Tyler Maunu is a passionate researcher with a broad range of experience in mathematics, data science, and machine learning. With a PhD in Mathematics from the University of Minnesota-Twin Cities and an MS in Statistics, Tyler has focused on developing mathematically guaranteed methods for data science and machine learning. His interests include developing robust methods for handling outliers in data, algorithms for optimization with probability measures, and novel 3D reconstruction methods for computer vision. Tyler has also worked in industrial and government settings, where he has developed and implemented methods for prediction and inference with time series. Currently, Tyler is an Instructor of Applied Mathematics at the Massachusetts Institute of Technology.