Abstract: Random variable is an important tool of modeling randomness in a practical problem. But besides randomness, in the real world, there exists other kind of uncertainties such as imprecision or vagueness. Set-valued function is a choice to model the imprecision. Set-valued random variable can describe both randomness and imprecision. Recently, as an extension of classical stochastic process, set-valued stochastic processes have been studied and employed to describe complicated real world. In this talk, at first we shall introduce the fundamental theory of set-valued stochastic processes. Then we consider the set-valued Lebesgue integral with respect to Lebesgue measure, set-valued stochastic integrals with respect to Brownian motion and Poisson point process in a M-type 2 Banach space. At last we will consider the existence and uniqueness of the strong solution to the set-valued stochastic differential equations with Brownian motion diffusion and Poisson jump.