Ankit Pensia (Computer Science), advised by Po-Ling Loh (Statistics) and Varun Jog (Electrical and Computer Engineering) is working on projects in robust machine learning. His focus is on designing statistically and computationally efficient estimators that perform well even when the training data itself is corrupted. Traditional algorithms don’t perform well in the presence of noise: they are either slow or incur large error. As the data today is high-dimensional and usually corrupted, a better understanding of fast and robust algorithms would lead to better performance in scientific and practical applications.
