Machine learning is fundamentally changing the ways that people build and maintain software.
We are a CS research group at Stanford led by Professor Chris Ré interested in understanding those shifts and building the foundations for the next generation of machine learning systems. On the machine learning side, we’re fascinated by how we can learn from increasingly weak forms of supervision and understand the mathematical foundations of these techniques. On the systems side, we want to exploit our theoretical insights to help people more effectively build, validate, and maintain machine learning models. And we are most excited when we can do both at the same time (e.g., Snorkel).
Check out our blog posts for an overview of our work and future directions we’re especially excited about!
Our group is supported by an amazing set of collaborators and sponsors, which we list here.