Abstract: We review some results on the recent development of statistical inference for high-dimensional linear models. We introduce three debiased LASSO estimators, which are asymptotically normal and thus we can construct statistical inference for low dimensional parameters in high-dimensional setting. In addition, we give a brief introduction to the bootstrap assistant procedures to conduct simultaneous inference based on the debiased LASSO.