Introduction

I’m an applied scientist at Amazon, using machine learning to create new ways to connect brands and online shoppers. Previously I was a data and applied scientist at Microsoft where I built product recommendation systems for online shoppers. On the side, I also offer data science consulting and contract services.

Before moving into the machine learning world, I was an astronomer, receiving my PhD from UC Santa Cruz in May 2019 and my bachelor’s in physics at MIT.

During my first two years of grad school, I worked with Prof. Mark Krumholz, using high performance computing to study the effects of supernovae explosions. After two years I gained Prof. Piero Madau as an advisor, and under Mark and Piero I added more complicated physics into our model of these explosions (magnetic fields, turbulence, gravity, etc.).

Near the end of grad school I also worked with Prof. Alexie Leauthaud, using machine learning to identify low mass, low redshift galaxies in the Hyper Suprime Cam survey. That was a fun challenge of applying Deep Neural Networks to a >100 TB image dataset.

As an undergrad at MIT (2010-2014), I used the Hubble Space Telescope, built experimental X-ray telescopes and devices, and worked with an international collaboration to track how trace gases move through our atmosphere.

When I’m not working on these projects, I love getting outdoors. In my free time I run, hike, ski, garden and take pictures.