Philippe is Research Scientist at Microsoft Research, based in New York. Previously, Philippe was at Salesforce Research, and before that he completed his Ph.D. in Computer Science at UC Berkeley, advised by Marti Hearst and John Canny.

Philippe's thesis work revolved around applying the latest NLP technology to the news domain, thinking of what news interfaces could look like in the not so distant future.

Philippe also works in text Summarization and Simplification, building methods for unsupervised text generation: designing methods (such as the Summary Loop and Keep it Simple) that can compete with supervised method, without relying on the existence of a dataset.

An area of excitement for Philippe is thinking about ways to evaluate NLP and NLG systems, particularly thinking of task-oriented human evaluation that put NLP systems in practical settings and measure value added by a system.

In Berkeley, I was a TA/GSI for:

• EE120 — Signals and Systems — Spring 2018,
• CS182/282 — Introduction to Deep Learning — Spring 2019 & 2020.

I enjoyed leading discussions and lectures, creating homeworks from scratch, and interacting with brilliant students.

I have also mentored 10+ undegraduate students in their first steps doing research. If you are an undergraduate student interested in research at the intersection of NLP and News, feel free to contact me.