AGLAIA G. KALAMATIANOU
Title/academic status: Professor
Sector: Social Morphology
Academic field: Applied Social Statistics
Phone: + 30 210 9201798
Address: 136, Syggrou ave., ATHENS, ATTICA 176 71, GREECE
Research interests: Survival models, stochastic Markovian models, multivariate methods, data mining techniques, growth models, quantitative approach of social research and their applications to social data.
Member in scientific associations: see Brief CV
- Statistics Ι: Introduction to the methods of univariate analysis.
- Statistics ΙΙ: Introduction to the methods of bivariate and Multivariate analysis.
- Statistics ΙΙΙ: Advanced multivariate methods for the analysis of data using statistical packages
- Methods and Techniques of Sociological Research I: the quantitative approach
- Quantitative Methods of Sociological Research
- B.S.C in Mathematics, University of Athens
- M. Sc, in Mathematics, Chelsea College, (now King's College), University of London
- Ph. D. in Statistics, London School of Economics & Political Science, University of London
Academic visits, on sabbatical leave Academic Visitor:
- University of Ulster, School of Informatics, Coleraine North Ireland UK and UMIST, Department of mathematics, Manchester England UK. 1/11/1998 - 30/10/1999.
- University of Cyprus Department of mathematics, 1/11/2004–30/05/2005.
- London School of Economics and Political Science, Department of Statistics, 1/11/2008-30/5/2009
- Milano Bicocca, Department of Statistics and Quantitative methods, 03/03/2014 -15/04/2014
I have been a member of Royal Statistical Society, Bernoulli Society for Mathematical Statistics and Probability, International Association for Statistical Computing, Manpower Society, Operational Research Society, Hellenic Statistical Institute, Hellenic Mathematical Society, and Hellenic Operational Research Society.
My current research interests concern the development of statistical models inspired by existing social problems as well as the implementation of social standards through data analysis. In particular, my scientific work includes survival analysis models, stochastic Markovian processes, multivariable analysis, data mining techniques, growth models, quantitative research methodology, and their application to social data. Current applications relate to education and employment data, mainly from the Higher Education Area. Specifically, issues are discussed regarding the distribution of the duration of university studies and the factors involved, the development process of student performance during studies, curricula, graduates' outputs in the labor market and the characteristics of their work (focusing mainly on the issues of overeducation and job and degree satisfaction), and lastly the overtime evolution process of gender participation in education.