With the rapid development of modern wireless communications, antennas and arrays design are very important and time-bound. However, more degrees of design freedom, integration and fabrication constraints and various objectives increase the difficulty of finding the best solution in antenna design. While full-wave electromagnetic simulation can be very accurate and therefore essential to the design process, it is also very time consuming. Recently, machine-learning-assisted optimization (MLAO) has been widely introduced to accelerate the design process of antennas and arrays. In this project, Artificial Neural Network (ANN) and Support Vector Machine (SVM) will be introduced in MLAO for antenna design, seeking for an accelerated approach for antenna synthesis.