Naila Murray

Meta AI

Names

How do you usually write your name as author of a paper? Also add any other names you have authored papers under.

Naila Murray (Preferred)

Emails

Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. This information is crucial for deduplicating users, and ensuring you see your reviewing assignments.

****@naverlabs.com
,
****@xrce.xerox.com
,
****@cvc.uab.es
,
****@gmail.com
,
****@fb.com
,
****@meta.com

Education & Career History

Enter your education and career history. The institution domain is used for conflict of interest detection and institution ranking. For ongoing positions, leave the end field blank.

Researcher
Meta AI (meta.com)
2020Present
 
Researcher
Naver Labs Europe (naverlabs.com)
20172020
 
Researcher
Xerox Research Centre Europe, Xerox (xrce.xerox.com)
20132017
 
PhD student
Computer Vision Center, Universitat Autónoma de Barcelona (cvc.uab.es)
20082012
 

Advisors, Relations & Conflicts

Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.

Coauthor
Peter Koniusz
****@data61.csiro.au
20212022
 
Manager
Jon Almazan
****@xrce.xerox.com
20152018
 
Coauthor
Jon Almazan
****@xrce.xerox.com
20152015
 
Coauthor
Albert Gordo
****@inria.fr
20152015
 
Coauthor
Albert Gordo
****@xrce.xerox.com
20152015
 
Coauthor
Herve Jegou
****@gmail.com
20112015
 
Coauthor
Luca Marchesotti
****@beautifey.es
20112015
 
Coauthor
Luca Marchesotti
****@xrce.xerox.com
20112015
 
Coauthor
Herve Jegou
****@inria.fr
20112014
 
Coauthor
Maria Vanrell
****@uab.cat
20112014
 
Coauthor
Robert Benavente
****@cvc.uab.cat
20112014
 
Coauthor
Florent Perronnin
****@xrce.xerox.com
20112014
 

Expertise

For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing

image retrieval, cross-modal retrieval
Present
 
saliency estimation
Present
 
image aesthetics
Present