Eliana Duarte

Eliana Duarte is an Assistant Professor in Probability and Statistics at Universidade do Porto, where she conducts interdisciplinary research at the intersection of statistics, algebraic geometry, commutative algebra, and combinatorics. Her work focuses on algebraic and geometric methods in statistical modeling, particularly in discrete models, graphical models, and tensor product surfaces.

Her research interests include Algebraic Statistics, Graphical Models, Discrete Statistical Models, Toric Varieties, Implicitization, and Polynomial Systems. She applies algebraic techniques to understand the structure of statistical models and their maximum likelihood estimators, with recent work on decomposable models, polytree learning, and rational linear precision in higher-dimensional polytopes.

The trend in her recent publications (2016–2024) reflects a consistent focus on the algebraic foundations of statistical models, combining symbolic computation with geometric insight. Her work spans pure mathematical theory and applications in causal inference, microbiome modeling, and geometric design. Key themes include the use of syzygies, toric fiber products, and virtual resolutions in modeling and implicitization.

Scientific Awards:

• No awards listed in the provided text.

Advising and Grants:
Dr. Duarte advises graduate students in statistics and algebraic methods, although specific advisee names are not listed. She is involved in multiple research projects related to algebraic statistics and probabilistic modeling. While no specific grants are mentioned, her sustained publication record suggests active research funding.

Labs and Teams:
No specific laboratory or research team name is provided in the text. However, her collaborative publications indicate active participation in interdisciplinary research networks, particularly in algebraic statistics and computational geometry.