Her most relevant research contributions include computational complexity classification and algorithm design for bilevel programs and non-cooperative integer programming games. Motivated by Machine Learning predictions of a kidney transplant quality, most recently, Margarida started to analyze the social impact of this extra information. In particular, she is investigating the consequences in terms of strategical behaviors by decision makers in Kidney Exchange Programs. This research involves data science, graph theory, game theory (Nash equilibria computation) and integer programming.
M. Carvalho, X. Klimentova, A. Viana, 2017. Observability of Power Systems with Optimal PMU Placement. https://doi.org/10.1016/j.cor.2017.10.012
A. Baggio, M. Carvalho, A. Lodi, A. Tramontani, 2017. Multilevel Approaches for the Critical Node Problem. DS4DM-2017-012
M. Carvalho, X. Klimentova, A. Viana, 2017. Observability of Power Systems with Optimal PMU Placement. DS4DM-2017-010.
M. Carvalho, J. P. Pedroso, C. Telha, M. Van Vyve. Competitive Uncapacitated Lot-Sizing Game, 2017. DS4DM-2017-008.
M. Carvalho, A. Lodi, P. Marcotte, 2017. A Polynomial Algorithm for a Continuous Bilevel Knapsack Problem. DS4DM-2017-006
M. Carvalho, A. Lodi, J. P. Pedroso, 2017. Existence of Nash Equilibria on Integer Programming Games. DS4DM-2017-003