Explanatory Data Analysis group

Research projects

Below is a list of concrete research projects (more to be added soon); there is also an overview of research themes.


SAPPAO – A Systems Approach towards Data Mining and Prediction in Airlines Operations
Joint project with the Natural Computing Group.
Project members
Matthijs van Leeuwen (LIACS), Hugo Manuel Proença (LIACS), Sarang Kapoor (IIT Roorkee), Dr. Dhish Saxena (IIT Roorkee), Dr. Michael Emmerich (LIACS), Divyam Aggarwal (IIT Roorkee), Prof. dr. Thomas Bäck (LIACS, PI)
Industrial partner
GE Aviation, Bangalore, India
Period
2016 – 2020
Description
By analysing historical flight data and data on the associated disruptive events on the flight network, the NWO-DeitY SAPPAO project aims to optimise the accuracy and reliability of predicting scheduled flight times, thereby potentially saving millions of Euro’s on better utilisation of airplanes, decreased fuel consumption, decreased CO2‐emissions, decrease of ambient noise and better use of time for passengers and airports. At LIACS we will focus on feature construction for improved flight predictability and reduced airline operating cost. The challenge in this prediction is that it is not clear which features should be used to obtain the best estimates. There is a wide range of available data, including network data, time series data, and so on, which is not straightforwardly used in existing attribute‐value based machine learning and statistical techniques. This project will deal with these challenges.

DAMIOSO – Data Mining on High Volume Simulation Output
Joint project with the Natural Computing Group.
Project members
Matthijs van Leeuwen (LIACS), Sander van Rijn (LIACS), Prof.dr. Stefan Manegold (LIACS, CWI), Dr. Michael Lew (LIACS), Thodoris Georgiou (LIACS), Pedro Holanda (CWI), Prof. dr. Thomas Bäck (LIACS, PI)
Other partners
Honda Research Institute Europe, Offenbach, Germany.
Period
2015 – 2019
Description
The DAMIOSO project, funded by NWO and Honda Research Europe, focuses on developing algorithms and tools for data management, data mining and knowledge extraction from massive volumes of data, as generated by modern simulation tools, which are being used in a wide range of industries (aerospace, automotive, shipping, and others), in order to deliver advanced design and process optimisation to support engineers in their design processes.

Research themes

Research projects