Designing thermoelectric (TE) alloys is particularly challenging because it is a multi-property optimization problem, where the properties that contribute to high TE performance are interdependent. Alloying has been employed to optimize a variety of properties that directly or indirectly affect the TE performance: (1) enhance phonon scattering to reduce lattice thermal conductivity, (2) promote band convergence to improve power factor, (3) tune band gap to suppress bipolar conduction, and (4) optimize dopability . Figure summarizes some of the beneficial effects of alloying on the TE performance, including enhanced power factor through band convergence, optimized doping by manipulating the native defects, and reduced lattice thermal conductivity due to increased phonon scattering and lattice softening. Notably, automated high-throughput experimental procedures are being developed to synthesize bulk samples with the goal of discovering new TE materials and optimizing TE alloys. Computations have greatly facilitated new TE materials discovery, and their optimization through electronic doping . At the same time, first-principles modeling of TE alloys has provided useful mechanistic insights ; however, a systematic computational framework for designing and optimizing TE alloys has not been demonstrated yet. In concert with highthroughput bulk synthesis, computations can provide guidance to navigate the continuous compositional space, and identify the optimal compositions in the multi-property phase space. Outside of thermoelectrics, computations have been successfully em- Beneficial effects of alloying on the electronic and thermal transport and doping of thermoelectric materials. Band convergence leads to higher power factor (S s ), increased phonon scattering and lattice softening lowers lattice thermal conductivity (k L ), and changes in defect chemistry may promote dopability.