Artificial Intelligence & Machine Learning

The modern world is full of artificial, abstract environments that challenge our natural intelligence. The goal of our research is to develop Artificial Intelligence that gives people the capability to master these challenges, ranging from formal methods for automated reasoning to interaction techniques that stimulate truthful elicitation of preferences and opinions. Another aspect is characterizing human intelligence and cognitive science, with applications in human-computer interaction and computer animation.

Machine Learning aims to automate the statistical analysis of large complex datasets by adaptive computing. A core strategy to meet growing demands of science and applications, it provides a data-driven basis for automated decision making and probabilistic reasoning. Machine learning applications at EPFL range from natural language and image processing to scientific imaging as well as computational neuroscience.

Affiliated People
Antoine Bosselut
Antoine Bosselut

Tenure Track Assistant Professor

[email protected] INR 234
Maria Brbic
Maria Brbic

Tenure Track Assistant Professor

[email protected] INJ 331
Nicolas Flammarion
Nicolas Flammarion

Tenure Track Assistant Professor

[email protected] INJ 336
Martin Jaggi
Martin Jaggi

Tenure Track Assistant Professor

[email protected] INJ 341
Frédéric Kaplan
Frédéric Kaplan

Tenure Track Assistant Professor

[email protected] GC D2 386
Tanja Käser
Tanja Käser

Tenure Track Assistant Professor

[email protected] INF 234
Robert West
Robert West

Tenure Track Assistant Professor

[email protected] INN 310
Amir Zamir
Amir Zamir

Tenure Track Assistant Professor

[email protected] INJ 230