Spotlight! Ani Krishna

Ani Krishna, Postdoctoral Scholar, Computer Science

What are you working on?

I work on quantum error correcting codes. If we find more efficient ways to perform error correction, we can significantly reduce the size of quantum computers that are capable of running interesting algorithms. I personally find it exciting because I can talk to both theorists doing fascinating abstract work which I find fun and simultaneously to experimentalists who are designing real systems which keeps me grounded.

What got you into your research?

Lunch-time conversations with Daniel Gottesman at the Blackhole bistro at Perimeter back in 2015. I asked Daniel what the next big topic was and he mentioned reducing the overhead required to construct efficient quantum circuits. In particular, that low-density parity-check (LDPC) codes could be useful. This became one of the focal points of my Ph.D

What are your career plans?

Industry is exciting because there are large teams working together to build a quantum computer. This aspect of large teams with one goal is very different from the academic setting I'm used to. I'd like to work on such teams and be part of the research effort.

What do you like most about Stanford?

It's a fantastic environment for research. The weather is perfect. Everyone has diverse interests outside of research.

What do you like most about quantum science at Stanford?

I've learned very broadly outside my core research area. Patrick and his students work on using information theory as a lens to understand physics. Mary and her students study (classical) error correction. These areas have enough overlap with my area of expertise that I've found useful tools to borrow and new topics to explore.

Where do you see quantum science going in the coming years?

We're at the cusp of realizing scalable error correction in devices. We're beginning to see lots of prototype devices that demonstrate the right types of noise suppression. It's only a matter of time before we're at the 'threshold' where larger systems get better. Hopefully, there's a Moore's Law type of progression where devices get exponentially better over time.

What are your hobbies?

Biking and wine!