I am PhD student in Applied Mathematics and Computer Science at Purdue University. I am broadly interested in the theory behind Big Data and Machine Learning problems. My doctoral research is focused on developing fast and efficient randomized algorithms for large-scale problems. Currently, I am working on the intersection of tensor network with randomized algorithms. My goal is developing algorithms with provable guarantees, accurate and fast solutions to computationally expensive methods by leveraging dimensionality reduction and multi linear algebra techniques. During my doctoral journey, I am extremely fortunate to be advised by Petros Drineas and Guillaume Rabusseau.