The Machine Learning & Neural Computing department shares an interest in the development of theories, algorithms and models that contribute to the science and engineering of naturally and artificially intelligent systems. This mission is pursued through two complementary focus areas.
Focus 1: Machine Learning
The department develops machine learning theory and methods grounded in applied mathematics, statistical physics, and computer science. Guided by real-world constraints, this research advances sustainable applications in science, industry, and society, contributing to the objectives of the European ELLIS excellence network in machine learning.
Focus 2: Neural Computing
The department advances the theoretical and mechanistic understanding of neural information processing mechanisms through modeling, simulation and manipulation of neural systems. Grounded in computational neuroscience, biophysics, and theoretical biology, this research advances neurotechnology, neuromorphic computing, and neurorobotics, and thus contributes to the research focus of the Donders Institute.
Both focus areas are mutually informative: machine learning provides insights into natural intelligence, while neural computation inspires novel machine learning methods. These theories are evaluated in real-world applications using computational platforms ranging from large-scale clusters and edge devices to neuromorphic and unconventional computing systems. Fundamental research is further informed by real-world constraints, with several researchers working at the intersection of both research lines.
Impact
Our research generates impact by advancing machine learning, deepening the understanding of information processing in biological systems, enabling breakthroughs in disciplines such as neurotechnology and neuromorphic computing, and improving intelligent systems. In line with the UN Sustainable Development Goals and the European Lighthouse on Sustainable AI, we develop sustainable AI that is performant, efficient, robust, safe, and explainable, with applications in neurotechnology, healthcare, robotics, and smart industry.
Education
The MLNC department provides in-depth training for AI students related to the two focus areas of the department. In the Bachelor's programme we contribute to the disciplines Computation and Neuroscience. In the Master's programme we coordinate the MLNC specialization Machine Learning and Neural Computing, in line with the research of the department.
Scientific network
The department is connected to European networks such as the ELLIS network of excellence, NeurotechEU, the European lighthouse on AI for sustainability and EuroDBS, as well as to Dutch networks such as the Innovation Centre of AI (ICAI) and NeuroTechNL.