Explanatory Data Analysis
Insights from data
We focus on exploratory data mining and interpretable machine learning. The goal of the former is knowledge discovery, i.e., to gain new insights from data, whereas the goal of the latter is to make intelligible, data-driven predictions. Regardless of the objective, we aim for algorithms that are accurate, principled and reliable, and can be guided by the analyst (in order to exploit prior knowledge).
Our research builds on the state of the art in information theoretic data mining (e.g., using the minimum description length (MDL) and maximum entropy principles), statistical pattern mining, and interactive data exploration and analytics. More broadly speaking, our research can be situated in the fields of data mining, machine learning, data science, and artificial intelligence (AI).
We often work on interdisciplinary projects, as we strongly believe that this leads to interesting, fundamental data mining and machine learning problems for which the solutions we propose have the potential to positively impact society.
News and updates
Dr. Hugo Proença
26 October 2021
Hugo has successfully defended his PhD thesis. Congratulations Dr. Hugo Proença!
6 August 2021
Congratulations to Atish, Floyd, and Milou, who successfully defended their MSc/BSc thesis projects!
Dr. Sarang Kapoor
14 June 2021
Sarang has successfully defended his PhD thesis. Congratulations Dr. Sarang Kapoor!
1 April 2021
We welcome Atish, Eric, and Milou to the group, while congratulations go to Siri and Michiel for successfully defending their theses!
New PhD student
16 December 2020
Hermes has started working on the 'AI for Neuroscience' project, in collaboration with the Neurology department of the LUMC. Welcome Hermes!