The increase of electric vehicle (EV) adoption in recent years has correspondingly increased the importance of providing adequate charging infrastructure for EV users. For a charging service provider, the fundamental question is to determine the optimal location and sizing of charging stations with respect to a given objective and subject to budget and other practical constraints. One possible objective is to maximize EV adoption as part of a public policy on electric transportation. Alternatively, the objective may be to maximize the profit gained from providing this service, in which case the price of charging is also to be optimized. These problems are fundamentally combinatorial and frequently formulated using mixed-integer linear optimization. In this talk, the focus will be on the use of bilevel optimization in this area, in particular to more accurately capture the interactions between the charging service provider and the EV users. This is joint work with Ikram Bouras, Luce Brotcorne, and Alemseged Weldeyesus.