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Τμήμα Οικονομικών Επιστημών

LABORATORY OF ANALYTICS AND DATA SCIENCE

Department of Economics

National and Kapodistrian University of Athens

Laboratory of Analytics and Data Science

About us

The Laboratory of Analytics and Data Science of the National and Kapodistrian University of Athens was founded in 2017. Our mission is to develop innovative ideas and techniques in the areas of Analytics, Data Science, and Artificial Intelligence.

The last decade has been characterized by a dramatic rise in computer power and in data and scientific break-troughs. These advances, on the one hand, have created new perspectives (not only in science, but also in economy, business and industry) and, on the other hand, they have led to new challenges. Therefore, the need for a lab oriented towards these areas has been emerged.

Our aim is to advance world-class research in the areas of (pure and applied) mathematics, data science and artificial intelligence. Our work supports both theoretical developments and application to real problems. Much of our research is driven by real-world problems, since it is one of our primary objectives to bridge the gap between academic work and its applications.

We collaborate with several departments of the University of Athens as well as other universities. We also collaborate with businesses, the industry and banking sector.

Additionally, we are seeking to establish further collaboration with universities, businesses, public and third sector organizations. We undertake research that tackles challenges in science, business and economy.

The lab consists of experienced scientists as well as sharp minded new researchers. Our group incorporates scientists with different backgrounds (economics, pure and applied mathematics, physics, statistics, computer science etc.). We are dedicated to our work and we are inspired by our desire to innovate and generate impact both in theoretical and practical problems.

People

Research

List of papers 

Our research efforts are oriented (but not limited) towards the following directions

  • Big data analysis
  • Machine learning
  • Interbank data
  • Credit Risk and Credit Ratings
  • Business and Financial Data
  • Economic networks
  • Data driven decision making

The models that we use include: classical regression models, Data Mining analysis and prediction, Gaussian process interpolation, Random forests, Neural networks, Decision trees, Monte –Carlo simulation.

Our current work is focused on the Koopman operator theory and data-driven EDMD algorithms. The purpose is to approximate a dynamical system (whose dynamics are non-linear or even unknown) with a linear dynamical system defined in a space of bigger dimensionality. Then, provided that the approximation is satisfactory, the linear system can be used for analysis, prediction and Control of the non-linear one.

Keywords

Pure and applied dynamical systems; control theory; Artificial intelligence; neural networks; big data science.

Contact Us

You can contact us by sending an e-mail.