Tansel Dogan | Engineering | Distinguished Scientist Award

Published on by Research Hypothesis

Distinguished Scientist Award

Tansel Dogan
DMT GMBH, Germany

Tansel Dogan
Affiliation DMT GMBH
Country Germany
Scopus ID 58149576600
Documents 4
Citations 26
h-index 3
Subject Area Engineering
Event International Research Hypothesis Excellence Award
ORCID 0000-0001-7511-5097

Tansel Dogan is a Germany-based researcher affiliated with DMT GMBH whose documented research record encompasses engineering, mining, sustainable transition, post-mining management, and the interaction between geological materials and cement-based systems. His indexed publication record includes work addressing particle grading and interfacial behavior in rock specimens, European coal-transition pathways, post-mining management in the Ruhr region, and the preservation and visualization of European coal-mining heritage. These publications provide a basis for considering his research profile in the context of the International Research Hypothesis Excellence Award. [1] [2] [3] [4]

Abstract

Tansel Dogan’s documented research activity is situated within engineering and mining-related research, with publications addressing both technical and broader sustainability dimensions of the mining sector. His recent work includes an investigation of particle grading in core-derived rock specimens and its relationship with cement-based paste filling, rock interfacial behavior, strength acquisition, and microstructural development. [1] His research record also includes studies of coal-transition pathways in the European Union, with attention to governance and regional transformation in Germany, Poland, and Czechia, as well as post-mining management in the Ruhr region and potential knowledge transfer to Kosovo’s mining sector. [2] [3] A further publication examines European coal-mining heritage through the CoalHeritage initiative. [4]

Keywords

Tansel Dogan; Engineering; Mining Engineering; Sustainable Mining; Coal Transition; Post-Mining Management; Rock Mechanics; Cement-Based Paste Filling; Mining Heritage; European Mining; Knowledge Transfer; Regional Transformation; Microstructural Development.

Introduction

Contemporary mining engineering increasingly combines technical investigation of mining materials and processes with environmental, economic, governance, and regional-transition considerations. Within this context, Dogan’s documented publications represent several interconnected areas of mining research. The 2026 article on particle grading examines the behavior of core-derived rock specimens when used in cement-based paste filling systems, linking material characteristics with interfacial behavior, strength development, and microstructural progress. [1]

Research Profile

Dogan is affiliated with DMT GMBH in Germany and is identified in the supplied research record by Scopus Author ID 58149576600 and ORCID 0000-0001-7511-5097. The supplied bibliometric information records 4 documents, 26 citations, and an h-index of 3. These metrics provide a quantitative snapshot of the indexed record and should be interpreted in relation to publication dates, database coverage, disciplinary citation practices, and the development stage of the research portfolio.[1] [2] [3] [4]

Research Contributions

The available publications indicate several identifiable areas of research contribution:

  • Investigation of particle grading in core-derived rock specimens and its relationship with cement-based paste filling-rock interfacial behavior, strength acquisition, and microstructural development. [1]
  • Analysis of coal-transition pathways in the European Union, including governance and regional transformation across Germany, Poland, and Czechia. [2]
  • Research on sustainable transition and post-mining management in the Ruhr region, including consideration of prospective knowledge transfer to Kosovo’s mining sector. [3]
  • Contribution to the CoalHeritage initiative focused on visualizing and promoting Europe’s coal-mining heritage. [4]

Publications

The following publications are included in the supplied research record:

  1. Influence of particle grading of core-derived rock specimens on cement-based paste filling-rock interfacial behavior, strength acquisition, and microstructural progress. Green and Smart Mining Engineering, 2026.
  2. Coal Transition Pathways in the European Union: Governance and Regional Transformation in Germany, Poland, and Czechia. Sustainability, 2026.
  3. Examining Sustainable Transition and Post-Mining Management in the Ruhr Region and the Prospective Evaluation of Knowledge Transfer to Kosovo’s Mining Sector. Mining, 2024.
  4. CoalHeritage: Visualising and Promoting Europe’s Coal Mining Heritage. Mining, 2024.

Research Impact

The supplied bibliometric record reports 26 citations across 4 documents and an h-index of 3. These indicators suggest that the listed publications have received measurable scholarly attention within the indexed record. Citation counts, however, are database-dependent and can change over time; they therefore represent one dimension of research visibility rather than a complete assessment of research significance.[1] [2] [3] [4]

Award Suitability

For the International Research Hypothesis Excellence Award, the documented profile provides several areas that can be considered in relation to engineering-focused recognition. The research record includes peer-reviewed journal publications addressing technical mining engineering questions as well as sustainability and transition challenges affecting mining regions. [1] [2] [3] [4]

Conclusion

Tansel Dogan’s documented research profile at DMT GMBH is associated with engineering and mining-related scholarship spanning technical material behavior, sustainable mining transition, post-mining management, regional transformation, knowledge transfer, and mining heritage. The supplied record identifies 4 documents, 26 citations, and an h-index of 3, alongside an ORCID profile and Scopus author identifier. The listed publications provide a documented basis for recognizing the breadth of themes represented in the research record while allowing future work and additional bibliometric evidence to further develop the profile.

References

  1. Yilmaz, E.; Keskin, T.; Kasap, T.; Sari, M.; Selek, G.; Dogan, T.; Šancer, J.; Qi, C. (2026). Influence of particle grading of core-derived rock specimens on cement-based paste filling-rock interfacial behavior, strength acquisition, and microstructural progress. Green and Smart Mining Engineering.
    https://doi.org/10.1016/j.gsme.2026.03.007
  2. Dogan, T.; Flores, H.; Jarosławska-Sobór, S.; Šancer, J. (2026). Coal Transition Pathways in the European Union: Governance and Regional Transformation in Germany, Poland, and Czechia. Sustainability.
    https://doi.org/10.3390/su18189616
  3. Zeqiri, K.; Dogan, T.; Möllerherm, S.; Kasmaeeyazdi, S. (2024). Examining Sustainable Transition and Post-Mining Management in the Ruhr Region and the Prospective Evaluation of Knowledge Transfer to Kosovo’s Mining Sector. Mining.
    https://doi.org/10.3390/mining4030034
  4. Krassakis, P.; Karavias, A.; Zygouri, E.; Koukouzas, N.; Szewerda, K.; Michalak, D.; Jegrišnik, T.; Kamenik, M.; Charles, N.; Beccaletto, L.; et al., including Tansel Dogan. (2024). CoalHeritage: Visualising and Promoting Europe’s Coal Mining Heritage. Mining.
    https://doi.org/10.3390/mining4030028
  5. Elsevier. (n.d.). Scopus author details: Tansel Dogan, Author ID 58149576600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58149576600
  6. ORCID. (n.d.). Tansel Dogan — ORCID profile.
    https://orcid.org/0000-0001-7511-5097

Styliani Kontaki | Engineering | Innovative Research Award

Published on by Research Hypothesis

Innovative Research Award

Styliani Kontaki
University of West Attica, Greece

Styliani Kontaki
Affiliation University of West Attica
Country Greece
Documents 1
Subject Area Engineering
Event International Research Hypothesis Excellence Award
ORCID 0009-0009-5536-3144

Styliani Kontaki is a researcher affiliated with the University of West Attica in Greece whose documented research activity falls within the field of Engineering. Her listed scholarly record includes a journal article addressing time-series machine learning for fault diagnosis and severity estimation in industrial processes, published in Machines in September 2026. The publication brings together machine-learning methods and industrial process analysis, reflecting the application of computational approaches to engineering diagnosis and severity assessment. [1]

Abstract

Styliani Kontaki is associated with engineering research at the University of West Attica, Greece. The available publication record identifies her as a contributor to the study Time-Series Machine Learning for Fault Diagnosis and Severity Estimation in Industrial Processes, published in Machines in September 2026. The work examines the use of time-series machine-learning approaches for industrial fault diagnosis and severity estimation, linking data-driven computational methods with engineering process monitoring. The publication lists Paraskevi Zacharia, Styliani Kontaki, Konstantinos Moustris, and Constantinos Stergiou as contributors and is identified by DOI 10.3390/machines14091058. [1]

Keywords

Engineering; machine learning; time-series analysis; fault diagnosis; severity estimation; industrial processes; predictive analysis; industrial systems; data-driven engineering.

Introduction

Modern industrial systems generate substantial quantities of temporal and operational data that can be analyzed to identify deviations in system behavior. Time-series machine learning provides a framework for extracting patterns from sequential observations and can support engineering applications such as fault detection, diagnosis, classification, and severity estimation. The documented publication involving Styliani Kontaki applies this general research direction to industrial processes, focusing specifically on the relationship between time-dependent data and the identification and assessment of process faults. [1]

Research Profile

The available information places Styliani Kontaki within the Engineering subject area and associates her with the University of West Attica in Greece. Her documented research contribution includes participation in a multidisciplinary journal article focused on time-series machine learning for industrial fault diagnosis and severity estimation. The study’s contributor list indicates collaboration with Paraskevi Zacharia, Konstantinos Moustris, and Constantinos Stergiou. [1]

Research Contributions

The documented research contribution can be described through several interconnected areas:

  • Application of time-series machine-learning methods to industrial process data.
  • Investigation of computational approaches for fault diagnosis in industrial processes.
  • Consideration of fault severity estimation as an additional dimension of industrial condition assessment.
  • Contribution to collaborative engineering research combining machine learning and industrial process analysis.

These areas demonstrate a research direction in which data-driven methods are applied to practical engineering problems. The identified article provides the principal documented basis for describing this contribution. [1]

Publications

The supplied publication record identifies one journal article involving Styliani Kontaki:

  • Time-Series Machine Learning for Fault Diagnosis and Severity Estimation in Industrial Processes. Machines, September 2026. Contributors: Paraskevi Zacharia; Styliani Kontaki; Konstantinos Moustris; Constantinos Stergiou.

The article is published by the Multidisciplinary Digital Publishing Institute and is associated with the journal Machines. The DOI provides a persistent identifier for the publication and enables access to the publisher’s bibliographic record. [1]

Research Impact

The available information does not provide verified citation counts, h-index values, or other quantitative impact indicators for Styliani Kontaki. Accordingly, no numerical bibliometric impact assessment is assigned here. The documented research nevertheless addresses an applied engineering problem in which machine-learning techniques are used to analyze industrial process behavior, fault conditions, and severity. [1]

The potential relevance of this research lies in the broader use of data-driven methods for industrial monitoring and diagnosis. Further assessment of scholarly impact would require additional evidence such as citation data, subsequent publications, adoption of the methods, or documented industrial applications.

Award Suitability

The documented research profile provides a basis for consideration in the context of an Innovative Research Award associated with the International Research Hypothesis Excellence Award. In particular, the identified work connects machine-learning methodology with an applied engineering challenge involving industrial fault diagnosis and severity estimation. [1]

Conclusion

Styliani Kontaki is an engineering researcher affiliated with the University of West Attica in Greece. The documented publication Time-Series Machine Learning for Fault Diagnosis and Severity Estimation in Industrial Processes identifies her as a contributor to research applying time-series machine learning to industrial fault diagnosis and severity assessment. [1]

References

  1. Multidisciplinary Digital Publishing Institute. (2026). Time-Series Machine Learning for Fault Diagnosis and Severity Estimation in Industrial Processes. Machines. DOI: 10.3390/machines14091058.
    https://doi.org/10.3390/machines14091058
  2. ORCID. (n.d.). ORCID record for Styliani Kontaki.
    https://orcid.org/0009-0009-5536-3144
  3. Research Hypothesis. (n.d.). International Research Hypothesis Excellence Award.
    https://researchhypothesis.com/

Guo Ying | Engineering | Best Researcher Award

Published on by Research Hypothesis

Best Researcher Award

Guo Ying
Zhongyuan University of Technology

Guo Ying
Affiliation Zhongyuan University of Technology
Country China
Scopus ID 59836544400
Documents 32
Citations 491
h-index 14
Subject Area Engineering
Event International Research Hypothesis Excellence Award

Guo Ying is a researcher affiliated with Zhongyuan University of Technology in China whose documented scholarly record includes research in engineering, with particular activity in optical fiber and thulium-doped fiber laser technologies. The available bibliographic information identifies 32 documents, 491 citations, and an h-index of 14 in the supplied Scopus profile information. These indicators provide a quantitative overview of research output and citation visibility, while individual publications provide additional context concerning research themes and technical contributions.[1]

Abstract

The Best Researcher Award profile for Guo Ying summarizes a research record associated with Zhongyuan University of Technology and the engineering discipline. The supplied bibliographic record indicates 32 documents, 491 citations, and an h-index of 14, providing measurable indicators of publication activity and scholarly visibility.[1] Recent listed publications address thulium-doped fiber lasers, single-longitudinal-mode operation, wavelength tuning, narrow-linewidth performance, optical signal-to-noise characteristics, and composite mode-selection approaches. These studies are situated within the broader development of fiber-optic and laser technologies.[2] [3] [4]

Keywords

Guo Ying; Best Researcher Award; Zhongyuan University of Technology; Engineering; optical fiber technology; thulium-doped fiber laser; 2 μm wavelength; single-longitudinal-mode laser; narrow-linewidth laser; wavelength-tunable laser; gain switching; composite mode selection.

Introduction

Research in optical fiber technologies encompasses the design, characterization, and application of optical fibers, fiber-based light sources, and related photonic systems. Thulium-doped fiber lasers operating around the 2 μm region are of interest for applications and research involving infrared photonics because their spectral region supports specialized sensing, communications, and laser-system investigations. The publications supplied for Guo Ying’s profile focus on experimental laser architectures and methods for controlling longitudinal modes, linewidth, wavelength, and output characteristics.[2] [3]

Research Profile

The supplied research profile places Guo Ying within Engineering and associates the researcher with Zhongyuan University of Technology, China. The reported Scopus author identifier is 59836544400. The supplied metrics are 32 documents, 491 citations, and an h-index of 14.[1] Citation counts and h-index values are bibliometric measures that can change as databases are updated, and therefore should be interpreted as time-dependent indicators rather than permanent characteristics of a research career.[2] [3] [4]

Research Contributions

The supplied publication record identifies several related technical contributions in thulium-doped fiber laser research. The first listed article reports an experimental demonstration of a stable gain-switched single-longitudinal-mode thulium-doped fiber laser in the 2 μm wavelength region. Its stated emphasis on stable operation and longitudinal-mode control reflects an engineering approach to improving the spectral behavior of fiber lasers.[2][3]

Publications

The following publications are included in the supplied research record. The bibliographic details are presented as provided and should be cross-checked against the relevant publisher and indexing records for definitive metadata.

The three supplied articles were listed with zero citations in the source material at the time represented by the provided record. This article does not infer citation performance for the individual papers beyond the information supplied. The overall Scopus citation and h-index figures are reported separately in the researcher profile.[1]

Research Impact

Research impact can be considered through multiple dimensions, including publication output, citation activity, technical relevance, reproducibility, and contribution to a research community. The supplied Scopus indicators of 32 documents, 491 citations, and an h-index of 14 provide quantitative evidence of scholarly visibility within the indexed record.[1]

Award Suitability

The Best Researcher Award recognizes a research profile that can be evaluated through scholarly productivity, research relevance, publication quality, citation visibility, and demonstrated contributions to a field. Based on the information supplied for Guo Ying, the profile contains measurable bibliometric indicators together with recent publications in specialized engineering journals.[1]

  • Documented research activity within Engineering and optical fiber technologies.
  • A reported Scopus record comprising 32 documents, 491 citations, and an h-index of 14.[1]

Conclusion

Guo Ying’s supplied academic profile represents an engineering researcher associated with Zhongyuan University of Technology whose documented work includes research on thulium-doped fiber lasers and related optical-fiber technologies. The reported bibliometric indicators and publication record provide a basis for assessing scholarly productivity and research visibility, while the recent articles demonstrate continued activity in experimental fiber-laser engineering.[1] [2] [3] [4]

References

  1. Elsevier. (n.d.). Scopus author details: Guo Ying, Author ID 59836544400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59836544400
  2. Qin, Q., Liu, P., Liu, S., et al. (2026). Experimental demonstration of a stable gain-switched single-longitudinal-mode thulium-doped fiber laser at 2 μm wavelength region. Optical Fiber Technology.
  3. Xu, J., Yan, F., Li, T., et al. (2026). High-OSNR narrow-linewidth single-longitudinal-mode thulium-doped fiber laser enabled by composite mode selection. Infrared Physics and Technology.
  4. Qin, Q., Liu, P., Guan, B., et al. (2026). Investigation of UHNA fiber assisted wavelength tunable thulium-doped fiber laser. Infrared Physics and Technology.