Dan Mikulincer is a PhD student of Mathematics at the Weizmann Institute of Science. His research involves probability and high-dimensional geometry, which is central to modern statistics. Dan examines concentration-of-measure phenomena and their interrelations with dimension, particularly the central limit theorem – a universal phenomenon according to which so long as a large enough sample is taken from a certain population, its average would have identical properties, independently of the sampling population. Dan quantifies the dependency of the theorem on the dimension or number of parameters of the sample using stochastic calculus tools, which have gained prominence in financial mathematics. By using these novel methods , Dan hopes to create new statistical tools applicable to our modern environment, and to shed new light on existing statistical tools when applied in high dimensions. These insights can find their application in a myriad of other fields by introducing new approximation and sampling algorithms.