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, reliable methods, and large models. E-mail: schmidt@cs.washington.edu

Before joining UW, I was a postdoc at UC Berkeley where my mentors were Moritz Hardt and Ben Recht. I received my PhD from MIT advised by Piotr Indyk.

The papers below give an overview of topics I have worked on. For a full list of publications, please see this page or Google Scholar.

Selected publications

• LAION-5B: An open large-scale dataset for training next generation image-text models
  Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev
  NeurIPS 2022, datasets & benchmarks track
  Outstanding paper award

• Robust fine-tuning of zero-shot models
  Mitchell Wortsman, Gabriel Ilharco, Jong Wook Kim, Mike Li, Simon Kornblith, Rebecca Roelofs, Raphael Gontijo-Lopes, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, Ludwig Schmidt
  CVPR 2022
  Best paper finalist

• 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)

• Practical and Optimal LSH for Angular Distance
  Alexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya Razenshteyn, Ludwig Schmidt
  NIPS 2015 (Conference on Neural Information Processing Systems)

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