Efficiency-driven design of modern engineering systems, such as critical infrastructure, cyber-physical systems, power grids, and enterprise networks, has left them exposed to increasingly risk-encumbered environments. Disruptions triggered by natural disasters, process hazards, human errors, and cyber attacks have elevated the risk exposure of engineering systems and revealed the need for systems that can offer higher resilience to hedge against adverse events. Resilience refers to a system’s ability to withstand and mitigate the impact of disruptions and return to normal operating conditions. The existing literature on system resilience and related quality attributes (e.g., reliability, availability, robustness, etc.) reveals that there is no uniform definition of resilience or a consistent way to measure it. In this paper, we provide a critical review of the existing models on resilience assessment and optimization. We identify important areas of potential contributions for measuring and optimizing resilience for complex systems operating in dynamic, uncertain environments. We also highlight the broader impacts of proposed research strategies.