Hello world! I recently finalized my PhD studies at the University of Edinburgh, where I was advised by Dr. Rico Sennrich and Dr. Ivan Titov. My research aims to explore and improve the extent of language understanding in neural machine translation (NMT) and (multi-lingual) language modeling. Additionally, I’m interested in developing methods that enable large language models (LLMs) to reason about and generate natural language in a manner that is aligned with principles of fairness and safety.

Work completed in the course of my PhD candidacy has demonstrated that NMT models rely on shallow heuristics when inferring the right sense of ambiguous words, and improved the ability of transformer models to represent lexical and contextual information. More recently, we showcased that state-of-the-art translation and multi-lingual language models perform poorly on tasks that incorporate commonsense reasoning. Related phenomena, such as co-reference resolution, discourse processing, and translation of figurative language are also among my varied research interests.

In the past, I completed several research internships, including one with the MOSAIC group at the Allen Institute of Artificial Intelligence, where I investigated commonsense reasoning abilities of state-of-the-art models of language. My most recent internship experiences centered around injecting factual knowledge into task-oriented dialogue systems at Amazon and the development of training objectives for LLMs that are informed by insights from language processing in the human brain at the University of Zurich.

In my spare time, I enjoy bouldering, acrobatics, music, learning new things, and caring for my miniature orchard.