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Chris Re

Co-Founder

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I’m a professor in the Stanford AI Lab (SAIL), the center for research on foundation models (CRFM), and the Machine Learning Group (bio). Our lab works on the foundations of the next generation of AI systems.

  • On the AI side, I am fascinated by how we can learn from increasingly weak forms of supervision, the basis of new architectures, the role of data, and by the mathematical foundations of such techniques.
  • On the systems side, I am broadly interested in how machine learning is changing how we build software and hardware. I’m particularly excited when we can blend AI and systems, e.g,. Snorkel, Overton (YouTube), or Together.

Our work is inspired by the observation that data is central to these systems, and so data management principles (re-imagined) play a starring role in our work. This sounds like Silicon Valley nonsense, but oddly enough, these ideas get used due to amazing students and collaborations with Google ads, YouTube, Apple, and more.
While we’re very proud of our research ideas and their impact, the lab’s real goal is to help students become professors, entrepreneurs, and researchers. To that end, over a dozen members of our group have started their own professorships. With students and collaborators, I’ve been fortunate enough to cofound a number of companies and a venture firm. For transparency, I try to list companies I advise or invest in here and our research sponsors here. My students run the ML Sys Podcast.

Research

Research Paper

Efficiently Modeling Long Sequences with Structured State Spaces

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Learn More about Efficiently Modeling Long Sequences with Structured State Spaces
Research Paper

Cross-Modal Data Programming Enables Rapid Medical Machine Learning

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Learn More about Cross-Modal Data Programming Enables Rapid Medical Machine Learning
Research Paper

Train and You’ll Miss It: Interactive Model Iteration With Weak Supervision…

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Learn More about Train and You’ll Miss It: Interactive Model Iteration With Weak Supervision…
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