Since the first Machine Learning class I took in 2013 I was fascinated by how much work can be done with a learning system. This fascination led me to apply Machine Learning algorithms in every area I worked in, from Natural Language Processing and Economics to Physics and Ecology.I am working both on practical applications of Machine Learning and on the general theory of Intelligence. My main areas of interest within Machine Learning are Reinforcement Learning and its theory, Multi-Agent systems, applications of ML to Economic modeling, and systems for Mathematical Reasoning.One of the projects I am proud of is the system I have built recently that allows automated annotation of images of fish using Deep Learning and will save hundreds of hours of volunteer time helping produce faster and better fish stock estimates from image data. It processes hundreds of thousands of images, uses cutting edge Deep Learning models and sophisticated decision making system.