Ludwig Schmidt

I am an assistant professor in computer science at the University of Washington. My research interests revolve around the foundations of machine learning, often with a focus on datasets, evaluation, and reliable methods. E-mail: schmidt@cs.washington.edu

Until recently, I was a visiting research scientist in Russ Tedrake's robotics team at the Toyota Research Institute (TRI). Before TRI, I spent three wonderful years as a postdoc at UC Berkeley where my mentors were Moritz Hardt and Ben Recht. I received my PhD from MIT, where I was fortunate to be advised by Piotr Indyk and collaborated on several projects with Aleksander Mądry. During my PhD I also spent time at Google Brain working with Yoram Singer and Kunal Talwar.

Selected publications

• Retiring Adult: New Datasets for Fair Machine Learning
  Frances Ding, Moritz Hardt, John Miller, Ludwig Schmidt
  NeurIPS 2021 & EAAMO 2021
  New Horizons Award

• Measuring Robustness to Natural Distribution Shifts in Image Classification
  Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt
  NeurIPS 2020

• Do ImageNet Classifiers Generalize to ImageNet?
  Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar
  ICML 2019

• Towards Deep Learning Models Resistant to Adversarial Attacks
  Aleksander Mądry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu
  ICLR 2018

• Algorithms Above the Noise Floor
  Ludwig Schmidt
  PhD thesis, 2018
  George M. Sprowls Award (for best PhD theses in computer science at MIT)

• A Nearly-Linear Time Framework for Graph-Structured Sparsity
  Chinmay Hegde, Piotr Indyk, Ludwig Schmidt
  ICML 2015
  Best paper award

Full list of publications and Google Scholar.