Irene Garcia-Marti

PhD Data Scientist

Dutch Met Office (KNMI)


PhD Data Scientist with a background in Geoinformatics (MSc) and Computer Science (BSc) keen on solving complex scientific problems through the spatio-temporal analysis of GIS data collections. Currently, I have six years of specialization in data analysis and machine learning in the fields of climate services and environmental modelling. During this period, citizen science observations have been at the core of my analytical activities, this is why I acquired a broad experience at integrating volunteered observations with heterogeneous geodata sources and modelling them with data-driven methods. In addition to my analytical skills, I am technically versatile, this is why I am comfortable at working with spatial databases, web services, sensor webs or performing GIS analyses. Having good communication skills and a good understanding of computers and algorithms, makes me an effective presenter, capable of conveying complex results to all audiences.


  • Machine learning
  • Climate services research
  • Environmental Modelling
  • Citizen Science


  • PhD in Geospatial Analytics, 2019

    University of Twente

  • MSc in Geospatial Technologies, 2011

    University Jaume I / University of Muenster

  • BSc in Computer Science Engineering, 2009

    University Jaume I


Machine Learning


Spatial Analysis










Recent Posts

Enhanced capability to monitor drought using citizen weather stations

Last week I presented some preliminary results of a project in a hydro-meteorology session of the European Geophysical Union (vEGU21) …

Extract rainfall data from radar files in stereographic projection given lat/lon coordinates

When you are a kid you often stumble upon these stories of pirates seeking a hidden chest in a remote island. The pirates embark on an …

Checking tick activity in your phone

In 2016, we developed a model capable of predicting daily tick activity in Dutch forests. This model used observations collected by a …

Assessing the quality of volunteered weather observations

Weather observations are typically collected by professional devices siting in open spaces. These weather stations provide very precise …

Explaining My PhD Research

Well, another PhD journey comes to an end. These have been fruitful and intense years of research and fast-paced learning. The PhD …


In this section you can find a brief and not-very-technical description of the projects I have worked in.


A quality-controlled data service of volunteered weather observations

In 2011, the UK Met Office launched a citizen science project intended to collect data from citizen weather stations (CWS) and, to …

Detecting probability of ice formation on overhead lines of the Dutch railway network

Ice formation along the overhead lines is a potential source of infrastructure failure and transportation disruption. Modelling ice …

Gridding station-based wind observations

The European Climate Assessment & Dataset (ECA&D) collects high-quality observational datasets provided by 60+ participant …

Identifying risky locations for road accidents due to crosswind

Crosswind is a potential source of road accidents, especially for unloaded trucks. We joined forces with colleagues from the ILT and …

Statistics of extreme rainfall events over the road network

Short-duration extreme rainfall events have the potential of causing problems with a high-impact for the road infrastructure and its …


Drop me an e-mail if you have any question