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Irma KveladzeView profile

Assistant Professor

• Geoinformatics
• Earth Observation
• Urban Planning
• +5 more

Dr. Irma Kveladze is a Tenure Track Assistant Professor at Aalborg University's Technical Faculty of IT and Design, specifically within the Department of Sustainability and Planning. Her research focuses on geoinformatics, earth observation, and urban mobility solutions. Current Affiliation: Aalborg University (Copenhagen campus), Technical Faculty of IT and Design Research Themes: Urban mobility, migration patterns, spatial data visualization, mixed reality geospatial applications Her work involves advanced spatial analysis and innovative cartographic representations, recently developing frameworks for micro-mobility integration in urban contexts through the PROMISE project. She contributes to mixed reality usability evaluation standards and analyzes digital communication networks across European countries. Key projects include: PROMISE (2025-2028): Principal Investigator for car dependency reduction through smart policy AquaINFRA (2024): Project participant in data infrastructure development She serves as peer reviewer for journals like Sustainability and ISPRS International Journal of Geo-Information , and participates in organizations such as AGILE and EuroSDR.

Manja Gersholm GrønbergView profile

Researcher

• Statistical Genetics
• Machine Learning
• Biostatistics
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Manja Gersholm Grønberg is a Postdoctoral researcher at the Technical University of Denmark (DTU) in the Department of Applied Mathematics and Computer Science, specifically within the Statistics and Data Analysis group. Her interdisciplinary research bridges statistics, computer science, and biomedical applications, contributing to several UN Sustainable Development Goals related to health and well-being. Her research interests span statistical genetics, machine learning, biostatistics, neuroscience, and data analysis with particular expertise in ordinal data modeling and single-cell RNA sequencing analysis. Dr. Grønberg's work demonstrates strong methodological innovation in crossed random effects models and neighborhood analysis techniques applied to complex biological datasets. Her recent publications (2024-2025) reveal a strong trend toward interdisciplinary applications, with significant contributions in both bioinformatics (scRNAseq data analysis) and neuroscience (brain stimulation techniques for Alzheimer's disease treatment). These works demonstrate her ability to develop sophisticated statistical methods and apply them to cutting-edge biomedical problems. Expertise in Crossed Random Effects modeling Specialization in Imbalanced Data techniques Research in Intranasal Oxytocin applications Advanced Neighborhood Analysis methods Cell Specification computational approaches Dr. Grønberg has served as an internal examiner for Statistical Genetics courses at DTU, demonstrating her expertise and teaching capabilities in this specialized field. Her completed PhD project on 'Computational methods for ordinal mixed models applicable to online user ratings' established her foundation in advanced statistical modeling. Her research team collaborations span multiple disciplines, connecting statistical methodology with biological and medical applications, particularly in the areas of neurodegenerative disease research and single-cell genomics.