Projects

Data is one of the most valuable resources businesses have today. Companies and institutions increasingly invest in tools and platforms to collect and store data about every event that is impacting their business, like their customers, transactions, products, and the market in which they operate. Although the costs for maintaining the huge, expanding volume of data are often considerable, companies are willing to make the investment as it ...

The project – in cooperation with the Joint Research Centre (JRC) of the European Commission – aims to develop and apply robust statistical and machine learning techniques for outlier/anomaly detection. Various approaches will be considered, such as distance/density or tree-based approaches, (generalised) Benford’s law, robust regression techniques, time series analysis and graphical models. Such methods will be applied to high-dimensional ...

In many research fields data dimension reduction techniques are widely used. Fields such as chemometrics, signal processing, and video compression, try to deal with these issues with tools that transform high-dimensional data to lower dimensions where the meaningful properties of the data are retained. Principal Component Analysis (PCA) is a widely used tool for dimension reduction. However, it is known that PCA is not robust against ...

The aim of this project is to develop a high-performance method for expressive and intuitive querying of data within the metastructure of the in-house developed NoSGL database management system, Dynizer.
Where the current survey follows technical expertise for the custom search of complex data structures using 3 basic queries, the query facility will be extended with generic query language that allows query searches based on semantic ...

Today's society generates data more rapidly than ever before, creating many opportunities as well as challenges for statisticians. Many industries become increasingly dependent on high-quality data, and the demand for sound statistical analysis of these data is rising accordingly.

In the insurance sector, data have always played a major role. When selling a contract to a client, the insurance company is liable for the claims arising ...

Fraud is a fierce threat to digital business. A typical organization is estimated to lose 5% of its revenues due to fraud, which is hard to eradicate since dynamic, system-dependent and organizationspecific. Powerful and intelligent fraud detection systems are therefore of crucial importance, to timely block, prevent and contain fraud and to mitigate losses. User and entity behavior analytics essentially profile the activity of users, peer ...

Ideally, a clinical trial should be conducted to provide evidence that a certain treatment improves some clinically relevant endpoint such as overall survival in oncology. Sometimes, the measurement of the clinically relevant endpoints is problematic because it requires a long follow-up time, is expensive to measure and/or requires an invasive procedure. This can complicate the design of the trial, increase the duration of the trial and ...