Google has named EECS Graduate student Ludwig Schimdt as a 2016 Google PhD fellow in Machine Learning. Google’s fellowship program recognizes and supports outstanding graduate students conducting exceptional research in Computer Science and related disciplines throughout North America, Europe and the Middle East.
Schmidt has been recognized for his research. Ludwig's research interests revolve around algorithmic problems in machine learning, statistics, and signal processing. The goal of Ludwig's research is to leverage theoretical insights for the design of new algorithms that combine provable guarantees with empirical performance improvements, especially on large data sets. In particular, Ludwig is working on faster algorithms for sparse recovery / compressive sensing, nearest neighbor search, and distribution learning. His work on approximation algorithms for structured sparse recovery has received the best paper award at ICML 2015.
Ludwig would like to thank his advisor Piotr Indyk for guidance and support.