Random projections of high-dimensional probability measures have gained much attention in asymptotic convex geometry and high-dimensional statistics. While fluctuations at the level of the central limit theorem have been classically studied, only more recently has an inquiry into large deviation principles for such projections been initiated. In this talk, I will review existing work and describe our results on large deviations. I will also talk about sharp large deviation estimates to obtain the prefactor apart from the exponential decay in the spirit of Bahadur and Ranga-Rao. Applications to asymptotic convex geometry and a range of examples including $\ell^p$ balls and Orlicz balls would be given. This talk is based on several joint works with S. S. Kim and K. Ramanan.