Machine Learning Theory

The amount and complexity of available data is steadily increasing. To make use of this wealth of information, computing systems are needed that turn the data into knowledge. 

Machine learning is about developing the required algorithms and software systems that automatically analyse data for making predictions, categorizations, and recommendations. Machine learning algorithms are already an integral part of today's computing systems – for example in search engines, recommender systems, or biometrical applications – and have reached superhuman performance in some domains. DIKU's research pushes the boundaries and aims at more robust, more efficient, and more widely applicable machine learning techniques.

Machine learning at DIKU

Machine learning is a branch of computer science and applied statistics covering algorithms that improve their performance at a given task based on sample data or experience. The machine learning research at DIKU, the Department of Computer Science at the University of Copenhagen, is concerned with the design and analysis of adaptive systems for pattern recognition and behaviour generation.








Name Title Phone E-mail
Gieseke, Fabian Cristian Associate professor   E-mail
Igel, Christian Professor +45 353-35674 E-mail
Krause, Oswin Assistant professor   E-mail
Seldin, Yevgeny Professor +45 30 45 00 82 E-mail


Christian IgelChristian Igel, Professor, Dr. habil.

University of Copenhagen
Sigurdsgade 41
2200 København N
Office: -
Phone: (+45) 21849673