Virtual reality (VR) holds promises for simulating interpersonal interactions, offering avenues to build social circles for individuals who may lack the possibility to interact with others in the physical world. As technology advances, avatars can better and better model the human movement, allowing to have interactions that feel more real, even with few tracking devices as is the case of consumer VR setups which comprise of only the headset and the controllers. One area where little work is present in the state of the art concerns the reconstruction of movements when multiple avatars are interacting with each other. This thesis explores the recreation of non-verbal interpersonal interactions, in particular the simulation of hugs, using machine learning-based techniques.