about me

I'm Daniel Ricks.

I have a Masters degree in Computer Science, and I worked on cutting-edge artificial intelligence research in a Deep Learning lab for three years. I've done projects in both natural language processing (for the Amazon Alexa Prize Competition) and machine learning (working with shallow neural networks trained to reconstruct the linguistic context of words).

I've published five papers, most of which are about novel uses of high-dimensional embedding spaces for knowledge extraction from text (notable conferences include IJCAI, and NeurIPS and AAAI workshops). As part of my research I engineered Autoplay, a learning environment for text-based games, which has been cited many times by peers who have used it for their own research. I also won the IEEE CIG Text-Based Adventure AI Competition two years in a row, with an agent that can derive action commands from its surroundings and disambiguate state space.

I'm passionate about applying machine learning applications to real world problems that can help people. I love writing clean, understandable code with a purpose. I enjoy solving problems and getting things done.