Machine Learning
Machine Learning is the sub-discipline of Computer Science that powers dramatic progress in, among other things, Data Science and Artificial Intelligence in recent years. In a nutshell, machine learning enables computers to detect statistical regularities in potentially very large volumes of observed data, to derive generalizations and make predictions for previously unseen inputs.
The Section comprises five specialized research groups, with renowned expertise in bio-medical informatics, image and signal processing, language technologies, nanoelectronics, and robotics. There are around one hundred researchers and engineers working in the division (in early 2020).
Subunits
Biomedical Informatics (BMI)
The BMI group focuses on computational and statistical applications in the medical and biological sciences. Combined, the two research areas bioinformatics and statistical genomics cover most of our activities.
Digital Signal Processing and Image Analysis (DSB)
Main research focus on signal processing, image analysis, and machine learning for applications in medical imaging, sonar, seismics, and remote sensing.
Language Technology Group (LTG)
Language Technology comprises theoretical and applied Informatics that seeks to enable computers to ‘make sense’ of human language.
Nanoelectronics (NANO)
The group specializes in innovative ASIC (application specific integrated circuit) design and testing in advanced deep sub-micrometer CMOS (complementary metal oxide silicon) technologies, including electronic prototype PCB assembly.
Robotics and Intelligent Systems (ROBIN)
The goal is to contribute to the development of ever more intelligent systems. This can be systems that in specific tasks or environments can assist or replace human judgment, or it can be systems that can accomplish tasks we would like to automate.
