Philippe Laban
Philippe is a Ph.D. Candidate in Computer Science at UC Berkeley, advised by Marti Hearst and John Canny.

Philippe's work revolves around NewsLens project, applying the latest NLP technology to the news domain, thinking of what news interfaces could look like in the not so distant future. Do check out the demo, also available on the Play and Apple stores.

Through this journey, some areas of focus have been: entity linking, story-telling, chatbots and summarization.
Teaching / Mentoring
Philippe has been a TA (a.k.a. GSI in UCB lingo) for: He enjoyed leading discussions and lectures, creating homeworks from scratch, and interacting with brilliant students. Debugging students' Python environments and scanning hundreds of midterms late at night was less fun.

Philippe has also mentored around 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.
Peer-Reviewed Publications
The Summary Loop: Learning to Write Abstractive Summaries Without Examples
Philippe Laban, Andrew Hsi, John Canny, Marti Hearst
Association for Computational Linguistics (ACL), 2020
What's The Latest? A Question-driven News Chatbot
Philippe Laban, John Canny, Marti Hearst
System Demonstration at ACL, 2020
A framework for a text-centric user interface for navigating complex news stories
Philippe Laban, John Canny, Marti Hearst
Computation + Journalism, 2019
newsLens: building and visualizing long-ranging news stories
Philippe Laban, Marti Hearst
Workshop on Events and Stories in the News, ACL, 2017
Other Work
Abstractive News Summarization via Copying and Transforming
Philippe Laban, John Canny, Marti Hearst
Unpublished, 2019
From Brooklyn Barbers To Movie Stars: Using Introductions To Construct Embeddings Of People
Philippe Laban, John Canny, Marti Hearst
Unpublished, 2018