Portrait of Amal Zouaq

Amal Zouaq

Associate Academic Member
Full Professor, Polytechnique Montréal, Department of Computer Engineering and Software Engineering
Associate Professor, University of Ottawa, School of Electrical Engineering and Computer Science
Research Topics
Generative Models
Information Retrieval
Knowledge Graphs
Learning on Graphs
Natural Language Processing
Representation Learning
Website

Biography

Amal Zouaq is a Full Professor at Polytechnique Montreal in the computer science and software engineering department. She holds an FRQS (Dual) Chair in AI and Digital Health. She is also an IVADO professor, a member of the CLIQ-AI consortium (Computational Linguistics in Québec), and an adjunct professor at the University of Ottawa.

Prof. Zouaq's research interests encompass artificial intelligence, natural language processing, and the Semantic Web. As the director of the LAMA-WeST research lab, her work extends to various facets of natural language processing and artificial intelligence, including LLMs with nonparametric memories, modular LLMs, neuro-symbolic models and Semantic Web.

Furthermore, she actively contributes to the academic community by participating as a program committee member in numerous conferences and journals related o knowledge and data engineering, natural language processing, and the Semantic Web.

Current Students

Edouard Albert-Roulhac
Master's Research - Polytechnique Montréal
Davide Baldelli
PhD - Polytechnique Montréal
Principal supervisor :
Sarath Chandar
Website
Github
Google Scholar
Alexis Brissard
Master's Research - Polytechnique Montréal
Website
Gaetan Butault
PhD - Polytechnique Montréal
Github
Arnaud Delage-Reid Delage-Reid
Master's Research - Polytechnique Montréal
arnaud.reid@gmail.com
Github
Karou Diallo
PhD - Polytechnique Montréal
diallokarou28@polymtl.ca
Google Scholar
Zacharie Garnier-Cuchet
Master's Research - Polytechnique Montréal
zacharie.garnier.cuchet@gmail.com
Github
Fabrice Lamarche
PhD - Polytechnique Montréal
Github
Gaya Mehenni
Master's Research - Polytechnique Montréal
Website
Github
Aditya Sharma
PhD - Polytechnique Montréal
Co-supervisor :
Chris Pal
Website
Github
Google Scholar

Publications

Local Structure Matters Most: Perturbation Study in NLU
Louis Clouâtre
Prasanna Parthasarathi
Amal Zouaq
Sarath Chandar
Recent research analyzing the sensitivity of natural language understanding models to word-order perturbations has shown that neural models … (see more)are surprisingly insensitive to the order of words.In this paper, we investigate this phenomenon by developing order-altering perturbations on the order of words, subwords, and characters to analyze their effect on neural models’ performance on language understanding tasks.We experiment with measuring the impact of perturbations to the local neighborhood of characters and global position of characters in the perturbed texts and observe that perturbation functions found in prior literature only affect the global ordering while the local ordering remains relatively unperturbed.We empirically show that neural models, invariant of their inductive biases, pretraining scheme, or the choice of tokenization, mostly rely on the local structure of text to build understanding and make limited use of the global structure.
2021-07-29
ArXiv (preprint)
doi.org
arxiv.org