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. As of July 2021, I joined, as associate editor, the editorial board of Soft Computing.
I am an applied mathematician and a computer scientist.
My research interests focus on optimization, discrete mathematics, and operations research. I am particularly interested in the mathematical and computational foundations of discrete optimization as well as in both the geometric approach (polyhedral combinatorics, convex geometry, cutting plane algorithms, and branch&cut methods) and in the algebraic approach (matroid and majorization theory and, more in general, optimization over partial ordered sets) to combinatorial optimization problems. Specific optimization problems I have worked on include: linear, nonlinear and uncertain network design problems, Steiner tree problems, coloring and covering problems, partitioning over particular classes of graphs, routing problems, (generalized versions of) the traveling salesman and the quadratic assignment problems, and nonlinear inverse problems.
I am deeply interested in solving optimization problems arising from practical applications. Hence, I often collaborate with scientists from other disciplines (e.g., biologists, medical doctors, engineers) to mathematically model and solve challenging problems arising from their domain of expertise. The theoretical analysis of such models and the need to solve them as efficiently as possible constitute a continuous source of inspiration for my research that spurs me to investigate the use of large scale optimization techniques, high performance computing, and massively parallel search algorithms to tackle and solve them as fast as possible. So far, I have contributed to the following application areas: mathematics of evolution and computational phylogenetics, bioinformatics, machine learning, computer science, supply chain logistics, and telecommunications.
My research activities have been supported by the Belgian National Fund for Scientific Research, the Louvain Foundation, the U.S. National Institutes of Health, the Belgian American Educational Foundation (BAEF), the European Union COST Action, and the Marie Curie Fellowship.
Selected & Recent Publications
- D. Catanzaro, R. Pesenti, and L. Wolsey. On the Balanced Minimum Evolution Polytope. Discrete Optimization, accepted, 2020.
- D. Catanzaro, M. Frohn, and R. Pesenti. An information theory perspective on the Balanced Minimum Evolution Problem. Operations Research Letters, 48(3): 362-367, 2020.
- D. Catanzaro and R. Pesenti. Enumerating Vertices of the Balanced Minimum Evolution Polytope. Computers and Operations Research, 109, 209-217, 2019.
- 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.
- D. Catanzaro, S. E. Shackney, A. A. Schäffer, and R. Schwartz. Classifying the progression of Ductal Carcinoma from single-cell sampled data via integer linear programming: A case study. IEEE/ACM Transactions in Computational Biology and Bioinformatics, 13(4):643–655, 2016.
- D. Catanzaro, R. Aringhieri, M. Di Summa, and R. Pesenti. A branch-price-and-cut algorithm for the minimum evolution problem. European Journal of Operational Research, 244(3), 753–765, 2015.
- D. Catanzaro, M. Labbé, and L. E. N. Gouveia. Improved integer linear programming formulations for the job sequencing and tool switching problem. European Journal of Operational Research, 244(3), 766–777, 2015.
- D. Catanzaro, M. Labbé, R. Pesenti, and J. J. Salazar-González. The balanced minimum evolution problem. INFORMS Journal on Computing, 24(2), 276-294, 2012.
- D. Catanzaro, A. Godi, and M. Labbé. A class representative model for pure parsimony haplotyping. INFORMS Journal on Computing 22(2), 195–209, 2010.