Estibaliz Gómez-de-Mariscal (Preferred)
, Estibaliz Gómez de Mariscal
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.
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
Personal Links
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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)
2021 – Present
PhD student
Universidad Carlos II de Madrid (uc3m.es)
2016 – 2021
MS student
Universidad Complutense de Madrid (ucm.es)
2015 – 2016
Undergrad student
University of the Basque Country (ehu.eus)
2009 – 2014
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
2020 – Present
PhD Advisee
Arrate Muñoz-Barrutia
****@ing.uc3m.es
2016 – 2021
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