Eduardo Dadalto Câmara Gomes (Preferred)
, Eduardo Dadalto Camara Gomes
Eduardo Dadalto Câmara Gomes
Université Paris-Saclay CNRS CentraleSupélec
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.
****@centralesupelec.fr
, ****@gmail.com
Personal Links
Add links to your profiles on other sites. (Optional)
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.
PhD student
Université Paris-Saclay CNRS CentraleSupélec (centralesupelec.fr)
2020 – Present
MS student
Institut Supérieur de l'Aéronautique et de l'Espace (isae-supaero.fr)
2018 – 2020
Undergrad student
Instituto Tecnológico de Aeronáutica (ita.br)
2015 – 2020
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Coauthor
Pierre Colombo
****@gmail.com
2022 – Present
Coauthor
Nathan Noiry
****@althiqa.io
2022 – Present
Coauthor
Guillaume Staerman
****@gmail.com
2022 – Present
PhD Advisor
Pablo Piantanida
****@centralesupelec.fr
2020 – Present
PhD Advisee
Florence Alberge
****@l2s.centralesupelec.fr
2020 – Present
Coauthor
Pierre Duhamel
****@l2s.centralesupelec.fr
2020 – Present
Coauthor
Meryem Benammar
****@isae-supaero.fr
2020 – Present
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
misclassification detection
2021 – Present
out-of-distribution detection
2020 – Present
trustworthy AI
2020 – Present
deep learning
2020 – Present