Projects

Research output often results from or centers around particular projects. Below is an overview of projects I am or was involved in.
Apart from projects, quite a number of my publications are simply the output of joined work with colleagues and students.

 

eScience Pathfinder project (2018-)

This project deals with eScience questions related to corporate network analysis and visualization, with particular focus on board interlock networks and ownership networks in the context of offshore finance. It is the result of the eScientist award that I received late 2017, and involves two research engineers from the eScience center.

Data-Driven Risk Assesment in Infrastructure Networks (2017-)

A four year project together with the inspectorate of the Dutch Ministry of Infrastructure and Water will focus on new data-driven methods for risk assessment, with the aim to for example better coordinate inspection efforts. As part of this project, two PhD students will work data of amongst other things (networks of) water transportation and vehicle movement.

Enriching official economic statistics using data-driven modelling techniques (2016-)

This four year research project aims to investigate data-driven modelling techniques from both computer science and economics in order to devise new methods, techniques and algorithms for determining official economic statistics. The project consists of one PhD student and is a collaboration between Centraal Bureau voor de Statistiek (CBS), the University of Amsterdam and Leiden University.

High Performance Corporate Network Analysis (2015-)

The main challenges addressed in this project deal with data management, availability and computation of large-scale network data. In particular, we are analyzing data on over 200 million corporations connected through hundreds of millions of links. This project’s multi-core big memory server architecture forms the backbone of the data analysis infrastructure of the CORPNET project (see below).

CORPNET (2015-)

At the CORPNET interdisciplinary research group of the University of Amsterdam, we use network science to understand the global economy. The five year project is a product of the 2015 ERC Starting Grant of Eelke Heemskerk, centered around the multidisciplinary collaboration between computer science and the social sciences on the analysis of corporate networks.  It considers data on corporate ownership and interlocking directorates, forming so-called networks of corporate control and features three PhD students and two postdocs.

RISK (2014-2015)

Project membership. This project, in collaboration with the Dutch National Police and Utrecht University, had as a main goal to better assess the risk around soccer matches and other soccer-related activities. Using state-of the art visualization and data science methods, we were able to devise a hands-on framework on an interactive itable. The resulting product could help police officers on a daily basis to make better decisions in terms of planning and allocation of resources around soccer matches, automatically re-using their past data on previous incidents related to soccer matches.

COMPASS (2010-2014)

Project membership. The goal of this project, in collaboration with TU Eindhoven, was the development of stream mining techniques for complex patterns such as graphs. The aim was to extend the existing state-of-the-art techniques into two, orthogonal directions: on the one hand, the mining of more complex patterns in streams, such as sequential patterns and evolving graph patterns (for example social networks), and on the other hand, more natural stream support measures taking into account the temporal nature of most data streams.