Engineering a real-time, statistical monitoring service for Google Cloud products.

I worked as a engineer - scaling one of the world's largest distributed databases and the backbone of Google's products.

In-house mathematics and physics tutor for a Monash University affiliated residential college.

Over the course of six weeks I investigated Neural Network implementations with the Google TensorFlow framework. I created a training dataset from raw sensor data and then trained a Recurrent Neural Network capable of predicting noisy signal segments from within a larger signal. I presented these results at the AMSIConnect conference.

I worked within an Agile development team tasked with building new features for the MyPost Consumer website. I divided my time between front-end programming, quality assurance and as a business analyst. This placement has provided me with strong knowledge of the entire software development life cycle, from feature inception to programming and testing.

Explored new optimization algorithms for big data processing. Implemented an algorithm in Apache Spark and tested it on a computing cluster.