Estibaliz Gómez-de-Mariscal

Instituto Gulbenkian de Ciência

Names

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

Estibaliz Gómez-de-Mariscal (Preferred)
,
Estibaliz Gómez de Mariscal

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.

****@gmail.com
,
****@pa.uc3m.es
,
****@igc.gulbenkian.pt

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.

Postdoc
Instituto Gulbenkian de Ciência (gulbenkian.pt)
2021Present
 
PhD student
Universidad Carlos II de Madrid (uc3m.es)
20162021
 
MS student
Universidad Complutense de Madrid (ucm.es)
20152016
 
Undergrad student
University of the Basque Country (ehu.eus)
20092014
 

Advisors, Relations & Conflicts

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

Coauthor
Ignacio Arganda-Carreras
****@ehu.eus
2020Present
 
PhD Advisee
Arrate Muñoz-Barrutia
****@ing.uc3m.es
20162021
 

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 processing
Present
 
microscopy
Present
 
cell migration
Present
 
statistical modeling
Present
 
biostatistics
Present
 
cell tracking
Present
 
machine learning
Present
 
segmentation
Present
 
cell mechanics
Present
 
image sequence processing
Present
 
video processing
Present
 
optical flow
Present
 
super-resolution
Present
 
transfer learning
Present
 
single image super-resolution
Present
 
active learning
Present
 
weak supervised learning
Present
 
unsupervised learning
Present