Sensor placement in wireless sensor networks (WSN) aims to maximize coverage while minimizing total deployment cost. However, existing coverage-only approaches do not consider the robustness of the entire system where sensors may break down or malfunction. In this talk, we first show a robustness-aware sensor placement approach by constructing a multi-objective optimization model. We demonstrate that this method increases the robustness of a WSN by up to 50%, with 201% higher probability of monitoring the entire environment as compared to the state-of-the-art coverage-only approach. We further improve our proposed method by introducing a robust optimization-based sensor placement approach that considers the uncertainty of the distance between a sensor and a target. We show that this improved model increases the probability of target detection by up to 77% compared to state-of-the-art coverage-only approach.