Daniele Catanzaro

Daniele Catanzaro is an Italian mathematician and computer scientist working in the field of discrete optimization and theoretical computer science. He is Associate Professor of Discrete Optimization at the Center for Operations Research and Econometrics (CORE) of the Université Catholique de Louvain and is mostly known for his contributions to the combinatorics and optimization aspects of phylogenetics.

Daniele Catanzaro
NationalityItalian
Alma materUniversité Libre de Bruxelles
Scientific career
FieldsCombinatorial Optimization
Integer Programming
Theoretical Computer Science
Phylogenetics
InstitutionsUniversité Catholique de Louvain
Rijksuniversiteit Groningen

Education and Career

Daniele Catanzaro graduated Summa cum Laude in Computer Science Engineering at the University of Palermo, Italy (2003). He was awarded the Ph.D. in Computer Science from the Université Libre de Bruxelles (2008), for his studies in discrete optimization, network theory, and combinatorics of phylogenetics.

As a Chargé de Recherches of the Belgian National Fund for Scientific Research (2009-2013) he 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 (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).

Prior to joining the Université Catholique de Louvain in 2014, he was appointed Assistant Professor of Discrete Optimization at the Faculty of Economics and Business of the Rijksuniversiteit Groningen (2013-2014).

Main Work

Catanzaro's work involves several aspects of combinatorial optimization and integer programming as well as advanced theory on models and algorithms for molecular phylogenetics and evolution. In particular, he contributed to the area of distance-matrix methods by setting the ground for the analysis of the polyhedral combinatorics of both the Balanced Minimum Evolution criterion[1][2][3] and the Minimum Evolution criterion under linear programming[4][5], first introduced in the literature by Beyer et al.[6] and Waterman et al. [7].

He has also contributed to characterize the fundamental equalities describing collections of path-length sequences encoding unrooted binary trees as well as the connections relating minimum evolution-based models to Information Theory[8]. He also proposed a new interpretation of the minimum length phylogeny under Pauplin' BME branch length estimation model as (Pareto optimal) consensus tree between concurrent minimum entropy processes encoded by a forest of n phylogenies rooted on the n analyzed taxa. This information theory-based interpretation is conjectured to be shared by all distance methods in phylogenetics.

References
  1. Desper R, Gascuel O (March 2004). "Theoretical foundation of the balanced minimum evolution method of phylogenetic inference and its relationship to weighted least-squares tree fitting". Molecular Biology and Evolution. 21 (3): 587–98. doi:10.1093/molbev/msh049. PMID 14694080.
  2. Catanzaro D, Pesenti R, Wolsey L (2020). "On the Balanced Minimum Evolution Polytope". Discrete Optimization. 36: 1–33.
  3. Catanzaro D, Labbé M, Pesenti R, Salazar-González JJ (2012). "The balanced minimum evolution problem". INFORMS Journal on Computing. 24 (2): 276–294.
  4. Catanzaro D, Labbé M, Pesenti R, Salazar-González JJ (2009). "Mathematical models to reconstruct phylogenetic trees under the minimum evolution criterion". Networks. 53 (2): 126–140.
  5. Catanzaro D, Aringhieri R, Di Summa M, Pesenti R (2015). "A branch-price-and-cut algorithm for the minimum evolution problem". European Journal of Operational Research. 244 (3): 753–765.
  6. Beyer WA, Stein M, Smith T, Ulam S (1974). "A molecular sequence metric and evolutionary trees". Mathematical Biosciences. 19: 9–25.
  7. Waterman MS, Smith TF, Singh M, Beyer WA (1977). "Additive evolutionary trees". Journal of Theoretical Biology. 64: 199–213.
  8. Catanzaro D, Frohn M, Pesenti R (2020). "An information theory perspective on the Balanced Minimum Evolution Problem". Operations Research Letters. 48 (3): 362–367.
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