Daniele Catanzaro

Professor of Discrete Optimization • Center for Operations Research & Econometrics • Université Catholique de Louvain

Short Bio

I am a Professor of Discrete Optimization at the Center for Operations Research and Econometrics (CORE) of the Université Catholique de Louvain.

Prior to joining UCL in 2014, I was appointed Assistant Professor at the Faculty of Economics and Business of the Rijksuniversiteit Groningen (2013-2014), and Chargé de Recherches at the Belgian National Research Council (2009-2013).

I graduated Summa cum Laude in Computer Science Engineering at the Universitá degli Studi di Palermo, Italy (2003). I was awarded the Ph.D. in Computer Science by the Université Libre de Bruxelles (2008), for my studies in discrete optimization, network design and computational phylogenetics.

During my academic career, I visited a number of universities and research institutions including, among others, the Department of Statistics and Operations Research of the University of La Laguna (2009), the Tepper School of Business of Carnegie Mellon University (2010-2011), the Department of Computer Science of Reykjavik University (2010), the Department of Mathematics and Computer Science of the Freie Universität Berlin (2010), the Department of Genetics and Evolution of the University of Geneva (2010), the Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier LIRMM-CNRS (2012), and the Department of Biological Sciences of Carnegie Mellon University (2012).

More recently, I was an Invited Professor at the Department of Management of the University Ca Foscari of Venice, Italy (2018), and Senior Research Leader at the Luxembourg Institute of Socio Economic Research (2019-2020).

As of May 2021, I joined the Advisory Board of the International Journal Mathematical Methods in Economics and Finance.

Extended Curriculum Vitae

Erdős number: 3

Mathematical Genealogy

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.

Selected & Recent Publications

  • D. Catanzaro, S. Chaplick, S. Felsner, B. V. Halldórsson, M. M. Halldórsson, T. Hixon, and J. Stacho. Max point-tolerance graphs. Discrete Applied Mathematics, 216(1): 84-97, 2017. 

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