SSH/LSM Louvain School of Management (LSM)
SSH/IDAM Louvain Institute of Data Analysis and Modeling in economics and statistics (LIDAM)
SSH/IDAM/CORE Center for operations research and econometrics (CORE)
Short Bio
I am Professor of Discrete Optimization and Operations Research, currently serving as President of the Center for Operations Research and Econometrics (CORE) of the Université Catholique de Louvain.
I graduated summa cum laude in Computer Science Engineering at the University of Palermo, Italy, in 2003. In 2008, I was awarded a Ph.D. in Computer Science from the Université Libre de Bruxelles for my research in discrete optimization, network design, and computational phylogenetics, conducted at the Computer Science Department, the Institute of Biology and Molecular Medicine (IBMM), and the Hospital Erasme of the same university. Before joining the Université Catholique de Louvain in 2014, I was a Chargé de Recherches of the Belgian National Fund for Scientific Research (2009-2013), Visiting Scholar at the Tepper School of Business and the Computational Biology Department of Carnegie Mellon University(2010-2012), and Assistant Professor of Discrete Optimization at the Faculty of Economics and Business of the Rijksuniversiteit Groningen (2013-2014). More recently, I have been invited as a Visiting Professor at the Department of Management at the University Ca’ Foscari of Venice, Italy, in 2018 and again in 2024.
I recently served as Vice-Chair for the ERC Horizon calls HORIZON-MSCA-2025-PF-01 and as Panel Member for the Canadian NSERC/CRSNG (calls 2022-2025).
Research
I am a computer scientist and an applied mathematician. My research focuses on the foundational theory and algorithmic development for combinatorial optimization and integer programming. I am particularly interested in advancing both exact and approximate methods for optimization over integers, aiming to deepen theoretical insights while designing effective and scalable algorithms for NP-hard problems arising in real-world applications. My work has addressed a range of topics so far, including linear, nonlinear, and uncertain network design; coloring, covering, and partitioning; routing; (versions of) the traveling salesman and the quadratic assignment problems; and the optimization of exponential functions over discrete domains (e.g., entropy-based models, optimal embedding trees). I have been interested in the applications of discrete optimization to bioinformatics, with particular focus on tumorigenesis and genome-wide association studies. In recent years, my research has focused intensively on the combinatorial and optimization aspects of phylogenetics, contributing to the development of distance-based methods, specifically minimum evolution and balanced minimum evolution.
Throughout my career, my research activities have been supported by several competitive funding programs, including the European Marie Curie Fellowship Program (grant HPRN-CT-1999-00106); the Belgian National Fund for Scientific Research (FNRS) , through the Aspirant and Chargé de Recherches mandates, the CDR grant S/25-MCF/OL J.0026.17, and PDR grant 2021-40007831; the Fonds Brachet (IBMM Prize 2007); the Louvain Foundation (grant Coalesces ); the U.S. National Institutes of Health (NIH) (grants 1R01CA140214 and 1R01AI076318); and the Belgian American Educational Foundation (BAEF) , through the Honorary Fellowship 2010–2011 for biomedical engineering research in the United States.
Research Keywords: combinatorial optimization, integer programming, polyhedral combinatorics, decomposition algorithms, branch-&-cut, branch-price-&-cut, computational complexity, routing, network design, coloring, covering, partitioning, location, games on graphs, constructive characterizations, high performance computing, massive parallel enumeration, enumeration of trees, lattices of unrooted binary trees, tree coding, Huffman coding, information entropy, entropy encoding, cross-entropy encoding, Kullback–Leibler divergence, encryption schemes, tree metric, submodular functions, convexity, Schur convexity, mathematics of evolution, phylogenetics, phylodynamics, mathematical modeling of tumor progression, genome-wide association studies, medical bioinformatics, deep reinforcement learning, hierarchical clustering, optimization aspects of machine learning.
Personal webpage: https://danielecatanzaro.github.io
Adresse postale
CORE - CV9L1.03.01
Voie du Roman Pays 34
1348 Louvain-la-Neuve
Catanzaro, Daniele ; Dehaybe, Henri ; Pesenti, Raffaele. New heuristics for phylogeny estimation under the balanced minimum evolution criterion. In: Bioinformatics (Oxford, England), Vol. 41, no.7 (2025). doi:10.1093/bioinformatics/btaf361 (Accepté/Sous presse).
Catanzaro, Daniele ; Pesenti, Raffaele ; Sapucaia Barboza, Allan ; Wolsey, Laurence. Optimizing over Path-Length Matrices of Unrooted Binary Trees. In: Mathematical Programming, (2025) (Accepté/Sous presse).
Legrand, Emma ; Coppé, Vianney ; Catanzaro, Daniele ; Schaus, Pierre. A Dynamic Programming Approach for the Job Sequencing and Tool Switching Problem. Integration of Constraint Programming, Artificial Intelligence, and Operations Research (Melbourne, du 10/11/2025 au 13/11/2025). In: Lecture Notes in Computer Science : Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Springer Nature Switzerland, 2025. 9783031959752, p. 70-85. doi:10.1007/978-3-031-95976-9_5.
Catanzaro, Daniele ; Pesenti, Raffaele ; Pisanu, Francesco. A Note on the Approximability of the Balanced Minimum Evolution Problem (LIDAM Discussion Paper CORE; 2025/21), 2025. 13 p.
Dehaybe, Henri ; Catanzaro, Daniele ; Chevalier, Philippe. Deep Reinforcement Learning for Inventory Optimization with Non-Stationary Uncertain Demand. In: European Journal of Operational Research, (2024). doi:10.1016/j.ejor.2023.10.007.
Catanzaro, Daniele ; Pesenti, Raffaele ; Ronco, Roberto. Characterizing path-length matrices of unrooted binary trees (LIDAM Discussion Paper CORE; 2024/28), 2024. 27 p.
Catanzaro, Daniele ; Pesenti, Raffaele ; Sapucaia Barboza, Allan ; Wolsey, Laurence. Optimizing over Path-Length Matrices of Unrooted Binary Trees (LIDAM Discussion Paper CORE; 2023/20), 2024. 35 p.
Catanzaro, Daniele ; Frohn, Martin ; Gascuel, Olivier ; Pesenti, Raffaele. A Massively Parallel Branch-&-Bound Algorithm for the Balanced Minimum Evolution Problem. In: Computers & Operations Research, Vol. 158, p. 106308 (2023). doi:10.1016/j.cor.2023.106308.
Gasparin, Andrea ; Camerota Verdù, Federico Julian ; Catanzaro, Daniele ; Castelli, Lorenzo. An evolution strategy approach for the balanced minimum evolution problem. In: Bioinformatics, Vol. 39, no. 11 (2023), p. btad660 (2023). doi:10.1093/bioinformatics/btad660.
Catanzaro, Daniele ; Pesenti, Raffaele ; Ronco, Roberto. Job scheduling under Time-of-Use energy tariffs for sustainable manufacturing: a survey. In: European Journal of Operational Research, Vol. 308, no.3, p. 1091-1109 (2023). doi:10.1016/j.ejor.2023.01.029.
Catanzaro, Daniele ; Frohn, Martin ; Gascuel, Olivier ; Pesenti, Raffaele. A Massively Parallel Exact Solution Algorithm for the Balanced Minimum Evolution Problem (LIDAM Discussion Paper CORE; 2023/01), 2023. 33 p.
Gasparin, Andrea ; Camerota Verdù, Federico Julian ; Catanzaro, Daniele. An evolution strategy approach for the Balanced Minimum Evolution Problem (LIDAM Discussion Paper CORE; 2023/21), 2023. 7 p.
Catanzaro, Daniele ; Frohn, Martin ; Gascuel, Olivier ; Pesenti, Raffaele. A tutorial on the balanced minimum evolution problem. In: European Journal of Operational Research, Vol. 300, no. 1, p. 1-19 (2022). doi:10.1016/j.ejor.2021.08.004.
Catanzaro, Daniele ; Coniglio, Stefano ; Furini, Fabio. On the exact separation of cover inequalities of maximum-depth. In: Optimization Letters, Vol. 16, no. 2, p. 449-469 (2022). doi:10.1007/s11590-021-01741-0.
Catanzaro, Daniele ; Pesenti, Raffaele ; Ronco, Roberto. A new fast and accurate heuristic for the Automatic Scene Detection Problem. In: Computers & Operations Research, Vol. 136, p. 105495 (2021). doi:10.1016/j.cor.2021.105495 (Accepté/Sous presse).
Catanzaro, Daniele ; Frohn, Martin ; Pesenti, Raffaele. A Massively Parallel Exact Solution Algorithm for the Balanced Minimum Evolution Problem (LIDAM Discussion Paper CORE; 2021/23), 2021. 41 p.
Catanzaro, Daniele ; Pesenti, Raffaele ; Ronco, Roberto. A New Fast and Accurate Heuristic for the Automatic Scene Detection Problem (LIDAM Discussion Paper CORE; 2021/22), 2021. 18 p.
Catanzaro, Daniele ; Frohn, Martin ; Gascuel, Olivier ; Pesenti, Raffaele. A Tutorial on the Balanced Minimum Evolution Problem (LIDAM Discussion Paper CORE; 2021/27), 2021. 31 p.
Catanzaro, Daniele ; Pesenti, Raffaele ; Ronco, Roberto. Job Scheduling under Time-of-Use Energy Tariffs for Sustainable Manufacturing: A Survey (LIDAM Discussion Paper CORE; 2021/19), 2021.
Catanzaro, Daniele ; Frohn, Martin ; Pesenti, Raffaele. On Numerical Stability and Statistical Consistency of the Balanced Minimum Evolution Problem (LIDAM Discussion Paper CORE; 2021/26), 2021. 5 p.
Catanzaro, Daniele ; Coniglio, Stefano ; Furini, Fabio. On the exact separation of cover inequalities of maximum-depth (LIDAM Discussion Paper CORE; 2021/18), 2021. 16 p.
Catanzaro, Daniele ; Frohn, Martin ; Pesenti, Raffaele. An information theory perspective on the balanced minimum evolution problem. In: Operations Research Letters, Vol. 48, no.3, p. 362-367 (2020). doi:10.1016/j.orl.2020.04.010.
Catanzaro, Daniele ; Pesenti, Raffaele ; Wolsey, Laurence. On the balanced minimum evolution polytope. In: Discrete Optimization, Vol. 36, p. 100570 (2020). doi:10.1016/j.disopt.2020.100570 (Accepté/Sous presse).
Luciano Porretta ; Catanzaro, Daniele ; Bjarni V. Halldórsson ; Bernard Fortz. A Branch & Price Algorithm for the Minimum Cost Clique Cover Problem in Max-Point Tolerance Graphs. In: 4OR : quarterly journal of the Belgian, French and Italian Operations Research Societies, Vol. 17, no. 1, p. 75-96 (2019). doi:10.1007/s10288-018-0377-3.
Catanzaro, Daniele ; Pesenti, Raffaele. Enumerating vertices of the balanced minimum evolution polytope. In: Computers & Operations Research, Vol. 109, p. 209-217 (2019). doi:10.1016/j.cor.2019.05.001.
Catanzaro, Daniele ; Chaplick, S. ; Felsner, S. ; Halldórsson, B.V. ; Halldórsson, M.M. ; Hixon, T. ; Stacho, J.. Max point-tolerance graphs. In: Discrete Applied Mathematics, Vol. 216, no. 1, p. 84-97 (2017). doi:10.1016/j.dam.2015.08.019.
Catanzaro, Daniele. Classifying the progression of Ductal Carcinoma from single-cell sampled data via integer linear programming: A case study. In: IEEE-ACM Transactions on Computational Biology and Bioinformatics, Vol. 13, no. 4, p. 643 (2016). doi:10.1109/TCBB.2015.2476808.
Catanzaro, Daniele ; Aringhieri, Roberto ; Di Summa, Marco ; Pesenti, Raffaele. A branch-price-and-cut algorithm for the minimum evolution problem. In: European Journal of Operational Research, Vol. 244, no. 3, p. 753-765 (2015). doi:10.1016/j.ejor.2015.02.019.
Catanzaro, Daniele ; Engelbeen, C.. An integer linear programming formulation for the minimum cardinality segmentation problem. In: Algorithms, Vol. 8, no.4, p. 999-1020 (2015). doi:10.3390/a8040999.
Catanzaro, Daniele ; Gouveia, Luis ; Labbé, Martine. Improved integer linear programming formulations for the job sequencing and tool switching problem. In: European Journal of Operational Research, Vol. 244, no.3, p. 766-777 (2015). doi:10.1016/j.ejor.2015.02.018.
Catanzaro, Daniele ; Ravi, R. ; Schwartz, R.. A mixed integer linear programming model to reconstruct phylogenies from single nucleotide polymorphism haplotypes under the maximum parsimony criterion. In: BMC Algorithms for Molecular Biology, Vol. 8, no.n.a., p. 3 (2013).
Catanzaro, Daniele ; Labbé, M. ; Halldórsson, B.V.. An integer programming formulation of the parsimonious loss of heterozygosity problem. In: IEEE-ACM Transactions on Computational Biology and Bioinformatics, Vol. 10, no.6, p. 1391-1402 (2013). doi:10.1109/TCBB.2012.138.
Catanzaro, Daniele ; Labbé, M. ; Pesenti, R.. The balanced minimum evolution problem under uncertain data. In: Discrete Applied Mathematics, Vol. 161, no.13-14, p. 1789-1804 (2013). doi:10.1016/j.dam.2013.03.012.
Catanzaro, Daniele ; Gourdin, E. ; Labbé, M. ; Özsoy, F.A.. A branch-and-cut algorithm for the partitioning-hub location-routing problem. In: Computers & Operations Research, Vol. 38, no.2, p. 539-549 (2011). doi:10.1016/j.cor.2010.07.014.
Catanzaro, Daniele ; Labbé, M. ; Porretta, L.. A class representative model for pure parsimony Haplotyping under Uncertain Data. In: PLoS One, Vol. 6, no.3, p. e17937 (2011). doi:10.1371/journal.pone.0017937.
Aringhieri, R. ; Catanzaro, Daniele ; Di Summa, M.. Optimal solutions for the balanced minimum evolution problem. In: Computers & Operations Research, Vol. 38, no.12, p. 1845-1854 (2011). doi:10.1016/j.cor.2011.02.020.
Catanzaro, Daniele ; Labbé, M. ; Salazar-Neumann, M.. Reduction approaches for robust shortest path problems. In: Computers & Operations Research, Vol. 38, no.11, p. 1610-1619 (2011). doi:10.1016/j.cor.2011.01.022.
Catanzaro, Daniele ; Labbé, Martine ; Pesenti, Raffaele ; Salazar-González, Juan-José. The Balanced Minimum Evolution Problem. In: INFORMS Journal on Computing, Vol. 24, no.2, p. 187-341 (2011). doi:10.1287/ijoc.1110.0455.
Catanzaro, Daniele. Estimating phylogenies from molecular data. In: R. Bruni, Mathematical approaches to polymer sequence analysis and related problems, 2011. 978-1-4419-6799-2. doi:10.1007/978-1-4419-6800-5.
Catanzaro, Daniele ; Andrien, Marc ; Labbé, Martine ; Toungouz-Nevessignsky, Michel. Computer-aided human leukocyte antigen association studies: a case study for psoriasis and severe alopecia areata.. In: Human immunology, Vol. 71, no.8, p. 783-8 (2010). doi:10.1016/j.humimm.2010.04.003 (Soumis).
Catanzaro, Daniele ; Labbé, Martine ; Godi, Alessandra. A class representative model for pure parsimony haplotyping. In: INFORMS Journal on Computing, Vol. 22, no.2, p. 195-209 (2009).
Catanzaro, Daniele ; Labbé, Martine ; Pesenti, Raffaele ; Salazar-González, Juan-José. Mathematical models to reconstruct phylogenetic trees under the minimum evolution criterion. In: Networks, Vol. 53, no.2, p. 126-140 (2009). doi:10.1002/net.20281.
Catanzaro, Daniele. The minimum evolution problem: Overview and classification. In: Networks, Vol. 53, no.2, p. 112-125 (2009). doi:10.1002/net.20280.
Catanzaro, Daniele ; Labbé, Martine. The pure parsimony haplotyping problem: overview and computational advances. In: International Transactions in Operational Research, Vol. 16, no. 5, p. 561-584 (2009). doi:10.1111/j.1475-3995.2009.00716.x.
Catanzaro, Daniele ; Pesenti, R. ; Milinkovitch, M.C.. An ant colony optimization algorithm for phylogenetic estimation under the minimum evolution principle. In: Evolutionary Bioinformatics, Vol. 7, no.2, p. 153-163 (2007).
Gatto, Laurent ; Catanzaro, Daniele ; Milinkovitch, Michel C. Assessing the applicability of the GTR nucleotide substitution model through simulations.. In: Evolutionary bioinformatics online, Vol. 2, p. 145-55 (2007).
Catanzaro, Daniele ; Pesenti, R. ; Milinkovitch, M.C.. A non-linear optimization procedure to estimate distances and instantaneous substitution rate matrices under the GTR model. In: Bioinformatics, Vol. 22, no.6, p. 708-715 (2006). doi:10.1093/bioinformatics/btk001.
Unités d'enseignement pour 2025
| Libellé | Code |
|---|---|
| Production and Operations management | LINGE1316 |
| Research Methods | LLSMA2002 |
| Operations, Management and Modeling | LLSMG2003 |
| Supply Chain Management | LLSMS2030 |
| Supply Chain Planning | LLSMS2034 |
| Supply Chain Management | MGEHD2223 |
| Coding Project | MINFO1302 |
| Quantitative Decision Making | MLSMM2155 |
| Optimization | MQANT1329 |