Introducing Nathan Rooy — Machine Learning Engineer
Tell us a bit about yourself.
I completed my undergrad here at the University of Cincinnati in Aerospace Engineering and went to graduate school in England for Motorsport Engineering. I used to work as a computational fluid dynamics (CFD) engineer doing aerodynamic design and optimization for race cars. I try to bike commute to work at least 100 times per year. I like traveling, camping, rock climbing and photography. Also, I’m really weird.
So, you jumped into Spatial. What made you decide to join us?
Spatial basically does what I used to do as a hobby in my freetime. Now I get paid to do it which is really cool. It’s a bit serendipitous actually. Plus we’re only five people right now which is nice. I enjoy working in small groups, where your individual contribution can mean success or failure for the company.
Rumor has it you have a very interesting blog, can you tell us about that?
Haha, well my blog basically started out as a series of questions that I was trying to answer for myself but because the questions involved a fair bit of work I decided to post them on the internet when I finished. This way, any poor sap out there with the same questions can just google them and hopefully save some time.
How did you get into machine learning?
I initially got into machine learning a few years back after I kept reading articles about how it was the “future” so I requested a couple textbooks from the library on the subject. After reading them, I was really impressed by the potential applications of machine learning thus providing the motivational fuel I needed to keep going. Compared to what I was doing with computational fluid dynamics, the math involved for machine learning is rather trivial. Actually, deep learning and CFD share a lot of similarities in relation to the calculus and linear algebra which makes for a fairly painless transition. Plus, the Kaggle data science competitions are pretty addicting which is nice because they force you to learn if you want to do well.
What gets you jazzed about machine learning as it pertains to Spatial?
Right now I’m most excited about deep learning with word vectors as they pertain to natural language processing and sentiment analysis.
What is your favorite flavor of Kombucha?
So far, it has to be the cherry/chia seed combo from GTS. Although, I’m expecting Will’s homebrew kombucha to deliver some serious weirdness in the coming weeks.
What does Spatial’s vision mean to you?
It means a lot. I’m one of those people who would much rather spend $600 on a last minute flight to South East Asia than buy the latest iPhone. To me, the ROI of money spent on traveling is almost infinite. Between the sights, people, music, food, and everything else, the knowledge gained from traveling is invaluable when trying to further your understanding of the world. So to be able to quantify this adventurous spirit we all share here at Spatial with the intended goal of helping other people in their exploration of the world is very fulfilling.
What is inspiring you right now?
Definitely working for a cutting edge startup with like minded people. Literally anything we think of can become reality within a short amount of time. Not very many work environments foster that kind of excitement and I find it very refreshing and motivating.
