Dmytro Charnyi | Earth and Planetary Sciences | Innovative Technology Leadership Award

Published on by Global Scholar Awards

Innovative Technology Leadership Award

Dmytro Charnyi
The Institute of Environmental Geochemistry of National Academy of Sciences of Ukraine

Dmytro Charnyi
Affiliation The Institute of Environmental Geochemistry of National Academy of Sciences of Ukraine
Country Ukraine
Scopus ID 55776816400
Documents 29
Citations 155
h-index 10
Subject Area Earth and Planetary Sciences
Event Global Scholar Awards
ORCID 0000-0001-6150-6433

Dmytro Charnyi is associated with applied environmental research spanning water treatment, groundwater systems, environmental geochemistry, and radioactive-waste management. Institutional records identify him as a Doctor of Technical Sciences and a senior scientist, while recent publications demonstrate applications of conventional treatment technologies and computational forecasting methods to environmental engineering problems. [1]

Abstract

Dmytro Charnyi is a Ukrainian researcher whose work connects environmental geochemistry, water treatment, radioactive waste management, groundwater systems, and applied engineering. His documented research addresses treatment of contaminated water, surface-water quality, groundwater prediction, and technologies relevant to environmental and nuclear safety. Recent publications examine sorption and coagulation for organic components in liquid radioactive waste and artificial neural networks for forecasting groundwater-level fluctuations. His profile indicates sustained scholarly activity across environmental engineering and Earth and planetary sciences, supported by indexed publications, citations, and international research collaboration. These contributions provide a substantive basis for considering technology leadership recognition within contemporary environmental research.

Keywords

Liquid radioactive waste, radionuclides, organic matter, activated carbon, water treatment, sorbents, oxidation, coagulation, filtration, groundwater level, artificial neural networks, data recovery, forecasting, wavelet analysis, surface-water quality, and environmental engineering. These terms reflect recurring subjects in his recent research and support focused academic indexing and discovery.

Introduction

Dmytro Charnyi works at the intersection of environmental engineering, geochemistry, hydrology, and radioactive-waste management. Public institutional records identify him as a Doctor of Technical Sciences and senior scientist at Ukraine’s Institute of Environmental Geochemistry. His research addresses practical environmental problems through treatment technologies, monitoring approaches, groundwater analysis, and applied methods. [1]

Research Profile

Dmytro Charnyi has a documented research profile associated with environmental geochemistry, water resources, radioactive waste, and engineering applications. Institutional sources identify his leadership within radioactive-waste management research, while publication records show work on groundwater forecasting and water-treatment processes. His supplied bibliometric record reports 29 documents, 155 citations, and h-index 10.

Research Contributions

Dmytro Charnyi contributes to environmental technology through research on water purification, contaminant removal, groundwater behavior, and radioactive-waste treatment. Recent work demonstrates adaptation of conventional sorption and coagulation methods for organic components in liquid radioactive waste, while other research applies artificial neural networks to groundwater-level forecasting. These studies support engineering decisions. [2][3]

Publications

Dmytro Charnyi‘s recent publication record includes studies of water treatment, groundwater dynamics, surface-water quality, and environmental technologies. Notable works include research on conventional treatment of organic components in liquid radioactive waste and forecasting groundwater-level fluctuations using artificial neural networks. Earlier studies addressed surface-source water quality and selection of treatment methods. [2][3][4]

Research Impact

Dmytro Charnyi‘s research impact is reflected in scholarly citation activity and application-oriented environmental research. The reported record of 155 citations and an h-index of 10 indicates measurable academic research visibility, while his publications address problems with direct relevance to water safety, environmental monitoring, radioactive-waste management, and engineering decision-making in Ukraine. [1]

Award Suitability

Dmytro Charnyi demonstrates characteristics relevant to an Innovative Technology Leadership Award through sustained work connecting scientific research with practical environmental technologies. His documented research integrates water treatment, groundwater forecasting, radioactive-waste management, and computational methods. These areas show an orientation toward applied innovation, interdisciplinary problem-solving, and technology-informed environmental protection and safety. [2][3][5]

Conclusion

Dmytro Charnyi represents a research profile centered on applied environmental engineering and technology development. His publications and institutional activities connect water treatment, groundwater analysis, environmental geochemistry, and radioactive-waste management. The documented record supports recognition for research-informed technological leadership where scientific methods are translated into approaches for monitoring, treatment, and safety. [1][2]

References

  1. Google Scholar. (n.d.). Dmytro Charnyi: Google Scholar profile. https://scholar.google.com.ua/citations?user=5nTmWpYAAAAJ&hl=uk
  2. Charnyi, D., Zabulonov, Y., Lukianova, V., Anpilova, Y., Chernova, N., Matselyuk, Y., & Marisyk, S. (2026). Adaptation of conventional water treatment technologies for organic component removal from liquid radioactive waste: sorption and coagulation mechanisms. Scientific Reports, 16, 2626. https://doi.org/10.1038/s41598-026-36799-2
  3. Charnyi, D., & Shevchenko, O. (2025). Forecasting of medium and long-term components of groundwater level fluctuations using artificial neural networks method. Meteorology, Hydrology, Environmental Monitoring, 2(8), 102–113. https://doi.org/10.15407/Meteorology2025.08.102
  4. Charnyy, D., Matseluk, Y., Levytska, V., Marysyk, S., & Chernova, N. (2021). Peculiarities of formation of water quality of surface sources of water supply as a factor of a choice of a method of water treatment. Land Reclamation and Water Management, (2), 45–54. https://doi.org/10.31073/mivg202102-307
  5. Helmholtz Centre for Environmental Research. (2026). Publication details: Adaptation of conventional water treatment technologies for organic component removal from liquid radioactive waste: sorption and coagulation mechanisms. https://www.ufz.de/index.php?en=20939&pub_id=31912

Giulia Cipriano | Earth and Planetary Sciences | Innovative Research Award

Published on by Global Scholar Awards

Innovative Research Award

Giulia Cipriano
University of Bari Aldo Moro, Italy

Giulia Cipriano
Affiliation University of Bari Aldo Moro
Country Italy
Scopus ID 57189524657
Documents 91
Citations 1,336
h-index 23
Subject Area Earth and Planetary Sciences
Event Global Scholar Awards
ORCID 0000-0002-2495-5165

Giulia Cipriano is a researcher affiliated with the University of Bari Aldo Moro whose scholarly work connects marine environmental science, biodiversity assessment, cetacean ecology, ecological modelling, and computational approaches. Her indexed research includes studies of Mediterranean marine ecosystems, species behaviour, habitat relationships, conservation, and data-driven ecological analysis, supporting interdisciplinary investigation and evidence-based environmental understanding.[1]

Abstract

Giulia Cipriano is a marine and environmental researcher whose publications examine Mediterranean biodiversity, cetacean ecology, marine habitats, ecological processes, and computational approaches to environmental analysis. Her research record demonstrates interdisciplinary engagement across biology, environmental science, marine conservation, ecological modelling, and machine learning. Published studies involving Cipriano address species identification, habitat relationships, feeding behaviour, environmental drivers, and ecosystem assessment. Her work combines field observations with quantitative and computational methods, contributing evidence relevant to marine monitoring and conservation planning. The profile presents a scholarly basis for consideration within an innovative research recognition framework focused on scientific contribution, methodological integration, and research impact.[1]

Keywords

Giulia Cipriano is associated with publication themes including machine learning, Random Forest, species distribution models, cetacean ecology, marine biodiversity, Mediterranean ecosystems, ecological monitoring, habitat modelling, marine conservation, dolphin photo-identification, computer vision, feeding behaviour, environmental drivers, marine spatial planning, and biodiversity assessment. These keywords reflect recurring methodological and ecological subjects represented across her documented scholarly publications.[2]

Introduction

Giulia Cipriano works within a research context where marine ecology increasingly depends on interdisciplinary observation, quantitative modelling, and computational interpretation. Her publication record includes investigations of cetaceans and Mediterranean marine environments, addressing ecological behaviour, habitat use, biodiversity, and conservation questions. Such research contributes to understanding complex relationships between organisms and changing environmental conditions.[3]

Research Profile

Giulia Cipriano has a documented research profile associated with the University of Bari Aldo Moro and marine environmental research. Available scholarly records identify interests encompassing conservation biology, marine biodiversity, marine mammals, fisheries management, and marine ecology. Her indexed publications demonstrate collaboration across biological, computational, environmental, and oceanographic research domains.[1]

Research Contributions

Giulia Cipriano contributes to research on marine megafauna through studies integrating ecological observations with analytical and computational techniques. Her collaborative publications include automated photo-identification of Risso’s dolphins and modelling of cetacean feeding behaviour. These contributions illustrate the application of computer vision and machine learning to ecological questions involving biodiversity monitoring and conservation.[4]

Publications

Giulia Cipriano appears as a co-author in peer-reviewed research addressing marine ecology, cetacean monitoring, environmental relationships, and computational analysis. Representative publications include work on SIFT-based photo-identification of Risso’s dolphins, convolutional neural networks for dolphin identification, and machine-learning modelling of cetacean feeding behaviour in the Central-Eastern Mediterranean Sea. These studies demonstrate methodological breadth across ecology and data-driven research.[4][5]

Research Impact

Giulia Cipriano has a research record indexed through scholarly databases and represented across collaborative publications. The supplied profile reports 91 documents, 1,336 citations, and an h-index of 23, while current public indexing records may display different totals as databases update. Her publications have addressed practical ecological monitoring challenges and the interpretation of environmental influences on marine species.[1]

Award Suitability

Giulia Cipriano presents characteristics relevant to an innovative research recognition framework through interdisciplinary publication activity, marine ecological investigation, and the application of computational methods to biological questions. Her documented work combines field-derived evidence with machine learning and computer vision, providing a reasonable scholarly basis for consideration under an award emphasizing methodological innovation and environmental research contribution.[4]

Conclusion

Giulia Cipriano represents an interdisciplinary research profile centred on marine environmental science, cetacean ecology, biodiversity, conservation, and computational analysis. Her documented publications demonstrate the integration of ecological knowledge with emerging analytical technologies, including machine learning and computer vision. On the supplied bibliometric information and published research evidence, her profile is suitable for consideration within an innovative research recognition context.[1]

References

  1. Elsevier. (n.d.). Giulia Cipriano — ScienceDirect author information and Scopus author details, Author ID 57189524657. ScienceDirect.
    https://www.sciencedirect.com/author/57189524657/giulia-cipriano
  2. ResearchGate. (n.d.). Giulia Cipriano research profile and publications. ResearchGate.
    https://www.researchgate.net/profile/Giulia-Cipriano
  3. ORCID. (n.d.). ORCID record: Giulia Cipriano, ORCID iD 0000-0002-2495-5165. ORCID.
    https://orcid.org/0000-0002-2495-5165
  4. Renò, V., Dimauro, G., Labate, G., Stella, E., Fanizza, C., Cipriano, G., Carlucci, R., & Maglietta, R. (2019). A SIFT-based software system for the photo-identification of the Risso’s dolphin. Ecological Informatics, 50, 95–101.
    https://doi.org/10.1016/j.ecoinf.2019.01.006
  5. Cherubini, C., Cipriano, G., Saccotelli, L., Dimauro, G., Coppini, G., Carlucci, R., Fanizza, C., & Maglietta, R. (2025). Cetacean feeding modelling using machine learning: A case study of the Central-Eastern Mediterranean Sea. Ecological Informatics, 86, 103066.
    https://doi.org/10.1016/j.ecoinf.2025.103066