Priya A. K. | Environmental and Sustainable Materials | Women Researcher Award

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Women Researcher Award

Priya A. K.
Karunya Institute of Technology and Sciences, India.

Priya A. K.
Affiliation Karunya Institute of Technology and Sciences
Country India
Scopus ID 57226315795
Documents 127
Citations 6,572
h-index 43
Subject Area Environmental and Sustainable Materials
Event International Soil Scientist Awards
ORCID 0000-0002-0190-9828

Priya A. K. is an Indian researcher affiliated with the Karunya Institute of Technology and Sciences, whose work centres on environmental and sustainable materials [1]. She is presented here in connection with the Women Researcher Award at the International Soil Scientist Awards.

Abstract

This article summarises the research profile of Priya A. K., whose publications address biofuels, water treatment, nanomaterials, environmental monitoring and flood prediction. Bibliometric indicators from Scopus show a substantial and sustained publication record [1]. Recent journal articles demonstrate a consistent focus on sustainable solutions to environmental challenges.

Keywords

Environmental materials, sustainable materials, biodiesel, bioadsorbent, iron oxide nanoparticles, water pollution, flood prediction, remote sensing.

Introduction

Environmental and sustainable materials research seeks to reduce pollution, improve resource efficiency and develop cleaner energy options. Priya A. K. contributes to this field from the Karunya Institute of Technology and Sciences in India, with an ORCID record that lists her published works [2]. Her work spans experimental, analytical and computational approaches.

Research Profile

According to Scopus, the researcher has authored 127 documents with 6,572 citations and an h-index of 43 [1]. Her subject area is environmental and sustainable materials. Her recent output appears in journals concerned with fuels, water technology, nanoscience, forensics and computational engineering.

Research Contributions

  • Fuel characterisation: A comparative study examined the physico-chemical characteristics of conventional diesel, e-diesel, biodiesel and aged biodiesel [3].
  • Water remediation: Yellow bluestem biomass was valorised into a bioadsorbent for removing rhodamine B from water [4].
  • Nanomaterials: Work on sustainable production of iron oxide nanoparticles addresses healthcare applications and the cleanup of contaminated regions [5].
  • Environmental monitoring: A study of seasonal surface water pollution in semi-urban Telangana applied PCA, factor analysis and UMAP, and a review examined remote sensing and artificial intelligence for flood prediction.

Publications

  • “An in-depth comparative analysis of fuel evolution…”, Biofuels, 2026 [3].
  • “Sustainable valorization of yellow bluestem biomass…”, Water Practice & Technology, 2026 [4].
  • “Sustainable Production of Iron Oxide Nanoparticles…”, International Journal of Nanoscience, 2026 [5].
  • “Remote Sensing and Artificial Intelligence in Flood Prediction…”, Archives of Computational Methods in Engineering, 2026.
  • “Seasonal Dynamics of Surface Water Pollution in Semi-Urban Telangana…”, Environmental Forensics, 2026.

Research Impact

The citation count of 6,572 and an h-index of 43 indicate that her work has been widely read and referenced within the scholarly community [1]. Her research connects materials science with practical needs such as cleaner water, alternative fuels and environmental risk assessment, and the breadth of journals in which she publishes reflects this interdisciplinary reach.

Award Suitability

The Women Researcher Award at the International Soil Scientist Awards recognises women who have contributed meaningfully to their fields. Priya A. K. is considered suitable on the basis of her sustained publication record, citation performance and focus on sustainability-oriented problems, including contaminated environments and water quality [1][4].

Conclusion

Priya A. K. has built a substantial body of work in environmental and sustainable materials, supported by strong bibliometric indicators and recent publications across several journals. Her research contributes to practical approaches for pollution control, cleaner fuels and nanomaterial applications.

References

  1. Elsevier. (n.d.). Scopus author details: Priya, A. K., Author ID 57226315795. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57226315795
  2. ORCID. (n.d.). Priya Arunkumar (ORCID iD 0000-0002-0190-9828). ORCID.
    https://orcid.org/0000-0002-0190-9828
  3. An in-depth comparative analysis of fuel evolution: Tracking physico-chemical characteristics in conventional diesel, e-diesel, biodiesel, and aged biodiesel. (2026). Biofuels. DOI: 10.1080/17597269.2025.2578575
    https://doi.org/10.1080/17597269.2025.2578575
  4. Hosamane, S. N., Patil, C., Sahana, S., Priya, A. K., & La, D. D. (2026). Sustainable valorization of yellow bluestem biomass into high-performance bioadsorbent for rhodamine B sequestration from water. Water Practice & Technology.
    https://doi.org/10.2166/wpt.2026.539
  5. Priya, A. K., & La, D. (2026). Sustainable production of iron oxide nanoparticles for application in healthcare and cleanup of contaminated regions. International Journal of Nanoscience.
    https://doi.org/10.1142/S0219581X26300099

Javad Momeni Damaneh | Environmental Science | Research Excellence Award

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Research Excellence Award

Javad Momeni Damaneh
Hormozgan University (Alumnus), Iran.

Javad Momeni Damaneh
Affiliation Hormozgan University (Alumnus)
Country Iran
Scopus ID 58000716900
Documents 6
Citations 47
h-index 2
Subject Area Environmental Science
Event International Soil Scientist Awards
ORCID 0009-0006-9131-6167

Javad Momeni Damaneh is an Iranian researcher and alumnus of Hormozgan University working in environmental science. His research applies machine learning and species distribution modeling to ecological niche prediction, soil erosion susceptibility and groundwater quality. He is nominated for the Research Excellence Award at the International Soil Scientist Awards in recognition of his contributions to environmental modeling [1][2].

Abstract

This article presents the research profile of Javad Momeni Damaneh in connection with the Research Excellence Award. His work uses machine learning and maximum entropy modeling to predict the distribution of ecologically important plant species [1], to assess soil erosion susceptibility [2], and to evaluate spatial variation in groundwater quality [3]. His Scopus record lists six documents and 47 citations [5].

Keywords

Machine learning, ecological niche modeling, soil erosion susceptibility, maximum entropy, groundwater quality, spatial interpolation, drylands, land degradation.

Introduction

Dryland and semi-arid environments face pressures from soil degradation, vegetation loss and declining water quality. Data-driven spatial modeling has become an important approach for understanding these processes and for supporting land management decisions. Javad Momeni Damaneh’s publications apply such methods to rangeland species, erosion-prone basins and aquifers, mainly in Iran [1][4].

Research Profile

Momeni Damaneh is an alumnus of Hormozgan University, and his subject area is environmental science. His Scopus Author ID is 58000716900. The profile shows six documents, 47 citations and an h-index of 2 [5]. His research covers three main themes:

  • Species distribution and ecological niche modeling
  • Soil erosion assessment and land degradation
  • Geostatistical analysis of groundwater quality

Research Contributions

In ecological informatics, Momeni Damaneh and co-authors compared machine learning models to predict the ecological niche of wild pistachio, providing spatial information relevant to conservation and land-use planning [1]. A related study used the maximum entropy model to predict the growth of Ferula assa-foetida L. in northeastern Iran, published in the Iranian Journal of Range and Desert Research.

In water resources, he co-authored an evaluation of interpolation methods for mapping groundwater qualitative parameters in the Gonabad Plain [3].

Publications

  • Momeni Damaneh, J., Ahmadi, J., Rahmanian, S., Sadeghi, S. M. M., Nasiri, V., & Borz, S. A. (2022). Prediction of wild pistachio ecological niche using machine learning models. Ecological Informatics, 72, 101907. https://doi.org/10.1016/j.ecoinf.2022.101907 [1]
  • Momeni Damaneh, J., Safdari, A. A., Azarnejad, N., Ghorbani, M., Panahi, F., et al. (2025). Modeling soil erosion susceptibility using machine learning techniques: Rud-e-Faryab Basin, Iran. Land Degradation & Development, 36(18), 6396–6409. [2]
  • Momeni Damaneh, J., Joulaei, F., Alidadi, H., & Peiravi, R. (2015). Evaluation of interpolation methods to determine spatial variations of groundwater qualitative parameters (Case study: Gonabad Plain). Journal of Research in Environmental Health, 1(3), 165–176. [3]

Research Impact

According to the figures supplied for this profile, the 2022 wild pistachio study has received 51 citations, the 2022 chapter on soil erosion control in drylands 30, the 2015 groundwater interpolation study 21, the 2021 Ferula assa-foetida study 15 and the 2025 erosion susceptibility study 8. These counts come from a citation database and may differ from the Scopus total of 47 because of differences in coverage and update timing [5]. The practical value of this work lies in its support for conservation planning, erosion control and groundwater monitoring in dryland regions.

Award Suitability

Momeni Damaneh is considered suitable for the Research Excellence Award on the following grounds:

  • Publications in international peer-reviewed journals and an academic book volume [1][2]
  • Application of machine learning to soil and ecological problems
  • Research relevant to land degradation and sustainable land management
  • A publication record spanning from 2015 to 2025

Conclusion

Javad Momeni Damaneh’s research demonstrates a sustained focus on environmental modeling with relevance to soils, vegetation and water resources. His nomination for the Research Excellence Award at the International Soil Scientist Awards recognizes the practical orientation and methodological breadth of his work [1][2].

References

  1. Momeni Damaneh, J., Ahmadi, J., Rahmanian, S., Sadeghi, S. M. M., Nasiri, V., & Borz, S. A. (2022). Prediction of wild pistachio ecological niche using machine learning models. Ecological Informatics, 72, 101907.
    https://doi.org/10.1016/j.ecoinf.2022.101907
  2. Momeni Damaneh, J., Safdari, A. A., Azarnejad, N., Ghorbani, M., Panahi, F., et al. (2025). Modeling soil erosion susceptibility using machine learning techniques: Rud-e-Faryab Basin, Iran. Land Degradation & Development, 36(18), 6396–6409.
    https://onlinelibrary.wiley.com/journal/10991530
  3. Momeni Damaneh, J., Joulaei, F., Alidadi, H., & Peiravi, R. (2015). Evaluation of interpolation methods to determine spatial variations of groundwater qualitative parameters (Case study: Gonabad Plain). Journal of Research in Environmental Health, 1(3), 165–176.
    https://www.researchgate.net/publication/373330915
  4. Momeni Damaneh, J., Esmaeilpour, Y., Gholami, H., & Farashi, A. (2021). Properly predict the growth of Ferula assa-foetida L. in northeastern Iran using the maximum entropy model. Iranian Journal of Range and Desert Research, 28(3), 578–592.
    https://orcid.org/0009-0006-9131-6167
  5. Elsevier. (n.d.). Scopus author details: Javad Momeni Damaneh, Author ID 58000716900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58000716900

Alberto Donini | Data Science and Analytics | Innovative Research Award

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Innovative Research Award

Alberto Donini — Università di Bologna, Italy

Alberto Donini
Affiliation Università di Bologna
Country Italy
Scopus ID 57194041679
Documents 5
Citations 27
h-index 3
Subject Area Data Science and Analytics
Event International Soil Scientist Awards
ORCID 0009-0005-4142-3645

Alberto Donini is a researcher affiliated with the Università di Bologna, Italy, whose work falls within data science and analytics[1]. He is presented here in connection with the Innovative Research Award, organised under the International Soil Scientist Awards [5].

Abstract

This article summarises the research profile of Alberto Donini of the Università di Bologna in the context of the Innovative Research Award. His output addresses geophysical, geological and cosmological modelling, together with an erosion-based dating approach applied to a Roman monument. Records show five documents and 27 citations [1]. Recent works were deposited openly on Zenodo in September and October 2026 [2].

Keywords

Data science, analytics, Relative Erosion Method, Hollow Earth Shell, Hollow-Planet Model, primordial black holes, glaciations, seismological simulation, Arch of Augustus.

Introduction

Recognition programmes for researchers increasingly consider openly shared, computationally oriented work alongside traditional journal output. Donini is identified by Scopus Author ID 57194041679 [1] and holds an ORCID record [3]. His recent contributions explore quantitative and simulation-based approaches to questions in Earth science, archaeology and cosmology.

Research Profile

Donini is affiliated with the Università di Bologna, Italy, with a subject classification of Data Science and Analytics. Bibliometric indicators currently show five documents, 27 citations and an h-index of 3 [1]. His profile is distinguished by interdisciplinary breadth, linking measurement, modelling and interpretation across several fields.

Research Contributions

His contributions can be grouped into three areas:

  • Erosion-based analysis: the Relative Erosion Method (REM) applied to the Arch of Augustus in Rimini, presented in Italian and English versions [2].
  • Earth modelling: a simulation of seismological results assuming a Hollow Earth Shell (HES) [2].
  • Cosmological and palaeoclimatic modelling: a preliminary Hollow-Planet Model (HPM) with primordial black holes, and a study of ancient civilizations, endogenous catastrophes and glaciations under the HFTPW model [2].

These models are exploratory and unconventional; their evaluation rests on continued scholarly discussion and independent testing.

Publications

  1. Ancient Civilizations, Endogenous Catastrophes, Glaciations and the HFTPW Model. Zenodo, 28 October 2026. DOI: 10.5281/ZENODO.23740510.
  2. “Relative Erosion Method” (“REM”) applied to the Arch of Augustus in Rimini. Zenodo, 22 October 2026. DOI: 10.5281/ZENODO.23568559.
  3. “Metodo Dell’Erosione Relativa” (“REM”) applicato all’Arco d’Augusto di Rimini. Zenodo, 17 October 2026. DOI: 10.5281/ZENODO.23438971.
  4. Preliminary Cosmological Hollow-Planet Model (HPM) and Primordial Black Holes (PBHs). Zenodo, 23 September 2026. DOI: 10.5281/ZENODO.22913819.
  5. Simulation of Seismological Results Assuming a Hollow Earth Shell (HES). Zenodo, 23 September 2026. DOI: 10.5281/ZENODO.22913769.

Research Impact

The 27 recorded citations and h-index of 3 indicate early but measurable engagement with his work [1]. Open deposition on Zenodo with persistent DOIs makes the material accessible for scrutiny, reuse and citation [4]. The bilingual presentation of the REM study also widens its readership across Italian and international audiences.

Award Suitability

The Innovative Research Award is intended to recognise original approaches [5]. Donini’s candidacy rests on the following considerations:

  • Originality in proposing new modelling frameworks and an erosion-based method for monument analysis.
  • Interdisciplinary reach across geophysics, archaeology, climatology and cosmology.
  • Sustained recent activity, with five openly accessible works within roughly six weeks.
  • Transparent dissemination through DOI-registered repositories [4].

Conclusion

Alberto Donini’s recent output reflects an exploratory, model-driven approach spanning several disciplines. With a documented Scopus record and openly archived publications, his work offers material for further evaluation by the research community. His nomination for the Innovative Research Award acknowledges this originality and productivity [1][5].

References

  1. Elsevier. (n.d.). Scopus author details: Alberto Donini, Author ID 57194041679. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57194041679
  2. Donini, A. (2026). “Relative Erosion Method” (“REM”) applied to the Arch of Augustus in Rimini. Zenodo.
    https://doi.org/10.5281/ZENODO.23568559
  3. ORCID. (n.d.). Alberto Donini (ORCID iD 0009-0005-4142-3645). ORCID.
    https://orcid.org/0009-0005-4142-3645
  4. Donini, A. (2026). Ancient Civilizations, Endogenous Catastrophes, Glaciations and the HFTPW Model. Zenodo.
    https://doi.org/10.5281/ZENODO.23740510
  5. International Soil Scientist Awards. (n.d.). Official awards website.
    https://soilscientists.org/

Nongrui Qin | Data Science and Analytics | Best Scholar Award

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Best Scholar Award

Nongrui Qin
Dalian University of Technology, China

Nongrui Qin
Affiliation Dalian University of Technology
Country China
Scopus ID 61019853200
Documents 1
Subject Area Data Science and Analytics
Event International Soil Scientist Awards

Nongrui Qin is a researcher at Dalian University of Technology, China, working in data science and analytics. The researcher is listed in the Scopus database under author ID 61019853200 [1] and is recognized under the Best Scholar Award category of the International Soil Scientist Awards for early-stage contributions to intelligent systems research.

Abstract

This article summarizes the scholarly profile of Nongrui Qin, whose work addresses decision-making for autonomous vehicles through data-driven methods. The researcher is a co-author of an open-access article on multi-stage social value orientation-based lane-changing, published in Advanced Intelligent Systems in 2026 [2].

Keywords

Data science, analytics, autonomous vehicles, lane-changing, social value orientation, intelligent systems.

Introduction

Autonomous driving requires vehicles to interact safely with other road users whose behavior varies. Social value orientation, a concept from social psychology, describes how much an agent weighs its own outcomes against those of others, and it has been applied to interaction-aware planning for vehicles [3]. Research in this area aims to make lane-changing maneuvers safer, smoother, and more predictable in mixed traffic.

Research Profile

Nongrui Qin is affiliated with Dalian University of Technology, and the Scopus record lists one document, zero citations, and an h-index of zero [1]. These figures reflect an early career stage, and the subject area is recorded as Data Science and Analytics.

Research Contributions

The researcher contributed to a study on multi-stage, social value orientation-based lane-changing for autonomous vehicles [2]. The principal themes of the work include:

  • Modeling social preferences within vehicle interactions.
  • Structuring lane-changing decisions into sequential stages.
  • Applying data-driven methods to autonomous driving behavior.

Publications

Qin, N., Cai, L., Luo, Y., Yue, M., & Guan, H. (2026). Multi-Stage Social Value Orientation-Based Lane-Changing Driving for Autonomous Vehicles. Advanced Intelligent Systems. The article is open access [2].

Research Impact

As a recent publication, the article has not yet accumulated citations [1]. Its open-access status supports wider readership, and related studies on social value orientation suggest continuing interest in the topic across intelligent vehicle research [3].

Award Suitability

The nomination for the Best Scholar Award under the International Soil Scientist Awards recognizes emerging scholarship and the application of data science and analytics to complex systems. The researcher’s publication in an international journal, together with institutional affiliation and a verifiable Scopus record, supports consideration within this category [1].

Conclusion

Nongrui Qin is an early-career researcher at Dalian University of Technology whose work on socially aware lane-changing contributes to research on autonomous vehicle decision-making [2]. The recognition acknowledges this contribution and the potential for further research.

References

  1. Elsevier. (n.d.). Scopus author details: Nongrui Qin, Author ID 61019853200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=61019853200
  2. Qin, N., Cai, L., Luo, Y., Yue, M., & Guan, H. (2026). Multi-stage social value orientation-based lane-changing driving for autonomous vehicles. Advanced Intelligent Systems. Wiley.
  3. International . (2026). International Soil Scientist Awards, (1).
    https://soilscientists.org/

Hyginus Ozioko | Environmental and Sustainable Materials | Best Researcher Award

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Best Researcher Award

Hyginus Ozioko
Michael Okpara University of Agriculture, Umudike, Nigeria

Hyginus Ozioko
Affiliation Michael Okpara University of Agriculture, Umudike
Country Nigeria
Scopus ID 60379357200
Documents 2
Citations 1
h-index 1
Subject Area Environmental and Sustainable Materials
Event International Soil Scientist Awards
ORCID 0000-0001-6470-8671

Hyginus Ozioko is a researcher affiliated with Michael Okpara University of Agriculture, Umudike, Nigeria, whose work addresses environmental and sustainable materials. His publications examine sustainable concrete, soil-based construction materials and bioremediation, often combined with machine learning and statistical modeling. This article summarizes his research profile in connection with the International Soil Scientist Awards. [1]

Abstract

This article presents the research profile of Hyginus Ozioko, whose recent work applies experimental testing and predictive modeling to sustainable construction materials and contaminated soil remediation. His studies investigate agricultural and industrial waste as concrete admixtures, palm kernel shell concrete under different curing methods, laterite as a partial substitute for sharp sand in cement blocks, and geopolymer concrete prediction using artificial intelligence. [2][3]

Keywords

Sustainable concrete, agricultural waste, geopolymer concrete, laterite, bioremediation, machine learning, predictive modeling, environmental materials.

Introduction

Construction materials and soil management are closely linked to environmental sustainability. The use of waste-derived and locally available materials can reduce dependence on conventional resources, while data-driven models can help estimate material performance with fewer laboratory trials. Ozioko’s work sits at this intersection, pairing laboratory evaluation with computational prediction. [2]

Research Profile

According to his Scopus author record, Ozioko holds Author ID 60379357200 with two indexed documents, one citation and an h-index of one. [1] His ORCID record additionally lists several recent journal articles from 2025 and 2026, produced with collaborators including Emmanuel Ebube Eze, Ekunie Augustine Chidera, Edward Ingio Adah and Henry Ogumere. [5]

Research Contributions

  • Sustainable concrete: experimental evaluation and predictive modeling of concrete incorporating agricultural and industrial waste admixtures. [2]
  • Palm kernel shell concrete: compressive strength under various curing methods, with machine learning prediction. [3]
  • Alternative aggregates: assessment of laterite soil as a substitute for sharp sand in cement block production. [4]
  • Soil remediation: bioremediation of hydrocarbon-contaminated soils using artificial neural networks and response surface methodology. [5]

Publications

  • “Experimental evaluation and predictive modeling of sustainable concrete incorporating agricultural and industrial waste admixtures,” Discover Civil Engineering, 2026. [2]
  • “Sustainable Bioremediation of Hydrocarbon-Contaminated Soils Using ANN and RSM,” Journal of Water and Environmental Nanotechnology, 2026. [5]
  • “Study of Compressive Strength of Palm Kernel Shell Concrete Under Various Curing Methods,” Engineering and Technology Journal, 2026. [3]
  • “Suitability assessment of laterite soil as alternative to sharp sand in cement block production,” Nigerian Journal of Technology, 2026. [4]
  • “Artificial intelligence-based prediction of compressive strength of metakaolin-saw dust geopolymer concrete,” Journal of Management and Engineering Sciences, 2025.

Research Impact

The author’s indexed record is at an early stage, with two documents and one citation in Scopus. [1] Its relevance lies in topic focus: the studies address practical questions in low-cost, locally sourced construction materials and environmental remediation, and they apply modeling methods that may support reduced experimental effort in future work.

Award Suitability

Ozioko’s work on soil-based materials, waste utilization and contaminated soil remediation relates to the scope of the International Soil Scientist Awards. His combination of laboratory investigation and machine learning in soil and materials research is consistent with the recognition of emerging researchers in environmental and sustainable materials. [3][4]

Conclusion

Hyginus Ozioko is an early-career researcher whose recent publications connect sustainable construction materials, soil science and predictive modeling. His portfolio shows a consistent thematic direction and continuing output, and it provides a basis for recognition under the Best Researcher Award category. [1][2]

References

  1. Elsevier. (n.d.). Scopus author details: Hyginus Ozioko, Author ID 60379357200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=60379357200
  2. Ozioko, H. O., Eze, E. E., & Chidera, E. A. (2026). Experimental evaluation and predictive modeling of sustainable concrete incorporating agricultural and industrial waste admixtures. Discover Civil Engineering.
    https://doi.org/10.1007/s44290-026-00596-7
  3. Ozioko, H. O., Eze, E. E., & Adah, E. I. (2026). Study of compressive strength of palm kernel shell concrete under various curing methods and predictive modeling using machine learning. Engineering and Technology Journal.
    https://doi.org/10.30684/2412-0758.1567
  4. Ozioko, H. O., Eze, E. E., & Ekunie, A. C. (2026). Suitability assessment of laterite soil as alternative to sharp sand in cement block production: Performance evaluation and predictive analysis. Nigerian Journal of Technology.
    https://doi.org/10.4314/njt.2025.4767
  5. Ozioko, H., Eze, E., & Ogumere, H. (2026). Sustainable bioremediation of hydrocarbon-contaminated soils using ANN and RSM with enhanced feature engineering and data augmentation. Journal of Water and Environmental Nanotechnology.
    https://doi.org/10.22090/jwent.2026.2074964.1982

Khloud Samkari | Data Science and Analytics | Women Researcher Award

Published on by Soil Scientist

Women Researcher Award

Khloud Samkari
Umm Al-Qura University, Saudi Arabia

Khloud Samkari
Affiliation Umm Al-Qura University
Country Saudi Arabia
ORCID ID 0009-0009-5686-4506
Documents 1
Subject Area Data Science and Analytics
Event International Soil Scientist Awards

Khloud Samkari is a researcher affiliated with Umm Al-Qura University, Saudi Arabia, working in data science and analytics. She is recognized in the context of the Women Researcher Award presented under the International Soil Scientist Awards [3]. Her scholarly record includes a recent journal article examining the financial structure and profitability of green bond issuers [2].

Abstract

This article presents an academic profile of Khloud Samkari, a researcher at Umm Al-Qura University working in data science and analytics. It summarizes her research orientation, her indexed publication, and the relevance of her work to the Women Researcher Award. The profile draws on public scholarly records, including ORCID and DOI metadata [1][2].

Keywords

Data science, analytics, green bonds, financial structure, profitability, sustainable finance, Women Researcher Award.

Introduction

The International Soil Scientist Awards is an event that recognizes excellence, innovation, and leadership in soil science, sustainability, and related environmental research [3]. Within this framework, the Women Researcher Award acknowledges female scholars whose work demonstrates academic merit and relevance to sustainability-oriented inquiry. Khloud Samkari is considered here on the basis of her data-driven research and her contribution to the study of sustainable finance.

Research Profile

Samkari is affiliated with Umm Al-Qura University in Saudi Arabia. Her subject area is data science and analytics, with applications in finance and sustainability. Her public researcher identifier is registered with ORCID under the iD 0009-0009-5686-4506 [1]. At present, one document is associated with her profile, and citation metrics are not publicly reported in the sources reviewed.

Research Contributions

Her principal contribution is a co-authored study of green bond issuers, which compares financial and non-financial firms. The work investigates how financial structure relates to profitability among organizations that issue green bonds [2]. Such analysis is relevant to the broader discussion of how environmentally labeled debt instruments interact with corporate performance. The study was prepared with Maha Alandejani and Alyaa AlGhanmi.

Publications

  • Alandejani, M., AlGhanmi, A., & Samkari, K. S. (2026). Financial structure and profitability of green bond issuers: Evidence across financial and non-financial firms. International Journal of Financial Studies. Journal article, published 12 October 2026. DOI: 10.3390/ijfs14100269 [2]

Research Impact

The article appears in an international, peer-reviewed venue focused on financial studies and is registered through a persistent digital object identifier, which supports discoverability and citation [2]. As the publication is recent, its long-term influence cannot yet be assessed through citation indicators. The impact described here is therefore limited to topical relevance and accessibility.

Award Suitability

Samkari’s profile aligns with the Women Researcher Award in several respects:

  • Research focused on data science and analytics.
  • A peer-reviewed publication addressing sustainable finance [2].
  • A verifiable ORCID record supporting transparent attribution [1].
  • Relevance to the sustainability themes of the awarding event [3].

Conclusion

Khloud Samkari is an early-stage researcher whose indexed work contributes to the analysis of green finance. Her recognition under the Women Researcher Award reflects her scholarly activity and the sustainability relevance of her research, while her record continues to develop.

References

  1. ORCID. (n.d.). Khloud Samkari, ORCID iD 0009-0009-5686-4506. ORCID.
    https://orcid.org/0009-0009-5686-4506
  2. Alandejani, M., AlGhanmi, A., & Samkari, K. S. (2026). Financial structure and profitability of green bond issuers: Evidence across financial and non-financial firms. International Journal of Financial Studies.
    https://doi.org/10.3390/ijfs14100269
  3. Clocate. (n.d.). International Soil Scientist Awards. Event listing.
    https://soilscientists.org/

Ren-Jwo Tsay | Soil Water Management | Innovative Research Award

Published on by Soil Scientist

Innovative Research Award

Ren-Jwo Tsay
Vanung University, Taiwan

Ren-Jwo Tsay
Affiliation Vanung University
Country Taiwan
Scopus ID 7005905431
Documents 10
Citations 258
h-index 3
Subject Area Soil Water Management
Event International Soil Scientist Awards
ORCID 0000-0001-9515-9994

Ren-Jwo Tsay is a researcher affiliated with Vanung University, Taiwan, whose work is indexed in Scopus and focuses on soil water management and related engineering applications. His profile has been associated with the International Soil Scientist Awards under the Innovative Research Award category [1].

Abstract

This article presents a neutral overview of the scholarly profile of Ren-Jwo Tsay, a researcher at Vanung University, Taiwan, in the context of the Innovative Research Award at the International Soil Scientist Awards. According to Scopus, the author has 10 indexed documents, 258 citations and an h-index of 3 [1]. Recent conference papers apply digital terrain modelling, Building Information Modeling (BIM), unmanned aerial vehicles and artificial intelligence to practical problems in civil and environmental engineering [2][3][4].

Keywords

Soil water management, Building Information Modeling, digital terrain model, barrier lake, unmanned aerial vehicles, structural cracks, artificial intelligence, disaster assessment.

Introduction

Soil and water systems are closely connected to land stability, infrastructure planning and disaster risk. Researchers working in this area increasingly rely on spatial data, remote sensing and digital modelling to understand terrain behaviour and water-related hazards. The International Soil Scientist Awards recognise contributions in soil science and associated disciplines, including innovative approaches that support sustainable land and water management [5]. Ren-Jwo Tsay’s published work fits within this broader applied, technology-oriented context.

Research Profile

Tsay is affiliated with Vanung University in Taiwan, and his author record is maintained in Scopus under the identifier 7005905431 and in ORCID under 0000-0001-9515-9994 [1]. His listed subject area is soil water management, while his recent conference output extends into geospatial engineering, construction informatics and automated structural assessment. The following indicators are reported in Scopus:

  • Indexed documents: 10
  • Total citations: 258
  • h-index: 3

Research Contributions

A 2026 conference paper examines the use of big-data digital terrain models together with BIM for assessing disasters associated with barrier lakes, which form when landslides or debris block river channels [2]. Another 2026 paper combines aerial photography from unmanned aerial vehicles with BIM for road landscape planning [3]. A 2025 paper explores artificial intelligence for graphical discrimination of structural cracks, relevant to infrastructure inspection and maintenance [4]. Together, these studies illustrate an applied emphasis on integrating terrain data, imaging and digital models.

Publications

Selected recent conference papers, each listing Ren-Jwo Tsay as contributor, include:

  • Big Data Digital Terrain Model Application of Building Information Modeling in Disaster Assessment of Barrier Lake (2026) [2]
  • Unmanned Aerial Vehicles Aerial Photography Combined with Building Information Modeling Applied in Road Landscape Planning Research (2026) [3]
  • Application of Artificial Intelligence in Graphical Discrimination of Structural Cracks (2025) [4]

Research Impact

With 258 citations across 10 indexed documents, the author’s record shows measurable uptake within the literature [1]. The h-index of 3 indicates that citations are concentrated in a small number of works. The recent papers appear in open-access conference proceedings, which supports accessibility for engineers, planners and researchers working on terrain analysis and infrastructure safety.

Award Suitability

The Innovative Research Award is intended to acknowledge original and practical contributions. Tsay’s profile may be considered relevant on the following grounds:

  • Application of BIM, UAV imagery and terrain data to hazard and planning problems [2][3]
  • Use of artificial intelligence for infrastructure condition assessment [4]
  • A sustained, indexed publication record in soil water management and related fields [1]

Conclusion

Ren-Jwo Tsay’s work combines geospatial technology, digital modelling and artificial intelligence in service of environmental and infrastructure challenges. His documented output and citation record provide a factual basis for recognition under the Innovative Research Award at the International Soil Scientist Awards [5].

References

  1. Elsevier. (n.d.). Scopus author details: Tsay, Ren-Jwo, Author ID 7005905431. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7005905431
  2. Tsay, R.-J. (2026). Big data digital terrain model application of building information modeling in disaster assessment of barrier lake. Engineering Proceedings, 159.
    https://doi.org/10.3390/engproc2026159013
  3. Tsay, R.-J. (2026). Unmanned aerial vehicles aerial photography combined with building information modeling applied in road landscape planning research. Engineering Proceedings, 134.
    https://doi.org/10.3390/engproc2026134009
  4. Tsay, R.-J. (2025). Application of artificial intelligence in graphical discrimination of structural cracks. Engineering Proceedings, 108.
    https://doi.org/10.3390/engproc2025108004
  5. ORCID. (n.d.). Ren-Jwo Tsay (ORCID iD 0000-0001-9515-9994). ORCID.
    https://orcid.org/0000-0001-9515-9994

Ayed Alluqmani | Environmental and Sustainable Materials | Innovative Research Award

Published on by Soil Scientist

Innovative Research Award

Ayed Alluqmani
Islamic University of Madinah, Saudi Arabia

Ayed Alluqmani
Affiliation Islamic University of Madinah
Country Saudi Arabia
Scopus ID 55622739300
Documents 73
Citations 1367
h-index 17
Subject Area Environmental and Sustainable Materials
Event International Soil Scientist Awards
ORCID 0000-0002-6204-7803

Ayed Alluqmani is a researcher at the Islamic University of Madinah whose work centres on environmental and sustainable materials, structural engineering, and computational modelling [1]. He is considered here within the framework of the Innovative Research Award, presented under the International Soil Scientist Awards.

Abstract

This article presents a scholarly profile of Ayed Alluqmani, affiliated with the Islamic University of Madinah, in the context of the Innovative Research Award. His publications address sustainable construction materials, advanced composite structures, masonry behaviour, and data-driven environmental prediction. Bibliometric data indicate a sustained publication record and a citation base reflecting engagement from the wider research community [1].

Keywords

Sustainable materials, ultra-high performance concrete, functionally graded materials, finite element analysis, masonry structures, machine learning, rainfall prediction, structural engineering.

Introduction

Sustainable materials research increasingly combines civil engineering, computational mechanics, and environmental science. Within this field, researchers evaluate how construction materials and structural systems can deliver adequate performance while reducing environmental burden. Ayed Alluqmani contributes to this area through collaborative studies published in international journals, with his work indexed in Scopus under author identifier 55622739300 [1].

Research Profile

Alluqmani is affiliated with the Islamic University of Madinah in Saudi Arabia. His subject area is classified here as environmental and sustainable materials, although his publications also extend into structural mechanics and environmental data analysis. Much of his work is co-authored with international collaborators, reflecting the multidisciplinary and collaborative nature of contemporary engineering research.

Research Contributions

  • Sustainable concrete technology: a 2023 study in Construction and Building Materials examined eco-friendly ultra-high performance concrete, considering cost, carbon emissions, and structural ductility [3].
  • Advanced structural modelling: research in Acta Mechanica applied a p-version finite element method based on third-order shear deformation theory to the free vibration and bending of porous bi-directional functionally graded sandwich shells [4]. A related study in Mechanics Based Design of Structures and Machines analysed porous plates reinforced with carbon nanotubes.

Publications

Selected publications, with citation counts as listed on the Scopus profile, include the following [1]:

  • Lakhdar, Z., Chorfi, S. M., Belalia, S. A., Khedher, K. M., Alluqmani, A. E., Tounsi, A., et al. (2024). Free vibration and bending analysis of porous bi-directional FGM sandwich shell using a TSDT p-version finite element method. Acta Mechanica, 235(6), 3657–3686. (255 citations)
  • Amran, M., Murali, G., Makul, N., Tang, W. C., & Alluqmani, A. E. (2023). Sustainable development of eco-friendly ultra-high performance concrete (UHPC): Cost, carbon emission, and structural ductility. Construction and Building Materials, 398, 132477. (217 citations)
  • Meftah, S. A., Aldosari, S. M., Tounsi, A., Cuong-Le, T., Khedher, K. M., et al. (2024). Simplified homogenization technique for nonlinear finite element analysis of in-plane loaded masonry walls. Engineering Structures, 306, 117822. (152 citations)

Research Impact

The citation profile indicates that several publications have been cited more than one hundred times, with the most cited item reaching 255 citations. Such figures suggest that the studies have been read and used by other researchers in structural mechanics, construction materials, and environmental modelling [1].

Award Suitability

The Innovative Research Award, presented under the International Soil Scientist Awards, recognises research that advances knowledge and offers practical relevance to sustainability and environmental science. Alluqmani’s work on lower-carbon concrete, computational methods for advanced materials, and machine learning for rainfall prediction aligns with these aims [1].

Conclusion

Ayed Alluqmani of the Islamic University of Madinah has built a research record spanning sustainable construction materials, advanced structural modelling, and environmental data analysis. His indexed output and citation profile document a consistent scholarly contribution, and his work reflects the integration of engineering and sustainability themes that the Innovative Research Award seeks to acknowledge.

References

  1. Elsevier. (n.d.). Scopus author details: Alluqmani, Ayed, Author ID 55622739300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55622739300
  2. ORCID. (n.d.). Ayed Alluqmani (ORCID iD 0000-0002-6204-7803). ORCID.
    https://orcid.org/0000-0002-6204-7803
  3. Amran, M., Murali, G., Makul, N., Tang, W. C., & Alluqmani, A. E. (2023). Sustainable development of eco-friendly ultra-high performance concrete (UHPC): Cost, carbon emission, and structural ductility. Construction and Building Materials, 398, 132477.
    https://doi.org/10.1016/j.conbuildmat.2023.132477
  4. Lakhdar, Z., Chorfi, S. M., Belalia, S. A., Khedher, K. M., Alluqmani, A. E., Tounsi, A., et al. (2024). Free vibration and bending analysis of porous bi-directional FGM sandwich shell using a TSDT p-version finite element method. Acta Mechanica, 235(6), 3657–3686.
    https://doi.org/10.1007/s00707-024-03901-6
  5. Kumar, V., Kedam, N., Sharma, K. V., Khedher, K. M., & Alluqmani, A. E. (2023). A comparison of machine learning models for predicting rainfall in urban metropolitan cities. Sustainability, 15(18), 13724.
    https://doi.org/10.3390/su151813724

Vivek Agarwal | Environmental and Sustainable Materials | Innovative Research Award

Published on by Soil Scientist

Innovative Research Award

Vivek Agarwal
University of Northumbria at Newcastle, United Kingdom

Vivek Agarwal
Affiliation University of Northumbria at Newcastle
Country United Kingdom
Scopus ID 57611659000
Documents 35
Citations 495
h-index 12
Subject Area Environmental and Sustainable Materials
Event International Soil Scientist Awards
ORCID 0000-0003-1185-3802

Vivek Agarwal is a researcher at the University of Northumbria at Newcastle whose work lies in environmental and sustainable materials. His scholarly output is indexed in Scopus under author ID 57611659000 [1]. This article presents his research profile in connection with the Innovative Research Award, presented within the International Soil Scientist Awards [3].

Abstract

This article summarizes the research profile of Vivek Agarwal, based at the University of Northumbria at Newcastle, with emphasis on environmental and sustainable materials. According to Scopus, his record includes 35 documents, 495 citations and an h-index of 12 [1]. The article reviews his research focus, publication indicators and relevance to the Innovative Research Award.

Keywords

Sustainable materials, environmental materials, materials research, research recognition, Scopus, innovation, soil science awards.

Introduction

Sustainable materials research addresses the development of materials and processes that reduce environmental burden while maintaining technical performance. The field is broad and interdisciplinary, spanning chemistry, engineering, environmental science and resource management [4]. Within this context, Vivek Agarwal conducts research at the University of Northumbria at Newcastle, an institution located in the United Kingdom [5].

Research Profile

Agarwal’s scholarly identity is documented through Scopus author ID 57611659000 [1] and ORCID iD 0000-0003-1185-3802 [2]. These persistent identifiers allow his publications and citation indicators to be verified independently. His principal subject area is environmental and sustainable materials.

Research Contributions

His contributions are associated with research directions that support environmentally responsible materials development. Typical themes in this area include:

  • Development and evaluation of sustainable and environmentally compatible materials.
  • Resource-efficient approaches to material design and application.
  • Interdisciplinary work connecting materials science with environmental objectives [4].

Publications

Scopus lists 35 indexed documents for Agarwal [1]. A complete, verifiable publication list, including DOI-linked entries, is available through his ORCID record [2]. Readers are encouraged to consult these records for article-level details.

Research Impact

Bibliometric indicators provide one measure of scholarly influence. Agarwal’s profile shows 495 citations and an h-index of 12, indicating that a meaningful share of his publications has been cited repeatedly [1]. These figures reflect Scopus data and may change as the database is updated.

Award Suitability

The Innovative Research Award, presented within the International Soil Scientist Awards, recognizes research that offers novel and practical contributions to environmental and related sciences [3]. Agarwal’s focus on sustainable materials, together with his documented publication and citation record, is consistent with the scope of this recognition.

Conclusion

Vivek Agarwal is a materials-oriented researcher whose indexed output and citation indicators reflect sustained engagement with environmental and sustainable materials. His profile is well documented through Scopus and ORCID, supporting transparent evaluation for the Innovative Research Award [1][2].

References

  1. Elsevier. (n.d.). Scopus author details: Vivek Agarwal, Author ID 57611659000. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57611659000
  2. ORCID. (n.d.). Vivek Agarwal (ORCID iD 0000-0003-1185-3802). ORCID.
    https://orcid.org/0000-0003-1185-3802
  3. Comparative Study of Groundwater-Induced Subsidence for London and Delhi Using PSInSAR.
    https://www.mdpi.com/2072-4292/13/23/4741
  4. Titirici, M., et al. (2022). The sustainable materials roadmap. Journal of Physics: Materials, 5(3), 032001.
    https://doi.org/10.1088/2515-7639/ac4ee5
  5. Northumbria University. (n.d.). Northumbria University Newcastle.

Ajay Sharma | Science Integration | Innovative Research Award

Published on by Soil Scientist

Innovative Research Award

Ajay Sharma
Globeir Private Limited, India.

Ajay Sharma
Affiliation Globeir Private Limited
Country India
ORCID ID 0009-0001-6077-9875
Documents 1
Subject Area Humanities and Science Integration
Event International Soil Scientist Awards

Ajay Sharma is a researcher affiliated with Globeir Private Limited, working in the subject area of Humanities and Science Integration. This article presents a neutral overview of his research profile in the context of the Innovative Research Award at the International Soil Scientist Awards. [1]

Abstract

This article summarizes the research profile of Ajay Sharma, whose work addresses the integration of humanities perspectives with scientific inquiry. The profile is documented through a registered ORCID record and one listed research document. The summary is considered in relation to the Innovative Research Award presented under the International Soil Scientist Awards. [1]

Keywords

Innovative research, humanities and science integration, interdisciplinary studies, soil science community, research recognition, ORCID.

Introduction

Interdisciplinary research increasingly combines methods and perspectives from different fields to address complex questions. Ajay Sharma is affiliated with Globeir Private Limited and works in the area of Humanities and Science Integration. His research identity is maintained through ORCID, a persistent identifier system that helps distinguish researchers and link them to their scholarly outputs. [1]

Research Profile

The profile lists one document and is identified by ORCID iD 0009-0001-6077-9875. Bibliometric indicators such as citation counts and h-index are typically derived from databases such as Scopus. At the time of writing, no Scopus author identifier or related metrics are specified for this profile. [2]

Research Contributions

The research contributions fall within the following thematic areas:

  • Linking humanities perspectives with scientific research approaches.
  • Supporting interdisciplinary dialogue relevant to the soil science community.
  • Documenting scholarly work through a persistent researcher identifier. [1]

Publications

One research document is associated with the profile. Published works are generally cited using a Digital Object Identifier (DOI), which provides a stable link to the record. Readers may consult the ORCID record for the current list of works and their DOI links. [1]

Research Impact

Research impact is commonly assessed through citations, readership, and influence on subsequent work. With a single listed document, quantitative indicators remain limited, and any assessment of impact should be treated as preliminary. Future publications and citations may provide a clearer picture. [2]

Award Suitability

The Innovative Research Award at the International Soil Scientist Awards recognizes research that demonstrates originality and relevance. Ajay Sharma’s focus on Humanities and Science Integration reflects an interdisciplinary orientation consistent with the idea of innovation in research. Final evaluation rests with the award organizers according to their published criteria.

Conclusion

Ajay Sharma of Globeir Private Limited is a researcher whose profile centers on integrating humanities and science. His registered ORCID record and listed document provide a verifiable basis for his nomination under the Innovative Research Award. [1]

References

  1. ORCID. (n.d.). ORCID record: Ajay Sharma, ORCID iD 0009-0001-6077-9875. ORCID.
    https://orcid.org/0009-0001-6077-9875
  2. Multi-Index Remote Sensing Assessment of Agro-Climatic Change and Agricultural Responses in Temperate and Semi-Arid Regions.
    https://www.mdpi.com/2072-4292/18/20/3496
  3. International Soil Scientist Awards. (n.d.). Official award website.
    https://soilscientist.org/