Ludwig Schmidt

Ludwig Schmidt is an Assistant Professor in the Computer Science Department and Stanford Data Science at Stanford University. He is also a member of the technical staff at Anthropic and LAION. His office is located in Gates 341 at Stanford.

Dr. Schmidt's research focuses on the foundations of machine learning with particular emphasis on datasets, multimodality, reliable generalization, and language models. His work often bridges combinatorial algorithms and continuous optimization, exploring algorithmic aspects of machine learning, statistics, and signal processing. His research group actively contributes to open source projects including OpenCLIP, OpenFlamingo, LAION-5B, and the DataComp datasets.

Ludwig Schmidt has established himself as a leading researcher in machine learning with numerous high-impact publications at top conferences. His work spans language models, multimodal learning, dataset construction, and model robustness. His research has shown consistent innovation in creating benchmarks and datasets that push the field forward, particularly in evaluating model robustness and generalization capabilities.

• Google PhD Fellowship
• Simons-Berkeley research fellowship
• Best paper award at ICML
• Outstanding paper award at NeurIPS 2022
• Best paper finalist at CVPR 2022
• New Horizons Award at NeurIPS 2021
• George M. Sprowls Award for best PhD thesis in computer science at MIT
• Best paper award at NIPS 2015

Dr. Schmidt advises a diverse group of students and postdocs, with current advisees including Alex Fang, Anas Awadalla, Dhruba Ghosh, Jeffrey Li, and Thao Nguyen. His former students include Mitchell Wortsman and Josh Gardner. He has secured significant research funding that supports his lab's work on foundational machine learning research. His teaching includes CS229 Machine Learning (Winter 2025), CSE599 Advanced Machine Learning (Spring 2023), and CSE446/546 Machine Learning (Autumn 2022 and Spring 2022).