The Statistical Learning Lab at IACM-FORTH, aims to be at the forefront of applied statistics and data science, with research on
The Statistical Learning Lab at IACM-FORTH, aims to be at the forefront of applied statistics and data science, with research on
- spatial and spatio-temporal modeling
- spatial and spatio-temporal modeling
- parametric nonlinear time series analysis
- parametric nonlinear time series analysis
- Bayesian modeling
- Bayesian modeling
- nonparametric functional data analysis.
- nonparametric functional data analysis.
The Lab addresses interdisciplinary research questions from a wide variety of fields, including Social Sciences, Geo-Sciences, Bioinformatics and Biomedical Engineering, Environmental and Transportation Engineering, among others. Representative applications constitute network flow forecasting and incident detection, predictive modeling for virtual heart transplants and Statistical Analysis of Transportation Emissions from Real World Testing.
The Lab addresses interdisciplinary research questions from a wide variety of fields, including Social Sciences, Geo-Sciences, Bioinformatics and Biomedical Engineering, Environmental and Transportation Engineering, among others. Representative applications constitute network flow forecasting and incident detection, predictive modeling for virtual heart transplants and Statistical Analysis of Transportation Emissions from Real World Testing.
Modern experimental designs and observational studies produce large and complex datasets which require sophisticated analytical tools. The Lab’s mission is to
Modern experimental designs and observational studies produce large and complex datasets which require sophisticated analytical tools. The Lab’s mission is to
a) collaborate with research groups from FORTH, the University of Crete and other academic institutions in research projects, publications and patents related to advanced quantitative analyses and predictive modeling;
a) collaborate with research groups from FORTH, the University of Crete and other academic institutions in research projects, publications and patents related to advanced quantitative analyses and predictive modeling;
b) team up with industrial partners, offering consulting services and development of analytics software, and
b) team up with industrial partners, offering consulting services and development of analytics software, and
c) act as an umbrella for researchers working in Cretan academic institutions who use and develop statistical, econometric and machine learning models.
c) act as an umbrella for researchers working in Cretan academic institutions who use and develop statistical, econometric and machine learning models.