DeTaiL

Undoubtedly, we live in the era of big data. Real life data - in the biomedical field and beyond - often comes high-dimensional. Current signal processing solutions artificially segment such high-dimensional data into shorter one- or two-dimensional arrays, causing information loss by destroying correlations between these data. At the same time, advances in (biomedical) sensor and imaging technology – such as substantially larger recording durations of wearable sensor technology or the unprecedented increase in spatial and temporal resolution of the latest neuroimaging techniques – have led to ever increasing data sets. Tensors (multi-dimensional arrays) are the data structure of choice in artificial intelligence research to exploit the full potential of these data in a timely manner.

Within the DeTAIL Lab, we focus on both the development of novel low-rank tensor methods and their application for biomedical signal processing, thereby enabling a much faster, and therefore more energy-sustainable, training of AI models from large datasets without any loss of accuracy.

The DeTAIL Lab is part of the TU Delft AI Labs programme.