Research Support

What can we do for you?

The best way to learn how we can help you is to walk in during our walk-in hours or contact us for a (digital) coffee, so we can discuss your research, the challenges you face, and potential support we may be able to provide. What happens afterwards depends on the situation, but broadly speaking we will either consult or collaborate.

We can provide advanced statistics, community, data visualisation, workshops & webinars, machine learning, and much more. We work closely together with BMS Lab, Digital Competence Center, EEMCS High Performance Computing, and BMS Lab.

walk-in hours

We have walk-in hours (almost) every monday, from 15:00 to 16:00. During these hours, our data scientists will be available to answer all your questions. We're eager to learn what research you are doing, and explore any opportunities for applying modern data science together.

If we can't help you on the spot, we can set up a consultation later for us to prepare and discuss more in depth, refer you to other experts, or provide you with additional resources.

The next walk-in hour is November 25, 15:00–16:00.

Consultation

Consultations are always free. We will aim to provide advice and connect you with other researchers, communities or funding opportunities. Consultations are generally the first step towards collaboration.

To schedule a consultation, please reach out to bdsi@utwente.nl and one of our team members will answer your questions, or contact you for further consultations.

get in touch

Collaboration

BDSi also collaborates on projects with a high impact for data science at BMS. BDSi Data Science grants are provided several times per year to support projects with a high impact for data science at BMS.

BDSi Data Science grants are meant to:

  • kickstart high-risk, high-reward projects with an eye on obtaining further national and international funding at a later date
  • support valorization of ongoing BMS research with (interactive) visualization and data-exploration
  • explore data-driven approaches to new and existing lines of research by supporting the gathering, storage, and processing of complex datasets

For more information about the BDSi Data Science grants, please see the most recent call for proposals, or contact us directly. Keep an eye on our newsletter and this website for announcements about new calls for proposals.

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Latest Projects

Development of a methodological and statistical framework for studying mental health interventions with micro-randomised trials

Jannis Kraiss
, 
Anna MachensAnna Machens
, 
Ernst Bohlmeijer
, 
Jorge Piano Simoes
, 
Martin SchmettowMartin Schmettow
, 
and 
Peter ten KloosterPeter ten Klooster
This project is looking to improve the way we can study which mental health treatments work best for each person. Usually, researchers use group studies to test whether treatments work, but these don't always tell us what works for each individual. In this project, a new approach is developed for testing treatments more personally and more often using mobile technology. This will help researchers and clinicians understand what treatment is best for each person and may lead to improved mental health treatments. continue reading...

Digital Open Strategic Autonomy

Pauline Weritz
, 
Karel KroezeKarel Kroeze
, 
and 
Anna MachensAnna Machens
This project, led by a principal researcher serving as an Embassy Science Fellow in the UK, addresses the urgent need for digital open strategic autonomy (DOSA) and sustainable transformation policies. Focused on comparing Dutch and UK strategies, the study dissects six critical layers toward economic resilience in the digital economy. Employing a data-driven approach, the research involves gathering and analyzing official documents from Dutch and UK government websites, aiming to reveal differences, similarities, and dependencies behind policies. The key objectives include data scraping, descriptive statistics, visualizing layer dependencies, and comparing findings between the Netherlands and the UK. continue reading...

Digital Interaction Patterns in Climate Games

Lily Chen
, 
Karel KroezeKarel Kroeze
, 
Chia-Yu Wang
, 
and 
Hannie Gijlers
This research uses advanced social network analysis tools to explore how students converse in collaborative games about climate change. By analyzing their communication patterns, we aim to understand how to learn and collaborate effectively within a gaming context. continue reading...

Using machine learning to predict volunteer acceptance rates.

Derya Demirtas
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Anna MachensAnna Machens
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Karel KroezeKarel Kroeze
, 
Robin Buter
, 
and 
Tom Kooy
Out of hospital cardiac arrests (OHCA) are a leading cause of death. In the Netherlands, an innovative app alerts registered volunteers when an OHCA occurs nearby, and dispatches them either to the victim for CPR, or to an automated external defibrillator (AED) and then to the victim. Strategic location of AEDs with respect to both OHCA victims and volunteers is vital to decrease response time. The aim of this project is to predict the response rate of volunteers given the available volunteer and alert data. Modelling this acceptance behaviour will enable more realistic assumptions on availability and number of volunteers in the AED deployment problem. continue reading...

ELSA: Exploring new frontiers in research on the governance of connected and automated vehicles

Le Anh Long
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Dasom Lee
, 
Anna MachensAnna Machens
, 
and 
Karel KroezeKarel Kroeze

The race is on to develop smart and sustainable solutions to today’s most pressing challenges. Congestion, air pollution, rising energy costs, and public safety are just a few of the challenges developers of connected and automated vehicles (CAVs) claim to address. CAVs have captured the imagination of a whole host of stakeholders and sparked a new “gold rush” in the automotive industry. continue reading...

All projects