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Daniel Aloise
M.Sc. (PUC-Rio, Brésil) et un Ph.D. (Poly)

Research interests and affiliations

Research interests
  • Data Science
  • Big Data
  • Optimization
  • Mathematical Programming
Expertise type(s) (NSERC subjects)
  • 1601 Operations research and management science
  • 2510 Adaptive, learning and evolutionary systems
  • 2713 Algorithms
  • 2715 Optimization


Recent publications
Journal article
Rocha, C., Pessoa, B.J.S., Aloise, D. & Cabral, L.A. (2022). An efficient implementation of a VNS heuristic for the weighted fair sequences problem. International Transactions in Operational Research, 16 pages. Retrieved from
Journal article
Kohyarnejadfard, I., Aloise, D., Azhari, S.V. & Dagenais, M.R. (2022). Anomaly detection in microservice environments using distributed tracing data analysis and NLP. Journal of Cloud Computing, 11(1), 16 pages. Retrieved from
Conference paper
Rodrigues, I.M., Aloise, D. & Fernandes, E.R. (2022). FaST: A linear time stack trace alignment heuristic for crash report deduplication. Paper presented at the Mining Software Repositories Conference (MSR 2022), Pittsburgh, PA, USA (pp. 549-560). Retrieved from
Journal article
Costa, L.R., Aloise, D., Gianoli, L.G. & Lodi, A. (2022). Heuristics for optimizing 3D mapping missions over swarm-powered ad-hoc clouds. Journal of Heuristics, 28(4), 539-582. Retrieved from

Supervision at Polytechnique


  • Ph.D. Thesis (5)

  • Master's Thesis (9)

    • Courtade, E. (2022). Importance des variables et régressions statistiques imitant l'heuristique de branchement fort dans un problème de rotation d'équipages (Master's Thesis, Polytechnique Montréal). Retrieved from
    • Pereira, P. (2022). Imitation du branchement fort pour les problèmes de rotations d'équipage (Master's Thesis, Polytechnique Montréal). Retrieved from
    • Bouchard, I. (2021). Building Damage Assessment After a Natural Disaster in Emergency Contexts: A Deep Learning Approach (Master's Thesis, Polytechnique Montréal). Retrieved from
    • Ton, K. (2021). Using a Diversity Criterion to Select Training Sets for Machine Learning Models (Master's Thesis, Polytechnique Montréal). Retrieved from
    • Haouas, M.N. (2020). Résolution exacte du problème de partitionnement de données avec minimisation de variance sous contraintes de cardinalité par programmation par contraintes (Master's Thesis, Polytechnique Montréal). Retrieved from
    • Heutte, N. (2020). A Divide-and-Conquer Approach to Employee Scheduling (Master's Thesis, Polytechnique Montréal). Retrieved from
    • Moins, T. (2020). Modèle hybride combinant réseau de neurones convolutifs et modèle basé sur le choix pour la recommandation de sièges (Master's Thesis, Polytechnique Montréal). Retrieved from
    • Boucaud, L. (2019). Mécanismes d'attention pour les modèles convolutifs dans le cadre de la prédiction de trajectoires (Master's Thesis, Polytechnique Montréal). Retrieved from
    • Hulot, P. (2018). Towards Station-Level Demand Prediction for Effective Rebalancing in Bike-Sharing Systems (Master's Thesis, École Polytechnique de Montréal). Retrieved from

News about Daniel Aloise

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