Explanatory Data Analysis
Useful insights from data
Our main focus is on exploratory data analysis, often in the form of discovering novel and unexpected patterns that may give useful insights. Even when predictive modelling is the final goal, it is essential to first get a solid grasp on the data. Regardless of the analysis task, we aim for algorithms that are accurate, provide interpretable results, and can be guided by the analyst (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 mostly work on multidisciplinary data science projects, as we strongly believe that this leads to interesting, fundamental data mining problems for which the solutions we propose have the potential to positively impact society.
News and updates
Zhe Wang, MSc
18 December 2019
Congratulations to Zhe Wang, who successfully defended his MSc thesis today!
New PhD student
1 August 2019
Lincen Yang, who previously did his Master thesis project in our group, has joined the EDA group as PhD student working on human-guided data science. Welcome!
More group changes
1 July 2019
Three people have finished: Marlo Brochard has completed his Bachelor thesis, and Laura Leising and Martijn Hoogland have finished their research internships. Congratulations!