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
Conference paper
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 https://doi.org/10.1111/itor.13197
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 https://doi.org/10.1186/s13677-022-00296-4
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 https://doi.org/10.1145/3524842.3527951
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 https://doi.org/10.1007/s10732-022-09502-7
See all publications (42)
Supervision at Polytechnique
COMPLETED
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Ph.D. Thesis (5)
- Fournier, Q. (2022). Machine Learning for Anomaly Detection in Kernel Traces (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/10708/
- Kohyarnejadfard, I. (2022). System Performance Anomaly Detection using Tracing Data Analysis (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/10281/
- Muller Rodrigues, I. (2022). Algorithms and Learning Models for Bug Report Deduplication (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/10297/
- Alves Randel, R. (2021). Optimization Methods to Enhance Constraint-Based Semi-Supervised Clustering (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/9240/
- Rochink Costa, L. (2021). Workload Optimization for Swarm-Powered Ad-hoc Clouds (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/6650/
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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 https://publications.polymtl.ca/10471/
- Pereira, P. (2022). Imitation du branchement fort pour les problèmes de rotations d'équipage (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/10490/
- Bouchard, I. (2021). Building Damage Assessment After a Natural Disaster in Emergency Contexts: A Deep Learning Approach (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/9470/
- Ton, K. (2021). Using a Diversity Criterion to Select Training Sets for Machine Learning Models (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/9902/
- 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 https://publications.polymtl.ca/4207/
- Heutte, N. (2020). A Divide-and-Conquer Approach to Employee Scheduling (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/5362/
- 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 https://publications.polymtl.ca/5336/
- 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 https://publications.polymtl.ca/3951/
- Hulot, P. (2018). Towards Station-Level Demand Prediction for Effective Rebalancing in Bike-Sharing Systems (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/3160/