Statistical Learning Laboratory


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 modelling

- parametric nonlinear time series analysis

- Bayesian modelling

- 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 modelling 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

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 analysis and predictive modelling;

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.

For more information visit the Statistical Learning Lab Website.


For any information regarding the Group, please contact:

Remote Sensing Lab
Institute of Applied and Computational Mathematics
Foundation for Research and Technology - Hellas
Nikolaou Plastira 100, Vassilika Vouton,
GR 700 13 Heraklion, Crete

Tel: +30 2810 391800
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it. (Mrs. Maria Papadaki)

Tel.: +30 2810 391805
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it. (Mrs. Yiota Rigopoulou)

How to reach us
How to reach us (see Google map)