Data Science Grant Q4 2023 - Winners

January 3, 2024

The BDSi Data Science Grants are decided twice yearly, generally at the end of Q2 and Q4. The grants are open for all BMS faculty that are looking to include data science in their research or education. We take on a limited number of high-impact projects, often creating a proof-of-concept for further research and grant applications.

From the proposals for Q42023, we selected 4 very impactful and innovative proposals that we are looking forward to support. Two with full support in Q1 2024 and two which will be started as a limited pilot with potential extensions into Q3. We’re excited about starting these new projects, and look forward to collaborating with the great teams behind them.

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Winning proposals

It was our pleasure to inform the winning applicants just before the holidays, and we are now ready to announce the results to the BDSi community. So, without further ado, here are the winning proposals.

Using machine learning to predict volunteer acceptance rates.

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.

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Digital Interaction Patterns in Climate Games

Social network and discource analysis of learners’ communication patterns in a collaborative game on climate change.

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.

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Digital Open Strategic Autonomy

Comparative analysis of governance surrounding strategic autonomy in the United Kingdom, the Netherlands, and the European Union.

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.

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

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.

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