Welcome to the Grakn Labs team — Nick Powell
This summer we have two interns working in our office, learning all about Grakn and investigating various applications of and integrations with our distributed knowledge base.
We’re excited to have them as part of the team (even if only temporarily), and so we figure we’d revisit our ‘meet the team’ series, and find out what their background are and what they’re working on with us on Holloway Road.
This week, we’ll introduce you to Nick. He’s working on a few very exciting projects, which will be featured in this blog in the coming days.
So tell us what you do at Grakn Labs?
Hey I’m Nick, and I am interning as a data scientist/machine learning engineer. I get a lot of freedom in choosing what to work on and how to accomplish it, which is awesome, but the main goal is to uncover interesting new use cases for the Grakn platform. Basically, figure out what Grakn can do and where it can be used. It is very open-ended and thus I can get pretty creative with my work.
For the first two weeks I’ve been here I’ve been working on a couple projects. The first is an attempt to prove that training a neural net in tandem with Grakn can yield a higher predictive accuracy than simply running that neural net on its own. I’m making use of Grakn’s inference engine and the additive rule-making schema to find relationships among word entities that may not have been predicted by the neural network, and iteratively adding likely relationships into the knowledge base. I’m also working on a recommendation system built on top of Grakn. Expect to see some news on the blog this summer!
What were you doing before starting here?
I just finished my Bachelor of Science from Stanford, where I studied their computational mathematics major. I was always most interested in applied math and statistics — the idea that randomness can be ‘domesticated’ and made sense of if you have the right tools. I enjoy applying this paradigm to the social sciences (which are often way behind the times), as well as in the tech arena. Grakn allows you to think very abstractly about the problems you face and is applicable in practically any setting or domain, which is really cool.
I’ve interned as a software engineer in the past at Tableau and have done on-campus research (some NLP research, some database stuff), and I really like applying concepts and algorithms I’ve learned to real-world projects.
What are you up to when you’re not Grakn-ing around and tinkering with tech?
I love electronic music, particularly house and techno, and in my free time I produce and DJ. This is a super creative endeavor that yields immediate results, which might be why I like it so much. I also enjoy playing tennis, although in recent years I haven’t played as much due to a shoulder injury I picked up. Now that I’ve graduated, though, I hope to get back into it.
Looking forward to learning and creating this summer at Grakn!
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You can follow Nick on LinkedIn. For those who are interested, check out Nick’s music on his SoundCloud.
