About me

I am a Machine Learning Engineer at Berkeley Existential Risk Initiative (BERI). I am the lead engineer for the Seldonian Machine Learning Toolkit, a set of software libraries for building provably safe and fair ML models.

Previously, I was a software developer at the Princeton Neuroscience Institute. I developed applications for data analysis and visualization of terabyte-scale neuroscience imaging datasets. I created a web blog while working at Princeton where I shared demos of some of these tools: BrainMaps.

Before becoming a software developer, I was a postdoctoral researcher in astrophysics at UCLA. I studied the first galaxies in the universe and the imprint they left on the universe in a process known as reionization. During my PhD and Postdoc, I developed an image analysis pipeline for detecting and classifying galaxies in large space-based imaging datasets. My research has been featured in press releases from Keck Observatory and Space.com.

I published a side project in a Blog Post where I used a convolutional neural network to classify satellite images of the Martian surface.

My open-source work is shared at www.github.com/austinhoag.