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 experienced and early stage researchers from both the academic and industrial partners, strengthen the Network’s activities and knowledge transfer through secondments to different partner institutions.  Read more about the experienced researchers representing each NeEDS member organisation below:

Associate 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.

Work Package 1 leader: Developing innovative tools to tackle Network data

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.

Work Package 2 leader: Cutting-edge modelling to enhance Interpretability 

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.

Work Package 3 leader: Addressing the challenges of Complex data arising in Industry

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.

Work Package 4 leader: Innovative Extraction of knowledge by jointly addressing data processing and data analysis

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.


Georges Theys, AGEAS, Belgium

Georges Theys is the lead of the global centre of expertise for Data Analytics at Ageas. Mr. Theys coordinates research and development activities in Analytics for the group in domains such as: price elasticity optimization based on machine learning, psychometric modelling, cognitive analytics (roboadvisors and automate), customer journey analytics, process mining, voice analytics, etc. The center of expertise is also involved in defining analytic friendly IT architecture to ease the rollout of analytic-driven management techniques in insurance. He has more than 22 years of experience in ICT & Analytics, and has worked many years with the Informatics Directorate of the EC to introduce web-based applications to query institutions databases back in 1995.


Niels Ploug, Danmarks Statistik, Denmark

Niels Ploug is the Director of Social Statistics as well as former director of research at the Danish National Institute of Social Research, and a part-time Associate Professor at the Department of Economics of the University of Copenhagen. He also acts as chairman of the United Nations Global Working Group on Big Data, is head of the ESSnet on Quality of Multisource Statistics, and a member of the Eurostat Task Force on Big Data for Official Statistics. He has authored several books and articles on labor market and welfare state issues.

Laust Hvas Mortensen, Danmarks Statistik, Denmark

Laust Hvas Mortensen is Chief Advisor in Methods and Analysis as well as Professor at the Faculty of Health Sciences, University of Copenhagen. Laust holds visiting positions at Duke University and Stanford University.

Currently, he is involved in several big data and visualization research projects in collaboration with international research teams. Apart from the development of research and innovation products and services at Statistics Denmark, the group has published extensively in leading scholarly journals.

Sofie De Broe, Centraal Bureau voor de Statistiek, Netherlands

Sofie De Broe has been head of the methodology department since 2015. She also acts as scientific director of the Center for Big Data Statistics (CBDS) which develops experimental statistics using Big Data. Methodology and CBDS together create added value by bringing together expertise from different disciplines (IT, mathematics, physics, statistics, sociology, engineering sciences) and thereby answering relevant societal questions.  With her background in sociology, demography and statistics Sofie holds a PhD in Social Statistics on reproductive health differences between ethnic groups in the Ch’órti region of Guatemala.

Jorge Chacón García, Geographica, Spain

Jorge Chacón García is Technical Sales Specialist at Geographica. As Data Analyst focused on the technology sector, he is skilled in applied analysis, consulting and business management and has a strong interest in disruptive technology.

Jose Manuel Raposo Villamor, IECISA, Spain

Jose Manuel Raposo leads the R&D&I activities within the IECISA Digital Strategy & Innovation department. Previously, he was responsible for IECISA’s Expert Center for Quality and Processes, where he allocated resources, coordinated and monitored consultancy projects, as well as developed Process Improvement and Change Management. Since 2007, he is responsible for the coordination and performance of the Internal Audits of the Management Systems of the companies of the ECI group. Mr. Raposo has published two articles on H2020 R&D opportunities in ICT health as well as on H2020 R&D as a growth engine.

Andres Felipe Passalacqua, BancoEstado, Chile


Elena Nuñez Domingo, Repsol, Spain

Elena Nuñez Domingo is a Senior Scientist in the Advanced Mathematics Division at Repsol Technology Lab. She participates in different projects to address industrial problems through mathematical techniques of optimization, simulation and artificial intelligence and mostly focuses on the leadership of optimization projects to improve the company’s decision-making processes, such as refinery production plans, crude oil scheduling, logistic processes, etc. Elena furthermore manages relations with Universities and Research Centers, working together to achieve the successful development of projects and promoting the transfer of knowledge between industry and academia.

Alisdair Wallis, Tesco, UK

Dr. Alisdair Wallis is a Data Science Manager within the Data Science Team at Tesco Technology, where he is responsible for the academic engagements, internships, and R&D strategy. He holds a PhD in Theoretical Chemistry.



Julie Jespersen Groth, DSB, DK

Maria Montserrat Heiras Garibay, DSB, DK

Maria Montserrat Heiras thrives as an Operations Analyst at DSB with current focus on rolling stock planning operations. With a background within applied mathematics and operations research, Montserrat is truly passionate about railway problem-solving, network optimization and, generally speaking, finding solutions to long-term issues.
On top of this, she is also involved with multiple data analysis to improve the usage of time for the driving personnel, along with other data solutions.