Human Computing Machine Learning

Never one to turn down talking about high-powered  programming over biscuits and coffee, Jonni Bidwell  meets the multitalented Omoju Miller.

Omoju Miller is a Machine Learning Engineer at GitHub. She holds a PhD from the University of California,Berkeley (which, apart from its academic excellence, she chose for its proximity to Skywalker Ranch). While studying for this part-time, as well being a mother, she worked as an expert at Google for its non-profit fund for Computer Science Education. We were lucky enough to catch up with her at O’Reilly’s Velocity conference in London, October 2018.

Linux Format: Tell us about your data science work at GitHub.

Omoju Miller: At GitHub I am part of the Machine Learning team, which is a part of the Platform Engineering team. I work on building deep learning models. Let me dial that back, actually…

My job is to use data to supercharge our services. So we have all these different data sources and we’re trying to learn which approaches will be useful to engage in certain kinds of products. So for example, the last project I was working on, and probably am still working on, is about understanding the fundamental nature of code and how to represent that.

It’s a bit of applied research, because if we can understand how to represent code in some sort of vectorised space, then we can answer questions like “Is this piece of code similar to that piece of code?” and we can do things like code provenance: “Who first wrote this function?”. All these things could come from this understanding, so that’s what I’m working towards.

I work on other things that are more straightforward – there’s an immediate application to a product. Some things are more “We have to do this because it’s going to help us on our roadmap”, and if we eventually get there, say in 18 months, then we can really supercharge our products. So what I do is really Applied Mathematics plus common sense and usefulness in the real world.