I am a researcher working on advancing the state of the art in contextual natural language understanding, as part of the Semantic Machines team, with the goal of enabling more intuitive and accessible natural language interfaces to various technologies. Most recently, I have been working on developing methods for semantic parsing of natural language utterances in the context of semi-structured data (e.g., conversation histories or tabular data). Previously I graduated with a Ph.D. in Machine Learning from Carnegie Mellon University where I was advised by Tom Mitchell and worked on topics related to learning collections of functions, never-ending learning, curriculum learning, machine translation, and multiple other projects related to artificial intelligence and machine learning. Before I joined CMU, I graduated with an M.Eng. in Electrical and Electronic Engineering from Imperial College London. For my Master’s thesis I proposed a way to use topic modelling methods in order to perform human motion classification.