Semiconductor technology plays an important role in today’s modern life. Nanodevices including nanosensors using the semiconductor technology have crucial real-world applications ranging from bio-sensing and gas-sensing to energy conversion in solar cells as well as generation of security keys in cyber-security. In this work, first I give an overview of mathematical modeling of charge transport in semiconductor devices using PDE models incorporating uncertainty sources, and describe the effect of uncertainty propagation on the model solution. Then, I describe the quantification of parameter uncertainty using observational data in semiconductor devices by developing statistical Bayesian inference methods.