drmeco

Department of Economics

Dolores
Romero Morales
Professor
,
Professor of Operations Research, PhD in Operations Research, Erasmus University Rotterdam


Room: POR/16.A-2.79
Tel:
+4538153823
E-mail: drm.eco@cbs.dk
Dolores
Presentation

Dolores Romero Morales is a Professor in Operations Research at Copenhagen Business School. Her areas of expertise include Data Science, Supply Chain Optimization and Revenue Management. In Data Science she investigates explainability/interpretability, fairness and visualization matters. In Supply Chain Optimization she works on environmental issues and robustness. In Revenue Management she works on large-scale network models. Her work has appeared in a variety of leading scholarly journals, including European Journal of Operational Research, Management Science, Mathematical Programming and Operations Research, and has received various distinctions. Currently, she is Editor-in-Chief to TOP, the Operations Research journal of the Spanish Society of Statistics and Operations Research, and an Associate Editor of Journal of the Operational Research Society, and the INFORMS Journal on Data Science.

She has worked with and advised various companies on these topics, including IBM, SAS, KLM and Radisson Edwardian Hotels, as a result of which these companies managed to improve some of their practices. SAS named her an Honorary SAS Fellow and member of the SAS Academic Advisory Board. She currently leads the EU H2020-MSCA-RISE NeEDS project, which has a total of 15 participants and a budget of more than €1.000.000 for intersectoral and international mobility, with the aim to improve the state of the art in Data Driven Decision Making.

Dolores joined Copenhagen Business School in 2014. Prior to coming to Copenhagen Business School, she was a Full Professor at University of Oxford (2003-2014) and an Assistant Professor at Maastricht University (2000-2003). She has a BSc and an MSc in Mathematics from Universidad de Sevilla and a PhD in Operations Research from Erasmus University Rotterdam.

Primary research areas

Data Science 

Supply Chain Optimization

Revenue Management

Curriculum Vitae
Social media
Links
Link to this homepage
www.cbs.dk/en/staff/drmeco
Courses

Current teaching activities:

Analytics and Big Data (MBA)

Data Science: Data Driven Decision Making (MSc)

Introduction to Machine Learning for Economics (MSc)

Mathematical Optimization: Models, Methods and Applications (MSc)

Supervision

Nine PhD dissertations supervised, and two ongoing.

Publications sorted by:
2024
Emilio Carrizosa; Marcela Galvis Restrepo; Dolores Romero Morales / A Binarization Approach to Model Interactions Between Categorical Predictors in Generalized Linear Models
In: Applied Intelligence, 19.6.2024
Journal article > peer review
Peter Bogetoft; Jasone Ramírez-Ayerbe; Dolores Romero Morales / Counterfactual Analysis and Target Setting in Benchmarking
In: European Journal of Operational Research, Vol. 315, No. 3, 6.2024, p. 1083-1095
Journal article > peer review
Emilio Carrizosa; Jasone Ramírez-Ayerbe; Dolores Romero Morales / Generating Collective Counterfactual Explanations in Score-based Classification via Mathematical Optimization
In: Expert Systems with Applications, Vol. 238, No. Part D, 3.2024
Journal article > peer review
Antti Punkka; Dolores Romero Morales / Guest Editorial to the Special Issue of the 32nd European Conference on Operational Research in Espoo (Finland)
In: European Journal of Operational Research, 2024, 2 p.
Editorial
Emilio Carrizosa; Jasone Ramírez-Ayerbe; Dolores Romero Morales / Mathematical Optimization Modelling for Group Counterfactual Explanations
In: European Journal of Operational Research, 5.1.2024
Journal article > peer review
Veronica Piccialli; Dolores Romero Morales; Cecilia Salvatore / Supervised Feature Compression Based on Counterfactual Analysis
In: European Journal of Operational Research, Vol. 317, No. 2, 9.2024, p. 273-285
Journal article > peer review
2023
Emilio Carrizosa; Jasone Ramírez-Ayerbe; Dolores Romero Morales / A New Model for Counterfactual Analysis for Functional Data
In: Advances in Data Analysis and Classification, 25.10.2023
Journal article > peer review
Emilio Carrizosa; Kseniia Kurishchenko; Alfredo Marín; Dolores Romero Morales / On Clustering and Interpreting with Rules by Means of Mathematical Optimization
In: Computers & Operations Research, Vol. 154, 6.2023
Journal article > peer review
Emilio Carrizosa; Vanesa Guerrero; Dolores Romero Morales / On Mathematical Optimization for Clustering Categories in Contingency Tables
In: Advances in Data Analysis and Classification, Vol. 17, No. 2, 6.2023, p. 407-429
Journal article > peer review
Rafael Blanquero; Emilio Carrizosa; Cristina Molero-Río; Dolores Romero Morales / On Optimal Regression Trees to Detect Critical Intervals for Multivariate Functional Data
In: Computers & Operations Research, Vol. 152, 4.2023
Journal article > peer review
More results... (total 68 results)