The Constraint Reasoning and Optimization group, led by , develops, analyzes and applies practical algorithmic approaches to trustworthy automated reasoning and constraint optimization for efficiently solving computationally “intractable” (NP-complete or presumably harder) real-world problems. Contributions range from complexity analysis and algorithm design to open-source implementations of automated reasoning and constraint optimization solvers, as well as domain-specific applications in e.g. explainability, computational social choice, argumentation, and machine learning.