Daniel Aloise
M.Sc. (PUC-Rio, Brésil) et un Ph.D. (Poly)
Full Professor
Department of Computer Engineering and Software Engineering
Department of Computer Engineering and Software Engineering
Research interests and affiliations
Research interests
- Data Science
- Big Data
- Optimization
- Mathematical Programming
Affiliation(s)
Expertise type(s) (NSERC subjects)
- 1601 Operations research and management science
- 2510 Adaptive, learning and evolutionary systems
- 2713 Algorithms
- 2715 Optimization
Publications
Recent publications
Journal article
Journal article
Journal article
Journal article
Cocha, C., Pessoa, B. P. S., Aloise, D., & Cabral, L. A. (2024). An efficient implementation of a VNS heuristic for the weighted fair sequences problem. International Transactions in Operational Research, 31(3), 1720-1735.
Martins Silva, M. C., Aloise, D., & Jena, S. D. (2024). Data-driven prioritization strategies for inventory rebalancing in bike-sharing systems. Omega, 129, 103141 (15 pages).
Rastgar-Amini, F., Aloise, D., Contardo, C., & Desaulniers, G. (2024). Data Mining-Driven Shift Enumeration for Accelerating the Solution of Large-Scale Personnel Scheduling Problems. ACM Transactions on Evolutionary Learning and Optimization, 24 pages.
Liang, J., Martins Silva, M. C., Aloise, D., & Jena, S. D. (2024). Dynamic rebalancing for Bike-sharing systems under inventory interval and target predictions. EURO Journal on Transportation and Logistics, 13, 19 pages.
See all publications (72)
Supervision at Polytechnique
COMPLETED
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Ph.D. Thesis (7)
- Correia Pereira, T. (2023). Innovative Data Collection Framework for Humanitarian Logistics: A Serious Game Solution [Ph.D. thesis, Polytechnique Montréal].
- Martins Silva, M. C. (2023). Data-Driven Methods for Inventory Management in Dock-Based Bike-Sharing Systems [Ph.D. thesis, Polytechnique Montréal].
- Fournier, Q. (2022). Machine Learning for Anomaly Detection in Kernel Traces [Ph.D. thesis, Polytechnique Montréal].
- Kohyarnejadfard, I. (2022). System Performance Anomaly Detection using Tracing Data Analysis [Ph.D. thesis, Polytechnique Montréal].
- Muller Rodrigues, I. (2022). Algorithms and Learning Models for Bug Report Deduplication [Ph.D. thesis, Polytechnique Montréal].
- Alves Randel, R. (2021). Optimization Methods to Enhance Constraint-Based Semi-Supervised Clustering [Ph.D. thesis, Polytechnique Montréal].
- Rochink Costa, L. (2021). Workload Optimization for Swarm-Powered Ad-hoc Clouds [Ph.D. thesis, Polytechnique Montréal].
- Correia Pereira, T. (2023). Innovative Data Collection Framework for Humanitarian Logistics: A Serious Game Solution [Ph.D. thesis, Polytechnique Montréal].
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Master's Thesis (12)
- Silva De Oliveira, A. S. (2024). Predictive Power of Large Language Models in Bug Severity Detection: An Explorative Study [Master's thesis, Polytechnique Montréal].
- Moine, R. (2023). Comparaison empirique de deux stratégies de recherche locale [Master's thesis, Polytechnique Montréal].
- Aber Aouni, A. (2022). Utilisation d'un espace latent pour une déduplication de bogues rapide [Master's thesis, Polytechnique Montréal].
- 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].
- Pereira, P. (2022). Imitation du branchement fort pour les problèmes de rotations d'équipage [Master's thesis, Polytechnique Montréal].
- Bouchard, I. (2021). Building Damage Assessment After a Natural Disaster in Emergency Contexts: A Deep Learning Approach [Master's thesis, Polytechnique Montréal].
- Ton, K. (2021). Using a Diversity Criterion to Select Training Sets for Machine Learning Models [Master's thesis, Polytechnique Montréal].
- 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].
- Heutte, N. (2020). A Divide-and-Conquer Approach to Employee Scheduling [Master's thesis, Polytechnique Montréal].
- 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].
- Boucaud, L. (2019). Mécanismes d'attention pour les modèles convolutifs dans le cadre de la prédiction de trajectoires [Master's thesis, Polytechnique Montréal].
- Hulot, P. (2018). Towards Station-Level Demand Prediction for Effective Rebalancing in Bike-Sharing Systems [Master's thesis, École Polytechnique de Montréal].
