Combinatorics, spectral graph theory, quantitative linear algebra, random matrix theory, finite free probability.
Friedrich Eisenbrand’s main research interests lie in the field of discrete optimization, in particular in algorithms and complexity, integer programming, geometry of numbers, and applied optimization.
Ergodic Theory, Topological and Symbolic Dynamics, (Ergodic) Ramsey Theory, Additive Combinatorics, Combinatorial Number Theory, Multiplicative Number Theory
Fundamental limits and algorithms for data processing and machine learning. Statistics, discrete probability, learning theory, information theory, algorithms.