My research focused on primarily the fields of Computational Semantics, Natural Language Understanding, and Deep Learning and Neural Networks for NLP. My thesis focuses on training a syntactically motivated semantic composition function via the use of Recursive Neural Networks to allow for a length agnostic semantic vector-space rather than the word level vector-space of other algorithms. To read more about this research, you can download my thesis here. The acompanying code for this thesis can be found here.

I have experience in the professional sphere where I have worked as a Data Scientist for Chatdesk for 2 years. Through this experience I have created bespoke inferential models for downstream NLP tasks, as well as designed and implemented those downstream applications. I additionally have worked with and maintained many critical relational and non-relational databases. Before that I was on the Labs team of Transcendent Endeavors researching novel algorithms for blending language pairs in order to aid language acquisition.

In my free time I like to make dumb games and (hopefully) not dumb music. Games were mostly made in weekend long game jams, check them out here. Music is forthcoming, but I am available to teach lessons! Feel free to shoot me an email if you’re interested. I specialize in general music theory and jazz piano lessons.