I am currently an Assistant Professor at the University Poitiers. In 2022-2023 I was Lead Data Scientist at Elenchos AI. I apply deep neural networks and large language models to classification, summarization, retrieval and question answering tasks. In addition to research into algorithm design focused on deep learning, text embeddings, and latent-space models, I have worked with clients to develop systems for analyzing financial, legal and regulatory documents, optimize revenue management, and design survey experiments.

Previously, I spent three years as an Assistant Professor at the University of Poitiers. From 2017-2019 I was a Postdoctoral Researcher at the University of Geneva. I completed my PhD at New York University in January 2017, where my dissertation applied machine learning to analyzing political texts to understand strategic interactions among lawmakers, as well as political activity by nonprofits and the evolution of ideological dimensions of legislation.

Commonly used tools include Python, R, TensorFlow, Keras, pyTorch, Weights & Biases, sentence-transformers, scikit-learn, pandas, Adobe Hadoop and Spark, and SQL; and working through AWS and Google Cloud platforms.