Machine Learning

Our world is become ever-more data-driven. The data we collect has the potential to improve decision making throughout all aspects of society, ranging from disease treatment to improvements of logistical processes or traffic flows. For existing machine learning techniques, it’s important to make an impact on real-world systems - such as improvements to data access, use, quality, labelling, sensitivity, security, and prediction. TU Delft is working to contribute towards making machine learning techniques more effective and easier to use, so they have a positive impact on everyone’s quality of life. 

Fundamental & applied

Machine learning has been one of the most impactful paradigms in AI in recent years, so it isn’t surprising that it has found a place in almost every discipline studied at TU Delft. In that sense, we can classify two types of research: ‘IN’ machine learning research (focused on fundamental machine learning techniques) and ‘WITH’ machine learning research (applying and extending existing techniques). By combining fundamental and applied machine learning, we can push boundaries. This is where innovation and applications meet, and where the magic happens!

We are proud to be part of ELLIS, the European network of excellence in the area of machine learning and AI. Our ELLIS Delft unit brings together much of our ‘IN’ machine learning research. It focuses on using learning techniques as a key enabling technology to deal with complex tasks, and making intelligent systems adapt to their environment, including social circumstances.

Research areas

Application areas

As a technical university, Delft’s research explores not only fundamental techniques but also their impact on cutting-edge applications. Within our machine learning research, we also cover our other AI focus themes.

Below are some labs related to machine learning:

Projects

More information & contact

Scientific contact points

Valorisation & Community

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