Mean-field models with nonlocal interactions are ubiquitous in applications. Often, these models are computationally challenging due to the cost of handling interaction terms. In this talk, I will present dimension reduction techniques to overcome these difficulties based on Fourier analytic and kernel methods in machine learning.