In this paper we study the problem of how to efficiently embed $r$ interconnection networks $G_0 , \dots , G_{r-1}$, $r\le k$, into a $k$-dimensional hypercube $H$ so that every processor of the hypercube is assigned at most $r$ processors. We consider two models for the embeddings. The embeddings for balanced load model assign $r$ processors, all of which belong to different $G_i$'s, to a processor of $H$ and the ones for unrestricted load model allow any assignment of the $r$ processors to a processor of $H$. For the balanced load model, when each $G_i$ is a complete binary tree or a leap tree of $2^k-1$ processors, we describe an embedding achieving a dilation of $2$ and a congestion of $5$ and $6$, respectively. For the cases when each $G_i$ is a linear array or a 2-dimensional mesh of $2^k$ processors, we describe balanced load model embeddings that achieve a dilation of $1$ and an optimal congestion of $2$ and $4,$ respectively. Using these embeddings, we also show that $r_1$ complete binary trees, $r_2$ leap trees, $r_3$ linear arrays, and $r_4$ meshes can simultaneously be embedded into $H$ with constant dilation and congestion, $\displaystyle\sum_{i=1}^4 r_{i} \leq k $. We show that the congestion of the emmbeddings can be further reduced in the unrestricted load model by presenting embeddings of $r$ complete binary trees and $r$ linear arrays into $H$ that achieve a congestion of $3$ and $1$, respectively.