High-dimensional statistics, optimization, sampling algorithms, machine learning
Max Daniels is a graduate student in Applied Mathematics at MIT under the supervision of Phillipe Rigollet. He is broadly interested in theoretical and computational aspects of high-dimensional statistical inference algorithms. Max received a combined B.S. in Mathematics and Computer Science at Northeastern University (2022). His work is supported by the DOE CSGF fellowship.