Climate change is affecting extreme weather – we identify how and when society is at risk
Seasonal to sub-seasonal (S2S) predictability could provide societies with valuable information on weather-related risk, allowing decision-makers to initiate early warning action plans and to optimize resource management. Using Artificial Intelligence (AI), we are developing a rigorous data-driven framework that enables automatic detection of interpretable physical drivers on S2S timescales. Combining expert knowledge, causal inference and a variety of machine learning techniques, our tool has worked for science. Now we aim for societal impact by making predictions for stakeholders (e.g. NGO’s).
Eye-opening insights Consumers make about 95% of their decisions without conscious awareness. Attention Check objectively maps out their behavior by using biometrics such as eye tracking, skin conductance, and brain activity. In this way we tap into the non-conscious processes that truly underlie human behavior. In addition we run large N (e.g. 1000) online psychological […]
Calibration-free webcam eye-tracker based on deep learning DeepEye records eye movements using a regular webcam and cutting-edge AI algorithms. Eye-tracking is widely used to understand how humans process information. This information provides solutions for scientific research, marketing & advertising, building human-computer interfaces, and diagnosing mental disorders. DeepEye is designed to make eye-tracking available to everyone […]
We protect unique underground ecosystems in the face of rapid environmental change Beneath our feet, fungi complex underground networks of that regulate the earth’s climate and ecosystems. These hidden networks power the world’s soil, and act as a huge sink for atmospheric carbon. But these biomes are being rapidly destroyed: fires, pollutions, deforestation are killing […]