Gulnaz Zakariya | Data Science and Analytics | Research Excellence Award

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Mrs. Gulnaz Zakariya | Data Science and Analytics | Research Excellence Award

Satbayev University | Kazakhstan

Mrs. Gulnaz Zakariya is a researcher specializing in Machine Learning, Data Science, and Geospatial Analytics, with strong interdisciplinary contributions spanning FinTech and remote sensing. Her research focuses on the development of intelligent data-driven models for credit risk assessment, antifraud systems, and decision-support frameworks using machine learning and deep learning techniques. She has also made notable contributions to object-based image analysis and spatial change detection, particularly in the study of informal settlements using satellite imagery. Her work bridges applied artificial intelligence, geoinformatics, and financial technology, emphasizing model robustness, interpretability, and real-world deployment. She has published in peer-reviewed international journals and conferences indexed in major scholarly databases, contributing to innovation at the intersection of data science, spatial analytics, and applied AI-driven solutions.

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Featured Publications


Innovative Credit Scoring and Sales Accounting Solutions for SMEs in Kazakhstan

– Gulnaz Zakariya, Olzhas Akylbekov, Aiman Moldagulova,· FinTech, 2025


Object-based change detection of informal settlements

– P. Hofmann, G. Bekkarnayeva · JURSE 2017 (IEEE)

Olzhas Akylbekov | Data Science and Analytics | Research Excellence Award

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Mr. Olzhas Akylbekov | Data Science and Analytics | Research Excellence Award

Satbayev University | Kazakhstan

Mr. Olzhas Akylbekov is a researcher in data science and machine learning with a strong focus on applied artificial intelligence for spatial analysis and intelligent systems. His scholarly work emphasizes deep learning architectures, hybrid neural networks, and spatial data modeling for real-world decision support systems. According to Scopus, he has 2 peer-reviewed publications, with a total of 20 citations and an h-index of 2. His research contributions are published in internationally recognized journals indexed in Web of Science and Scopus, reflecting impact in areas such as urban spatial analytics and AI-driven content analysis.

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Featured Publications


Hybrid CNN-LSTM Network for Cyberbullying Detection on Social Networks using Textual Contents

– International Journal of Advanced Computer Science and Applications(IJACSA), 2023 · Cited by 19

Ana Josselinne Alegre Mondragón | Data Science and Analytics | Editorial Board Member

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Prof. Ana Josselinne Alegre Mondragón | Data Science and Analytics | Editorial Board Member

Geospatial Information Sciences Research Center | Mexico

Prof. Ana Josselinne Alegre Mondragón is a distinguished geospatial information sciences researcher whose scholarly contributions advance the understanding of violence dynamics, clandestine graves detection, and geospatial applications for public security and forensic investigations. Her research integrates geographic profiling, spatial statistics, remote sensing, UAV-based photogrammetry, and geointelligence modeling to address critical national challenges, particularly the search for missing persons and the analysis of organized crime patterns. She has authored influential book chapters, peer-reviewed journal articles, and scientific reports published by Springer, Forensic Sciences International, and leading academic institutions in Mexico. Her work includes the development of spectral indices for detecting clandestine graves, multivariate regional analyses of burial sites, geospatial modeling of crime, assessment of soil alterations linked to criminal activities, and advanced methodologies for drone-based terrain morphology assessment. She has actively contributed to high-impact research projects such as Espacio Clandestino, geospatial infrastructures for the Ayotzinapa investigation, and scientific applications supporting national systems for the search of missing persons. Her publications and research tools are widely referenced, shaping new standards for evidence-based forensic search protocols. She has collaborated on cross-disciplinary initiatives involving forensic science, anthropology, criminology, and remote sensing, generating innovative methodologies and academic outputs recognized both nationally and internationally. Her scholarly trajectory demonstrates a sustained commitment to advancing geospatial science for human rights, security analysis, and public policy, positioning her as a leading figure in Mexico’s emerging field of forensic geospatial analytics.

Profile: Scopus | ORCID

Featured Publications

  • Alegre-Mondragón, A. J. (2024). Cambios organizacionales en la policía de la Ciudad de México. Del modelo CompStat a la evaluación con transparencia y apertura hacia la ciudadanía. Revista Digital de Estudios Organizacionales, Universidad de Xalapa, Veracruz, México, 53–92. DOI: https://doi.org/10.69509/wxj14d34

  • Silván-Cárdenas, J. L., Alegre-Mondragón, A. J., Ramírez Aceves E. D., Campos Cornejo, D. R. & Bautista Nadalón, M. (2024). Diseño y aplicación de índices espectrales para la detección de fosas clandestinas. En Interpretar la naturaleza para encontrar a quienes nos faltan. COBUPEJ & CentroGeo, 355–389.

  • Alegre-Mondragón, A. J. & Silván-Cárdenas, J. L. (2024). Morfología del terreno mediante fotogrametría con drones: oportunidades y limitaciones para la detección de fosas clandestinas. En Interpretar la naturaleza para encontrar a quienes nos faltan. COBUPEJ & CentroGeo, 323–350.

  • Silván-Cárdenas, J. L. & Alegre-Mondragón, A. J. (2024). Espacio Clandestino: A Nationwide Platform to Support Clandestine Graves Search in Mexico. In Recent Developments in Geospatial Information Sciences. Springer, 175–186.

  • Alegre-Mondragón, A. J., Vilalta-Perdomo, C. J., Silván-Cárdenas, J. L. & Silva-Arias, C. (2024). Characteristics of Clandestine Burial Sites in Mexico: A Regional Overview with Multivariate Analysis. In Recent Developments in Geospatial Information Sciences. Springer, 53–64.

Adimias Wendimagegn | Data Science | Best Researcher Award

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Mr. Adimias Wendimagegn | Data Science | Best Researcher Award

Kotebe University of Education | Ethiopia

Mr. Adimias Wendimagegn is a data scientist and biostatistician specializing in statistical modeling, distribution theory, and applications in public health. His research primarily focuses on advanced regression frameworks, including classical and Bayesian modeling approaches under GAMLSS and BAMLSS structures. He has introduced novel models such as the Alpha Power Transformed Beta (APTBeta) regression for analyzing antenatal care utilization and developed methodological frameworks for Gamma and Beta-type distributions. He has published multiple peer-reviewed journal articles indexed in Scopus and Web of Science, contributing significantly to statistical theory and biostatistical applications. His works include studies on antenatal care utilization, maternal age at first birth, and advanced distributional models for proportion data. He is also the author of two academic books published by LAP Lambert Academic Publishing, covering joint modeling of longitudinal and survival data and determinants of teenage fertility in Ethiopia. His scholarly contributions extend to the development of R packages for regression modeling and diagnostics, enhancing reproducibility and accessibility in statistical analysis. Mr. Adimias Wendimagegnserves as a reviewer for leading international journals such as PLOS ONE and Value in Health, and his publications have received multiple citations reflecting his growing impact in the field. Through his research, he continues to advance innovative statistical methodologies and their applications in health and demographic studies.

Profile: ResearchGate

Featured Publications

  • Wendimagegn, A., & Arero, B. G. (2025, October). Alpha power transformed beta regression with application on antenatal care visit proportions among Ethiopian women. Journal of Statistical Theory and Applications. https://doi.org/10.1007/s44199-025-00135-w

  • Wendimagegn, A., Goshu, A. T., & Arero, B. G. (2024, September). New alpha power transformed beta distribution with its properties and applications. Frontiers in Applied Mathematics and Statistics, 10. https://doi.org/10.3389/fams.2024.1433767

  • Wendimagegn, A. (2019, March). Determinant of solid-waste management in Debre Birhan Town. American Journal of Theoretical and Applied Statistics, 8(1), 26–33. https://doi.org/10.11648/j.ajtas.20190801.14