Email: [email protected]
Twitter: @danintheory
GitHub: @danintheory
Website: danintheory.com
Email: [email protected]
Twitter: @danintheory
GitHub: @danintheory
Website: danintheory.com
I am a research scientist at Facebook AI Research in NYC.
I am interested in the interplay between physics and computation. My work in theoretical physics has focused on the relationship between black holes, quantum chaos, computational complexity, randomness, and how the laws of physics are related to fundamental limits of computation.
Previously, I was a postdoc in the School of Natural Sciences at the Institute for Advanced Study in Princeton, NJ. I completed my Ph.D. at the Center for Theoretical Physics at MIT, funded by a Hertz Foundation Fellowship and the NDSEG. Prior to that, I was a Marshall Scholar in the UK. While there, I read for Part III of the Mathematical Tripos at Cambridge and then studied quantum information at Oxford. In a previous life (undergrad), I worked on invisibility cloaks (metamaterials and transformation optics) with David R. Smith.
My full name is very common, but nevertheless I tend to go only by Dan Roberts—which I never publish under and which unfortunately (by logical necessity) is even more common.
I’m interested in black holes. I’m also interested in quantum information theory. Luckily, via the gauge/gravity duality or holography, these two subjects are intricately tied together.
Some of my work focuses on what happens when something falls into a black hole (in anti-de Sitter space). The black hole will very quickly scramble (but not destroy) the information. Black holes are thermal systems, and this is actually a manifestation of the well-known butterfly effect. We can try to think about this process in terms of its computational complexity, or we can study it as a distinguishing feature of quantum chaos.
In 2012, I co-founded Diffeo, a startup focused on collaborative machine intelligence. As part of Diffeo Labs, I also co-organized the TREC track Knowledge Base Acceleration.
At FAIR, I hope to focus on applying tools from theoretical physics to gain insight into machine learning and artificial intelligence.
I also organize an online journal club hep-ai for discussions of machine learning and AI papers from a theoretical physicist’s perspective. Please email me if you’re interested in joining!
Black Holes Produce Complexity Fastest – Viewpoint in the APS journal Physics (which is very nicely written) on Complexity Equals Action.
Complexity growth – research highlight in Nature Physics (which is two paragraphs—one and a half of which are behind a paywall—and is unfortunately incomprehensible) on the same work.