Safaa Najah Saud Al-Humairi | Optimization | Innovative Research Award

Published on by Math Scientist

Innovative Research Award

Safaa Najah Saud Al-Humairi
Management and Science University, Malaysia

Safaa Najah Saud Al-Humairi
Affiliation Management and Science University
Country Malaysia
Scopus ID 55851376600
Documents 135
Citations 1,993
h-index 27
Subject Area Optimization
Event Math Scientist Awards
ORCID 0000-0001-5978-7651

Safaa Najah Saud Al-Humairi is a researcher affiliated with Management and Science University in Malaysia whose documented scholarly profile is associated with optimization and computationally supported engineering research. The available bibliographic record lists 135 documents, 1,993 citations, and an h-index of 27. These indicators provide a quantitative context for considering the researcher for an Innovative Research Award.

Abstract

This academic recognition profile examines the research record of Safaa Najah Saud Al-Humairi in the context of optimization-oriented scientific work. Recent publications address photovoltaic panel modelling, curved photovoltaic structures, Internet of Things-enabled environmental monitoring, artificial intelligence in materials research, and bioactive nanomaterials. Collectively, these works illustrate interdisciplinary applications of modelling, optimization, computation, and engineering design.

Keywords

  • Optimization
  • Photovoltaic Modelling
  • Computational Techniques
  • Artificial Intelligence
  • Sustainable Energy

Introduction

Optimization research frequently connects mathematical or computational methods with practical engineering objectives. In this profile, the documented publication portfolio includes studies that apply modelling and design approaches to renewable-energy systems and emerging computational applications. The researcher’s Scopus record supplies an additional bibliometric basis for evaluating scholarly activity. [1]

Research Profile

The profile is characterized by 135 indexed documents, 1,993 citations, and an h-index of 27, as supplied for this recognition article. The subject-area designation is Optimization. These bibliometric measures should be interpreted as indicators of publication and citation activity rather than as standalone measures of research quality. [1]

Research Contributions

Recent work demonstrates attention to sustainable photovoltaic engineering. One 2026 study investigates modelling and optimization of curved photovoltaic panels for high-efficiency solar-energy conversion. [2] Another examines a floating curved photovoltaic panel combined with IoT-enabled weather monitoring for river and lake environments. [3] Additional contributions extend toward artificial intelligence and advanced computational techniques in shape memory alloy research, alongside biomedical nanomaterial applications. [4] [5]

Publications

  • Modelling and optimisation of curved photovoltaic panels for high-efficiency solar energy conversion — Next Sustainability, 2026. [2]
  • Design of a Floating Curved Photovoltaic Panel with IoT-Enabled Weather Monitoring for Rivers and Lakes Environments — Al-Khwarizmi Engineering Journal, 2026. [3]
  • The Role of AI and Advanced Computational Techniques in Transforming Shape Memory Alloy Research — book chapter, 2026. [4]
  • Bioactive Nanomaterials: Revolutionizing Biomedical Science — book chapter, 2026. [5]

Research Impact

The supplied bibliometric record indicates substantial scholarly visibility, with 1,993 citations and an h-index of 27. The publication themes also connect optimization with renewable energy, environmental monitoring, computational engineering, and biomedical research. Such cross-domain activity may support knowledge transfer between computational methods and applied scientific problems. [1]

Award Suitability

The documented research profile provides relevant evidence for consideration for the Innovative Research Award at the Math Scientist Awards. Its suitability is supported by an established publication and citation record and by recent research addressing optimization, sustainable photovoltaic technologies, IoT monitoring, and advanced computational methods. Final award decisions remain subject to the applicable evaluation criteria and review process.

Conclusion

Safaa Najah Saud Al-Humairi’s research profile combines optimization-oriented scholarship with applied investigations in renewable energy, computational engineering, and emerging scientific technologies. The supplied Scopus indicators and recent publications provide a structured basis for academic recognition and demonstrate a research trajectory relevant to interdisciplinary innovation.

References

  1. Elsevier. (n.d.). Scopus author details: Safaa Najah Saud Al-Humairi, Author ID 55851376600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55851376600
  2. Elsevier. (2026). Modelling and optimisation of curved photovoltaic panels for high-efficiency solar energy conversion. Next Sustainability.
    https://doi.org/10.1016/j.nxsust.2026.100495
  3. Al-Khwarizmi Engineering Journal. (2026). Design of a Floating Curved Photovoltaic Panel with IoT-Enabled Weather Monitoring for Rivers and Lakes Environments.
    https://doi.org/10.22153/kej.2026.03.002
  4. IGI Global. (2026). The Role of AI and Advanced Computational Techniques in Transforming Shape Memory Alloy Research.
    https://doi.org/10.4018/979-8-3373-6127-7.ch006
  5. Springer. (2026). Bioactive Nanomaterials: Revolutionizing Biomedical Science.
    https://doi.org/10.1007/978-981-96-8023-8_5
  6. ORCID. (n.d.). Safaa Najah Saud Al-Humairi, ORCID iD 0000-0001-5978-7651.
    https://orcid.org/0000-0001-5978-7651
  7. Math Scientist Awards. (n.d.). Math Scientist Awards.
    mathscientists.com

Sina Samadi Gharehveran | Optimization | Innovative Research Award

Published on by Math Scientist

Innovative Research Award

Sina Samadi Gharehveran
Tabriz Islamic Art University, Iran

Sina Samadi Gharehveran
Affiliation Tabriz Islamic Art University
Country Iran
Scopus ID 57741285600
Documents 21
Citations 367
h-index 11
Subject Area Optimization
Event Math Scientist Awards
ORCID 0000-0001-5442-2485

Sina Samadi Gharehveran is a researcher affiliated with Tabriz Islamic Art University, Iran, whose documented research profile is associated with optimization and computational approaches to complex engineering and scientific problems. The researcher has 21 indexed documents, 367 citations, and an h-index of 11, providing a measurable basis for academic recognition. The profile is considered in the context of the Math Scientist Awards.

Abstract

Sina Samadi Gharehveran’s research profile reflects scholarly activity in optimization, with applications extending to electric vehicles, adaptive cybersecurity, intelligent agricultural diagnosis, and predictive construction materials research. Available bibliographic indicators document 21 research documents, 367 citations, and an h-index of 11. Recent publications demonstrate the application of multi-objective optimization, reinforcement learning, active vision, and interpretable machine-learning techniques to multidisciplinary problems.

Keywords

  • Optimization
  • Multi-objective optimization
  • Electric vehicles
  • Reinforcement learning
  • Artificial intelligence
  • Predictive modeling

Introduction

Optimization research addresses the systematic selection of solutions under defined objectives and constraints. In contemporary computational research, optimization increasingly intersects with artificial intelligence and machine learning to address complex, data-intensive systems. Gharehveran’s recent publication record illustrates this multidisciplinary orientation, particularly through work involving multi-objective optimization and intelligent computational methods. [1]

Research Profile

The research profile is associated with 21 documents indexed in Scopus, 367 citations, and an h-index of 11. These indicators provide quantitative evidence of research dissemination and citation influence within the indexed scholarly literature. The primary subject area identified for the researcher is Optimization, while the publication portfolio shows applications across engineering, cybersecurity, agriculture, and materials-related computational research. [2]

Research Contributions

A notable research direction concerns the optimization of battery quantity and arrangement in electric vehicles through multi-objective optimization. This work addresses a practical engineering design problem in which competing performance considerations must be evaluated systematically. [3] Other recent work applies graph-aware reinforcement learning to adaptive advanced persistent threat hunting in dynamic enterprise networks, demonstrating the relevance of intelligent optimization strategies to cybersecurity environments. [4]

Publications

  • Optimization of the Number of Batteries and their Arrangement in Electric Vehicles Based on Multi-Objective Optimization. Passive Defense, 2026. [3]
  • Graph-Aware Reinforcement Learning for Adaptive APT Threat Hunting in Dynamic Enterprise Networks. Technologies, 2026. [4]
  • RAVA: a robust recurrent active vision agent for plant disease diagnosis under severe environmental noise. Scientific Reports, 2026. [5]
  • Interpretable Prediction of Geopolymer Concrete Compressive Strength Using DBO–CatBoost and SHAP Analysis. Buildings, 2026. [6]

Research Impact

The combination of 367 citations and an h-index of 11 indicates an established level of scholarly visibility within indexed literature. The range of application domains represented in the recent publications also suggests a research approach that connects optimization with practical computational problems. Citation indicators should, however, be interpreted alongside publication quality, disciplinary norms, collaboration patterns, and the characteristics of individual research fields. [2]

Award Suitability

The available profile provides a reasonable scholarly basis for consideration for an Innovative Research Award. The evidence includes measurable citation impact, an established h-index, and recent research addressing optimization and intelligent computational methods in several application areas. The award assessment should consider the complete publication record and applicable evaluation criteria in addition to bibliometric indicators. [1]

Conclusion

Sina Samadi Gharehveran’s documented research profile combines optimization-focused scholarship with interdisciplinary applications involving electric vehicles, cybersecurity, plant disease diagnosis, and predictive materials research. With 21 documents, 367 citations, and an h-index of 11, the profile demonstrates measurable academic impact. Recent publications further indicate engagement with contemporary computational methods, supporting consideration for recognition through the Innovative Research Award.

References

  1. Elsevier. (n.d.). Scopus author details: Sina Samadi Gharehveran, Author ID 57741285600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57741285600
  2. Scopus. (n.d.). Author metrics and indexed publication record: Sina Samadi Gharehveran. Elsevier.
  3. Passive Defense. (2026). Optimization of the Number of Batteries and their Arrangement in Electric Vehicles Based on Multi-Objective Optimization.
    https://doi.org/10.47176/pd.2026.1490
  4. MDPI. (2026). Graph-Aware Reinforcement Learning for Adaptive APT Threat Hunting in Dynamic Enterprise Networks. Technologies.
    https://doi.org/10.3390/technologies14100624
  5. Nature Portfolio. (2026). RAVA: a robust recurrent active vision agent for plant disease diagnosis under severe environmental noise. Scientific Reports.
    https://doi.org/10.1038/s41598-026-67160-2
  6. MDPI. (2026). Interpretable Prediction of Geopolymer Concrete Compressive Strength Using DBO–CatBoost and SHAP Analysis. Buildings.
    https://doi.org/10.3390/buildings16163326

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

Saeed Farsad | Optimization | Excellence in Research

Published on by Math Scientist

Dr. Saeed Farsad | Optimization | Excellence in Research

Assistant Professor at Birjand University of Technology, Iran

Dr. Saeed Farsad is an accomplished researcher and academic with expertise in experimental fluid dynamics, renewable energy, and heat transfer. He holds a Ph.D. in Mechanical Engineering from the Iranian Research Organization for Science and Technology (IROST) and has extensive experience in wind/water tunnel testing, aerodynamics, and energy conversion systems. Currently serving as an Assistant Professor at Birjand University of Technology (BUT), he has published numerous high-impact journal articles in Q1 and Q2-ranked journals, focusing on vortex shedding, energy storage, and thermo-fluidic properties. His research contributions extend beyond academia, including patents, award papers, and a book on solar desalination. With international collaborations at Toronto Metropolitan University and York University, Dr. Farsad has strengthened his global research footprint. Recognized as an Elective Researcher of the Province, his work has significant industrial and academic applications, making him a prominent figure in mechanical and applied engineering sciences.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

Education

Dr. Saeed Farsad holds a Ph.D. in Mechanical Engineering from the Iranian Research Organization for Science and Technology (IROST), specializing in experimental fluid dynamics, wind/water tunnel tests, and advanced measurement techniques. He completed his M.Sc. in Mechanical Engineering – Energy Conversion at the University of Sistan & Baluchestan, where he focused on solar desalination, heat transfer, and numerical simulations. His B.Sc. in Automotive Technology from the Technical College of Mashhad provided a strong foundation in vehicle systems, transmission lines, and automotive engineering. His academic journey showcases a deep multidisciplinary approach, integrating energy systems, experimental fluid mechanics, and automotive applications. With supervisors from renowned institutions, his education has been instrumental in shaping his expertise in thermo-fluid sciences and renewable energy applications. His ability to blend theoretical knowledge with practical applications has led to impactful research contributions, journal publications, and patented innovations in mechanical and automotive engineering.

Professional Experience

Dr. Saeed Farsad has over a decade of professional experience, combining academic research, teaching, and industry involvement. He is currently an Assistant Professor at Birjand University of Technology (BUT), where he teaches courses in fluid mechanics, statics, technical drawing (CATIA), and automotive technology. His international exposure includes a Visiting Assistant Professorship at Toronto Metropolitan University (TMU) and a Research Assistant position at York University, where he contributed to energy storage and fluid mechanics research. Beyond academia, Dr. Farsad has worked in the automotive industry, including roles at Toyota Motor Manufacturing Canada (TMMC) and Mechatronic Diagnostic Inc., where he gained hands-on experience in diagnostics and assembly line operations. His expertise spans experimental fluid flow measurement, energy systems, and mechanical design, making him a versatile researcher and educator with a unique blend of theoretical and applied engineering knowledge.

Research Interest

Dr. Saeed Farsad’s research interests lie in experimental fluid dynamics, renewable energy, and heat transfer. His work focuses on vortex shedding, aerodynamics, and thermo-fluidic properties, with applications in wind and water tunnel experiments. He has also made significant contributions to solar desalination, adsorption-based energy storage, and magnetic nanofluid heat transfer. His interdisciplinary research integrates advanced experimental techniques such as Particle Image Velocimetry (PIV), Laser Doppler Velocimetry (LDV), and Hot-Wire Anemometry (HWA) to enhance the understanding of fluid flow and heat exchange mechanisms. In addition, Dr. Farsad explores automotive aerodynamics, energy-efficient HVAC systems, and turbulence modeling, bridging the gap between engineering applications and sustainable energy solutions. His collaborations with international researchers in Canada and Iran further strengthen his impact in the global scientific community, ensuring that his research contributes to both theoretical advancements and industrial applications.

Awards and Honors

Dr. Saeed Farsad has received several awards and recognitions for his contributions to mechanical engineering and applied sciences. He was honored as the Elective Researcher of the Province in 2011, recognizing his pioneering research in fluid mechanics and energy systems. His academic excellence is reflected in his third-place ranking in Associate Graduate Courses at Mashhad Technical College and his 16th rank among 6,000 applicants in the B.Sc. Automotive Mechanics Entrance Exam. His innovative research has led to multiple patents, including a Smart Filter equipped with an alarm system and a device for the collection and separation of machine tool waste. With publications in high-impact journals and invitations to prestigious international awards, Dr. Farsad’s achievements highlight his significant contributions to engineering innovation and scientific advancements.

Conclusion

Dr. Saeed Farsad is a highly accomplished researcher, educator, and engineer with expertise in experimental fluid dynamics, renewable energy, and heat transfer. His strong academic background, diverse professional experience, and impactful research contributions make him a leading figure in mechanical engineering. His ability to integrate theoretical research with practical applications has resulted in high-impact journal publications, patents, and industrial collaborations. His work in aerodynamics, solar desalination, and energy storage has broad implications for sustainable engineering and environmental solutions. With international research experience and teaching roles in Canada and Iran, Dr. Farsad has established himself as a global expert in his field. His dedication to scientific excellence and innovation positions him as a strong candidate for prestigious research awards, reinforcing his influence in the engineering and academic communities worldwide.

Publications Top Noted