Experienced Researchers

The NeEDS project is led by Professor of Operations Research, Dolores Romero Morales. The project consists of four research work packages, each led by an Experienced Researcher (ER), who is an expert within their respective fields.

Throughout the project, these ER’s, along with a number of other researchers from both the academic and industrial partners, will strengthen the Network’s activities and knowledge transfer through secondments to different partner institutions.  Read more about the ER’s involved in NeEDS below.

Professor Dolores Romero Morales, Copenhagen Business School, Denmark

Dolores Romero Morales is a Professor in Operations Research at Copenhagen Business School. Her areas of expertise include Supply Chain Optimization, Data Mining and Revenue Management. In Supply Chain Optimization she works on environmental issues and robustness. In Data Mining she investigates interpretability and visualization. In Revenue Management she works on large-scale network models. Her work has appeared in a variety of leading scholarly journals, including Management Science, Operations Research, INFORMS Journal on Computing and Discrete Applied Mathematics, and has received various distinctions.

Professor Emilio Carrizosa, Universidad de Sevilla, Spain

Emilio Carrizosa has almost 30 years of research and teaching experience. He has published more than 100 papers in international journals in Mathematical Optimization (Deterministic ad Stochastic Global Optimization, Multiobjective Optimization) and Data Analysis (Data Visualization, Support Vector Machines, Sparse Principal Component Analysis, Network Clustering).

The results of his research have appeared in prestigious journals such as Mathematical Programming, Operations Research, Journal of Biostatistics, Journal of Multivariate Analysis, among others. He has led national research projects nonstop for the last 20 years, and has been principal investigator in several national and international research contracts with industry. He is President of the Spanish Statistics and Operations Research Society.


Assistant Professor Jochen de Weerdt, KU Leuven, Belgium

Jochen De Weerdt has been an Assistant Professor at the Department of Decision Sciences and Information Management of the KU Leuven since 2014. He works within the Leuven Institute for Research on Information Systems, LIRIS for short, conducting research in the area of Information Systems, with a special interest in Business Process Management, process mining, data mining, artificial intelligence, and web analytics.


Professor Min Chen, University of Oxford, UK

Min Chen is an internationally-established scientist in visualization and visual analytics. Since arriving at Oxford in 2011, he has collaborated with scholars in mathematics, computer science, engineering science, medical sciences, and arts and humanities. He is currently leading visualization activities at Oxford, working on a broad spectrum of interdisciplinary research topics, ranging from the sciences to sports, and from digital humanities to cyber security.

He is currently the editor-in-chief of Computer Graphics Forum (Wiley/Eurographics), an elected member of the Eurographics Executive Committee, the EuroVis Steering Committee, and IEEE VAST Steering Committee. He is a fellow of British Computer Society, European Computer Graphics Association, and Learned Society of Wales.

Professor Richard Weber, Universidad de Chile, Chile

Richard Weber is Professor at the Department of Industrial Engineering within FCFM. His teaching and research activities concentrate on Data Science and related subjects. Since 2014 he is head of the Data Science group within the Institute of Complex Engineering Systems where six researchers and several research assistants develop Data Science applications for industry and the public sector. He is Program Committee chairman of the conference series BAFI.


Professor Cynthia D. Rudin, Duke University, USA

Cynthia Rudin is an Associate Professor of computer science, electrical and computer engineering, statistical science and mathematics at Duke University, and directs the Prediction Analysis Lab. Previously, Prof. Rudin held positions at MIT, Columbia, and NYU. She is the recipient of the 2013 and 2016 INFORMS Innovative Applications in Analytics Awards, an NSF CAREER award, was named as one of the “Top 40 Under 40” by Poets and Quants in 2015, and was named by Businessinsider.com as one of the 12 most impressive professors at MIT in 2015. Work from her lab has won 10 best paper awards in the last 5 years. She is past chair of the INFORMS Data Mining Section, and is currently chair of the Statistical Learning and Data Science section of the American Statistical Association.