Chris Cundy

Chris Cundy

Machine Learning PhD Student

Stanford University


I am broadly interested in Artificial Intelligence (AI), particularly in ensuring that sophisticated AI systems will robustly and reliably carry out the tasks that we want them to.

If you’re a student at Stanford (undergraduate/masters/PhD) who wants to work on a project involving safe and reliable machine learning: get in touch!

I studied Physics as an undergraduate at Cambridge University before switching area to take a computer science master’s degree. During my master’s, it was a pleasure to work with Carl E. Rasmussen, developing variational methods for Gaussian Process State-Space Models.

Before starting my PhD at Stanford, I worked at the Centre for Human Compatible AI, collaborating with Stuart Russell and Daniel Filan. I have also worked at the Future of Humanity Institute at Oxford University, collaborating with Owain Evans on scalable human supervision of complex AI tasks.

Get in touch at chris dot j dot cundy at gmail dot com


  • Probabilistic Machine Learning
  • Generative Models
  • Reinforcement Learning
  • Safe and Reliable ML


  • PhD in Computer Science, 2018-Ongoing

    Stanford University

  • MEng in Computer Science, 2017

    Cambridge University

  • BA in Natural Sciences (Physics), 2016

    Cambridge University

Recent Posts

F Divergences

A first try at blogging, I explore some interesting properties of f divergences

Managing ArXiv RSS Feeds in Emacs

Background It’s very important for any researcher to keep up with the papers that are being published, especially in the fast-moving field of machine learning. However, there are a lot of papers from the arxiv categories which I follow, sometimes hundreds of papers a day.