria
    Authors: B. Hassani, M. Khanzadi, S.M. Tavakkoli
    Year: 2012
    Citations: 169
    Source: Structural and Multidisciplinary Optimization, 45(2), 223–233

  • Title: Simultaneous shape and topology optimization of shell structures
    Authors: B. Hassani, S.M. Tavakkoli, H. Ghasemnejad
    Year: 2013
    Citations: 100
    Source: Structural and Multidisciplinary Optimization, 48(1), 221–233

  • Title: An isogeometrical approach to structural level set topology optimization
    Authors: H.A. Jahangiri, S.M. Tavakkoli
    Year: 2017
    Citations: 88
    Source: Computer Methods in Applied Mechanics and Engineering, 319, 240–257

  • Title: Application of isogeometric analysis in structural shape optimization
    Authors: B. Hassani, S.M. Tavakkoli, N.Z. Moghadam
    Year: 2011
    Citations: 74
    Source: Iranian Science, 18(4), 846–852

  • Title: An isogeometrical approach to error estimation and stress recovery
    Authors: B. Hassani, A. Ganjali, M. Tavakkoli
    Year: 2012
    Citations: 37
    Source: European Journal of Mechanics A: Solids, 31(1), 101–109

  • Title: Isogeometric shape optimization of three dimensional problems
    Authors: B. Hassani, M. Khanzadi, S.M. Tavakkoli, N.Z. Moghadam
    Year: 2009
    Citations: 33
    Source: 8th World Congress on Structural and Multidisciplinary Optimization, 1–5

  • Title: Isogeometric topology optimization of structures by using MMA
    Authors: S.M. Tavakkoli, B. Hassani, H. Ghasemnejad
    Year: 2013
    Citations: 27
    Source: International Journal of Optimization in Civil Engineering, 3(2), 313–326

  • Title: Free vibration of functionally graded thick circular plates: An exact and three-dimensional solution
    Authors: M.Z. Roshanbakhsh, S.M. Tavakkoli, B.N. Neya
    Year: 2020
    Citations: 25
    Source: International Journal of Mechanical Sciences, 188, 105967

  • Title: Structural damage detection in plane stress problems by using time domain responses and topology optimization
    Authors: F. Damghani, S.M. Tavakkoli
    Year: 2023
    Citations: 2
    Source: International Journal of Optimization in Civil Engineering (IJOCE), 13(2)

  • Title: An analytical study on piezoelectric-bistable laminates with arbitrary shapes for energy harvesting
    Authors: S.M. Tavakkoli, P.M. Weaver, C.R. Bowen, D.J. Inman, H. Alicia
    Year: 2015
    Citations: 2
    Source: [Not specified, likely conference proceedings or journal]

  • Title: Topology optimization of space structures using ant colony method
    Authors: S.M. Tavakkoli, L. Shahryari, A. Parsa
    Year: 2013
    Citations: 2
    Source: International Journal of Optimization in Civil Engineering, 3(3), 359–370

  • Title: Channels flow modeling by using isogeometric analysis
    Authors: R. Amini, R. Maghsoodi, N.Z. Moghaddam, S.M. Tavakkoli
    Year: 2016
    Citations: 1
    Source: Journal of Solid and Fluid Mechanics, 5(4)

  • Title: Size-dependent topology optimization for eigenfrequency maximization of microplates using consistent couple stress theory
    Authors: M.Z. Roshanbakhsh, S.M. Tavakkoli
    Year: 2025
    Source: Advances in Engineering Software, 206, 103941

🧾 Conclusion

Dr. Seyed Mehdi Tavakkoli exemplifies a rare blend of academic depth, technical precision, and forward-thinking research in structural engineering. With over three decades of cumulative experience across teaching, research, and international collaboration, he has become a key contributor to the evolving landscape of computational civil engineering 📘🌐. His isogeometric approach, grounded in rigorous mathematics and real-world applications, continues to influence emerging scholars and professionals alike. Whether through supervising doctoral candidates, publishing high-impact research, or exploring optimization in additive manufacturing, his work consistently pushes the boundary of what’s possible in engineering design. Dr. Tavakkoli stands out not only as a researcher but as a mentor, innovator, and thought leader of 21st-century structural systems 🏅🚀.

Zohaib Khan | Optimization | Best Researcher Award

Published on by Math Scientist

Dr. Zohaib Khan | Optimization | Best Researcher Award

Jiangsu University, China

Zohaib Khan is a dedicated researcher specializing in machine learning, object detection, and control science engineering, with a strong focus on precision agriculture and AI-driven automation. Currently pursuing a PhD at Jiangsu University, China, he has made significant contributions to deep learning-based agricultural robotics, publishing multiple first-author papers in high-impact SCI Q1, Q2, and EI journals. His work emphasizes real-time detection, optimization algorithms, and AI-driven sustainability solutions. With extensive mentoring experience (50+ Bachelor’s and 10 Master’s students), he has played a key role in academic development. Zohaib has received numerous national and international awards, including first prizes in elite research and innovation competitions. His technical expertise spans Python, MATLAB, LaTeX, and AI-driven modeling, complementing his ability to lead interdisciplinary research. With a passion for advancing AI applications in agriculture, he continues to drive innovation in sustainable and automated farming solutions.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

Education

Zohaib Khan is currently pursuing a PhD in Control Science Engineering at Jiangsu University, China (2022–2026), specializing in machine learning and object detection. He previously earned an MSc in Electrical Engineering (2019–2022) from the same institution, focusing on power systems and renewable energy. His Bachelor’s degree in Electrical Power Engineering (2013–2017) from Swedish College of Engineering and Technology, Pakistan, laid the foundation for his technical expertise. His early academic years were marked by excellence, having completed Pre-Engineering at Fazaia Degree College (2011–2013) and his Secondary School Certificate (2009–2011) at Agricultural University Public School. Zohaib’s academic journey is distinguished by his strong analytical skills and passion for integrating AI and automation in engineering solutions. His education reflects a deep commitment to advanced research, innovation, and interdisciplinary problem-solving, positioning him as a future leader in AI-driven technologies and precision agriculture.

Professional Experience

Zohaib Khan has gained substantial experience in both academic research and engineering practice. As an intern at WAPDA, Pakistan, he developed hands-on expertise in power distribution and transmission lines, strengthening his understanding of grid operations and maintenance. Later, as an Electrical Engineer at LIMAK (JV) ZKB – CPEC Project (2017–2018), he contributed to electrical system design, installation, and maintenance, gaining valuable project management experience. His role involved troubleshooting, safety compliance, and interdisciplinary collaboration, enhancing his problem-solving capabilities. In academia, Zohaib has mentored over 50 Bachelor’s and 10 Master’s students, guiding them through research projects in machine learning, object detection, and automation. His strong writing, teaching, and IT skills have been instrumental in fostering innovation. His diverse experience, spanning applied research and engineering implementation, makes him a well-rounded professional capable of driving breakthroughs in AI-powered automation and precision agriculture.

Research Interest

Zohaib Khan’s research focuses on machine learning, deep learning, object detection, and AI-driven automation, with applications in precision agriculture and robotics. His studies revolve around real-time detection, optimization algorithms, and advanced control systems for agricultural sustainability and industrial automation. He has pioneered AI-driven precision farming techniques, developing deep learning-enhanced YOLOv7 and YOLOv8 algorithms for real-time crop health assessment and robotic spraying systems. Additionally, his work explores autonomous navigation in unstructured farmlands, energy-efficient control systems, and reinforcement learning for AI-based decision-making. His research extends to risk assessment in renewable energy systems, contributing to more efficient and resilient smart grids. Through interdisciplinary collaborations, Zohaib continues to push the boundaries of AI in sustainable agriculture, robotics, and industrial automation, aiming to develop intelligent, scalable, and high-impact solutions for modern technological challenges.

Awards and Honors

Zohaib Khan has received multiple prestigious awards recognizing his contributions to research, innovation, and academic excellence. He has won First Prizes in National Competitions, including the China University Business Elite Challenge (2024) and the Brand Planning Competition (2024). His research excellence was acknowledged with the Excellent Paper Award at the Sino-award (2021) and special recognition in Jiangsu Province Graduate Energy-saving and Low-Carbon Research Competition (2023). Additionally, he was honored as an Outstanding Student in the 17th “Yale School of Jiangsu University” program and received a Certificate of Excellence for Teaching Assistance. His leadership and public speaking skills earned him first place in an English debate at Jiangsu University. These accolades reflect his dedication to research, leadership in innovation, and commitment to advancing AI applications in engineering and agriculture, solidifying his reputation as a promising researcher in his field.

Conclusion

Zohaib Khan’s academic, professional, and research journey showcases his exceptional talent in AI-driven automation, machine learning, and precision agriculture. His extensive experience in research, mentoring, and engineering practice positions him as a leading scholar in intelligent agricultural robotics and sustainable AI applications. With a strong publication record in high-impact journals (SCI Q1, Q2, and EI) and multiple national and international awards, he has demonstrated his ability to drive innovation and solve real-world problems. His work in deep learning-based automation and AI-driven optimization techniques continues to push the boundaries of technology for sustainability and efficiency. As he progresses in his career, Zohaib remains committed to advancing cutting-edge research, fostering academic collaborations, and contributing transformative solutions in AI, robotics, and smart energy systems. His dedication and achievements make him a strong candidate for prestigious research awards and a key contributor to the future of AI in engineering and agriculture.

Publications Top Noted