Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page
Demo Data from VLDB 2026 / reviewers in the wild / expert

Maria Emilia Echeveste

dblp:182/7004 · DBLP profile ↗
← Back
2ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0001-8338-0384ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Trustworthy machine learning · 87% Language models and text generation · 13%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computing education · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Trustworthy machine learning
fairness		 0.912025
HESEIA: A community-based dataset for evaluating social biases in large language models, co-designed in real school settings in Latin America · EMNLP 2025
Machine learning › Trustworthy machine learning › fairness › fairness evaluation
social bias evaluation		 0.912025
HESEIA: A community-based dataset for evaluating social biases in large language models, co-designed in real school settings in Latin America · EMNLP 2025
Natural language and speech › Language models and text generation
large language model		 0.312025
HESEIA: A community-based dataset for evaluating social biases in large language models, co-designed in real school settings in Latin America · EMNLP 2025

Methods — techniques the papers use, named apart from their topics

dataset co-design · 1.7
YearPublicationVenuePosition
2025 HESEIA: A community-based dataset for evaluating social biases in large language models, co-designed in real school settings in Latin America
abstract
Guido Ivetta, Marcos J Gomez, Sofía Martinelli, Pietro Palombini, M Emilia Echeveste, Nair Carolina Mazzeo, Beatriz Busaniche, Luciana Benotti. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. 2025.
Guido Ivetta, Marcos J. Gomez, Sofía Martinelli, Pietro Palombini, Maria Emilia Echeveste, Nair Carolina Mazzeo, Beatriz Busaniche, Luciana Benotti
 EMNLP5
2016 Challenges of Introducing Computer Science into the Traditional Grammar of K-12 Schooling
abstract
Introducing CS (Computer Science) programming into the mandatory school curriculum, requires considering the effects and implications of adding a subject area with its own learning characteristics and dynamics into the preexisting and rigid structure of schooling. Based on classroom observations, this poster presents four classroom dynamics that resulted from introducing CS teaching into regular schools: 1) heterogeneous grouping 2) learning from practice 3) flexible blocks of times 4) inclusion of special ed. students. We argue these dynamics challenge the traditional school.
Maria Emilia Echeveste
 ITiCSE1