Foundations of Learning Systems Research

Machine learning is expected to play a key role in future Army autonomous systems, both virtual and robotic. This research opportunity at the U.S. Army Research Laboratory (ARL) emphasizes mathematical development of new machine learning algorithms, with a particular emphasis on kernel and Bayesian methods, and their co-development with deep signal representations such as auto-encoders or wavelet scattering transforms. These will be coupled with adaptive control (iterative learning control), reinforcement learning, and hierarchical scenario-based decision systems such as random forests. The Computational and Information Sciences Directorate (CISD) conducts research in a variety of disciplines relevant to achieving and implementing the digital battlefield, with problems addressing the sensing, distribution, analysis, and display of information in the modern battle space. This position is part of the Army Research Laboratory Research Associateship Program (ARL-RAP), designed to significantly increase the involvement of creative and highly trained scientists and engineers from academia and industry in scientific and technical areas of interest and relevance to the Army.