Research Interests
Optimization & Random projections: Use random projections in optimization problem to reduce the size or the dimension of the problem while having theoretical guarantees on the induced error on the objective value; use random projections in iterative algorithms to derive algorithms that converge with high probability to an optimal solution of the problem while using only a subspace of the variables at each step.
Combinatorial Optimization: study & build innovative algorithms for optimization problems with discrete variables
Robust Optimization: Study optimization problems having uncertain data: we look for solutions that minimize the worst cost induced by the uncertainties
Bi-level Optimization: Optimization problems that model Stackelberg games: we optimize the decision of the leader that have to take into account the optimal response of the follower
Network Optimization: Optimal sensor location in networks, smart-grids