Daniele Catanzaro

Research

I am an applied mathematician and a computer scientist.

My research interests involve the mathematical foundations of discrete optimization as well as the development of models, methods and algorithms to solve practical optimization problems arising from (but not limited to) computer science, logistics, supply chain, telecommunications, transportations, machine learning and medical bioinformatics.

In particular, my interests cover the following areas:

Discrete Optimization: in particular, integer linear and nonlinear programming, polyhedral combinatorics, computational complexity, submodularity, impact of ordering in discrete optimization; optimization on lattices (partial ordered sets), majorization, network design, optimization under uncertainty, design and development of large scale exact and approximate solution algorithms for real life problems.

Optimization Methods for Machine Learning: including clustering, regression, and support vector machines.

Algorithms, Information Theory & HPC: in particular, massively parallel search algorithms, high performance computing, specific topics in data compression and encryption, information theory.

Mathematics of Evolution, Computational Phylogenetics, and Medical Bioinformatics: in particular, distance methods in phylogenetics, design of ad hoc estimation models for molecular evolution and phylogenetics, consistency analysis, combinatorics of phylogenetics, information entropy in phylogenetics, cancer phylogenetics, design of mathematical models and estimation algorithms for genome-wide association studies.