Mixed-integer semidefinite programs form an interesting generalization of mixed-integer linear programs with many applications. Here, some of the variables of a semidefinite program are required to be integer. This talk will introduce new methods as well as techniques that can be generalized from the linear to the semidefinite world. This includes presolving methods, e.g., fixing of variables, bound strengthening etc. Moreover, handling of symmetries and conflict analysis can be adapted and have a positive impact on the performance. The talk will also try to highlight the differences between the linear and semidefinite setting. The impact of the methods will be illustrated computationally, using SCIP-SDP, an open-source solver for mixed-integer semidefinite programs based on SCIP.