Saadia Gabriel

Hi! I'm Saadia Gabriel.

I'm a third-year PhD student in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. I am advised by Prof. Yejin Choi. My research area is natural language understanding and generation. I'm excited about machine learning techniques and deep-learning models for social commonsense and logical reasoning in text.

Recent Projects:

Coherent Text Generation with Narrative Flow:

Cooperative Generator-Discriminator Networks
for Abstractive Summarization with Narrative Flow

Saadia Gabriel, Antoine Bosselut, Ari Holtzman, Kyle Lo, Asli Celikyilmaz, Yejin Choi. arXiv preprint 2019.

Toxic Language Detection in Social Media:

The Risk of Racial Bias in Hate Speech Detection

Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi, Noah A. Smith.
ACL 2019. Best Paper Nominee.

Interpretable Question-Answering and Generation:

MathQA: Towards Interpretable Math Word Problem Solving
with Operation-Based Formalisms

Aida Amini, Saadia Gabriel, Shanchuan Lin,
Rik Koncel-Kedziorski, Yejin Choi, Hannaneh Hajishirzi.
NAACL 2019. Check out the dataset and leaderboard!

ML for Vision, Robotics and Social Impact:

Early Fusion for Goal Directed Robotic Vision

Aaron Walsman, Yonatan Bisk, Saadia Gabriel,
Dipendra Misra, Yoav Artzi, Yejin Choi, Dieter Fox .
IROS 2019. Best Paper Nominee.

Ruling the Roost with CNNs: Detecting and Tracking Communal Bird Roosts in Weather Radar Data

Zezhou Cheng, Saadia Gabriel, Pankaj Bhambhani,
Daniel Sheldon, Subhransu Maji, Andrew Laughlin, David Winkler.
Fine-Grained Visual Categorization Workshop (FGVC5) at CVPR 2018.