EURO PhD School on
Data Driven Decision Making
and
Optimization

June 13-22, 2022, Institute of Mathematics of the University of Seville

About

About

This EURO PhD School (EPS) will focus on giving participants advanced training on Data Driven Decision Making. There will be a methodological as well as an applied component to this EPS. Methodological training on the role of Mathematical Optimization in Data Science will be given in the format of lectures and computer workshops. The lectures will highlight the mathematical and statistical modeling and numerical optimization behind data analysis and data visualization tools. The computer workshops will make this knowledge actionable. Applications of the acquired knowledge to the modeling of specific industrial problems will be presented by professionals from industry and worked out by the PhD students. Mathematical and statistical models and numerical solution approaches will be developed and communicated, following a collaborative approach, in which the PhD students will work in small groups under the guidance of the instructors. The training of the EURO PhD School on Data Driven Decision Making and Optimization is eligible for 5 ECTS.

Where

Institute of Mathematics of the University of Seville

When

June 13-22, 2022

Program



Confirmed Speakers

Pietro Belotti

Pietro Belotti

Politecnico di Milano, Italy

Pietro Belotti is assistant professor at the Department of Electronics, Information and Bioengineering of the Politecnico di Milano. His research interests are primarily in discrete nonlinear optimization, multiobjective optimization, and optimization under uncertainty. He is currently working on various applications of Optimization to sustainable mobility, both at the national and European level. Pietro obtained a PhD in Computer Engineering in 2003 from Politecnico di Milano. He then worked at Carnegie Mellon University, Lehigh University, and Clemson University. Between 2013 and 2020, he was software engineer at FICO in the development team of the FICO Xpress optimizer. Over the last 20 years, he has collaborated with Linköpings Universitet in Linköping, Sweden; Bilkent University, Ankara; Zuse Institute, Berlin; University of Rome, Tor Vergata; and École Polytechnique, Paris. He is author and maintainer of the open-source software package Couenne for mixed integer nonconvex optimization problems.
Ilker Birbil

Ilker Birbil

University of Amsterdam, The Netherlands

Ilker Birbil is a professor in AI & Optimization Techniques for Business & Society at University of Amsterdam, where he is currently the head of Business Analytics Section. He received his PhD in 2002 from North Carolina State University with a major in Industrial Engineering, and minors in Operations Research and Mathematics. He was a postdoctoral research fellow at the Erasmus Research Institute of Management for two years. From 2004 to 2018, he was a faculty member at Sabanci University in Istanbul, where he was one of the founders of the Data Analytics professional degree program. He held the Chair in Data Science and Optimization at Erasmus University Rotterdam from 2018 to 2021. With his colleagues and students, he authored research articles on mathematical optimization, operations management, and data science. These articles appeared in leading journals such as, Mathematical Programming, SIAM Journal on Optimization, Mathematical Methods of Operations Research, Management Science, European Journal on Operational Research, and Transportation Science. He completed various research projects as the principal investigator and participated in several initiatives as a researcher or as a committee member. He also collaborated with industry to work on business problems ranging from cloud computing to airline crew planning. His research interests center around optimization methods in data science and decision making. Lately, he is interested in interpretable machine learning and data privacy in operations research.
Víctor Blanco

Víctor Blanco

Institute of Mathematics of the University of Granada, Spain

Víctor Blanco is an Associate Professor in Quantitative Methods for Economics & Business at the Universidad de Granada, Spain. He has a MSc in Pure Mathematics from the Universidad de Granada (2005) and PhD in OR from the Universidad de Sevilla (2009). His research has focused in a wide variety of topics related to Mathematical Optimization, as Logistics & Transportation, Data Science, Computational Algebra or Algorithmic with more than 40 papers published in top OR journals, including Mathematical Programming, European Journal of Operations Research, Computers & Operations Research, Omega, Fuzzy Sets & Systems and Advances in Data Analysis and Classification. He has been interested both in the theoretical and applied aspects of Mathematical Programming. He is PI in several (local, regional and national) research projects and has colaborated in different industrial contracts. He has carried several research stays at internationally recognized research centers as the Institute of Mathematics & its application (IMA, University of Minnesota), the University of British Columbia, the University of California-Davis or the University of Edinburgh. He is currently an active member of the Spanish Stats & OR Society (SEIO), the Spanish Network on Location Analysis and Related Problems (REDLOCA) and the Institute of Mathematics of the Universidad de Granada (IMAG).
Emilio Carrizosa

Emilio Carrizosa

Institute of Mathematics of the University of Seville, Spain

Professor of Statistics and OR at the University of Seville. President of math-in, the Spanish Network of Mathematics for Industry. Past President of the Spanish Statistics and Operations Research Society, past Director of the Mathematical Institute of the University of Seville, past Editor-in-Chief of TOP, and now Associate Editor of TOP and ADAC. His publications track record includes papers in Operations Research, Data Science and Industrial Mathematics, published in top OR journals (e.g. Opns Res, Manage Sci, Maths of OR) and in applied fields as a consequence of his crossdisciplinary research. Since 1996, PI in projects funded by public and private agencies and leader of industrial contracts in different sectors. 10 PhD theses supervised (plus 6 ongoing) in the last 10 years. Visiting Professor at Copenhagen Business School (Otto Mønsted Visiting Professor), Vrije Universiteit Brussel, U. Montréal, U. Wien.
Jochen De Weerdt

Jochen De Weerdt

Katholieke Universiteit Leuven, Belgium

Jochen De Weerdt is an Associate Professor in Process and Business Analytics at the Research Centre of Information Systems Engineering (LIRIS) of the Faculty of Economics and Business at KU Leuven. He obtained a PhD in Business Economics at KU Leuven in 2012 on the topic of Automated Business Process Discovery. Subsequently, he worked as a postdoctoral research fellow at the Information Systems School of the Queensland University of Technology (Brisbane, Australia). His research and teaching interests include Business Information Systems, Business Analytics, Process Mining, Machine Learning, Learning Analytics, and Business Process Management. He has published over 70 papers on these topics, including academic book chapters, peer-reviewed journal articles, and refereed papers at international conferences and workshops. He published papers in renowned journals such as IEEE Transactions on Knowledge and Data Engineering, Data Mining and Knowledge Discovery, Decision Support Systems, Information Systems, Computers in Human Behavior, etc. In addition, his findings have been presented at well-known international conferences such as BPM, ECML-PKDD, DSAA, and IEEE CEC.
Martina Fischetti

Martina Fischetti

Joint Research Center of the European Union, Spain

Martina Fischetti is Senior Researcher-Transport Policy Analyst at the Joint Research Center of the European Union, in Seville. She holds a PhD in Operations Research from the Technical University of Denmark, titled "Mathematical Programming Models and Algorithms for Offshore Wind Park Design". This was an industrial PhD in collaboration with a leading energy company in North Europe: Vattenfall. The models and algorithms developed during her PhD have been used by the company to design the layout of important wind farms, such as Danish Kriegers Flak and Hollandse Kust Zuid. The PhD project was awarded several international prizes, including best thesis in Europe in Operations Research (EURO-EDDA award), best Industrial PhD in Denmark, the Glover-Kingsman prize, and finalist position at the prestigious INFORMS Franz Edelman Award. Martina was also awardee for the EURO WISDO WOMEN4OR last year. Her areas of expertise include networks, mathematical modelling, heuristics for large-scale optimization problems and machine learning. She is also active in promoting Operations Research with talks and different activities. In particular, she is co-founder of the EUROYoung network for PhD students in OR. She has been founder and coordinator of AIROYoung, the Young Researchers Chapter of the Italian Operational Research Society (AIRO) for several years. She has been in the organization committee of different workshops, and guest editor for a special issue in Springer OR Forum.
Vanesa Guerrero

Vanesa Guerrero

Department of Statistics of the University Carlos III of Madrid, Spain

Vanesa Guerrero is an Assistant Professor (on tenure-track) at the Department of Statistics in Universidad Carlos III de Madrid since 2017. Her research interests consist of developing innovative frameworks that enhance interpretability of complex datasets by combining theoretical modeling methods of mathematical optimization and statistical data analysis with computational tools. Her work has been published in leading scholarly journals such as Mathematical Programming, Omega, European Journal of Operational Research or Multivariate Behavioral Research. She is the principal investigator of two publicly funded research projects, one in collaboration with industry and the other involving a multidisciplinary academic group. She has a BSc, MSc and PhD in Mathematics from Universidad de Sevilla and she has visited Copenhagen Business School (Frederiksberg, Denmark) and École Polytechnique (Palaisseau, France) as a pre- and post-doctoral researcher, respectively.
Daniel Herrero

Daniel Herrero

Director of the mathematical optimization and ML area at decide4AI, Spain

Daniel Herrero Giner, Industrial engineer from the Polytechnic University of Madrid, Master in Industrial Organization and director of the mathematical optimization and machine learning area at decide4AI. Daniel has more than 10 years of experience implementing optimization solutions based on linear programming, heuristic techniques, constraint programming, local search, uncertainty programming, column generation, etc. During his career, he has developed solutions in the logistics field, personnel planning, energy solutions and TELCO. He is interested in real optimization and data science use cases, focused in out of the box thinking for solving huge optimization problems and always willing to improve efficiency in his projects with state of the art algorithms.
Javier León

Javier León

Senior Business Consultant at decide4AI, Spain

Javier León is a senior business consultant at decide4AI. In 2020 he received his PhD in Operations Research from Complutense University of Madrid (UCM) and RMIT University (Melbourne, Australia). He was a predoctoral and postdoctoral researcher at UCM, where he is also a member of the research group 'Decision aid models in logistics and disaster management'. His research interests are mathematical programming with uncertainty and multicriteria decision making. From 2021 he has been working at Decide4AI, helping customers with optimization-related problems identify their needs, as well as developing solutions using tools such as mathematical programming, heuristics, constraint programming or column generation.
Belén Martín-Barragán

Belén Martín-Barragán

Business School of the University of Edinburgh, UK

Belen Martín-Barragán is Reader in Management Science at The University of Edinburgh. Her research lies at the interface between Data Science and Mathematical Programming, with a special interest on Explainable Artificial Intelligence. In a board sense, her research interests focus on using or developing variants of Operational Research techniques and applying them to data analysis problems, such as classification and clustering. Her work has appeared in a variety of top-ranked journals such as European Journal of Operational Research, Risk Analysis, INFORMS Journal on Computing, Discrete Applied Mathematics, Computers and Operations Research. She is also contributed to other areas such as statistics (Journal of Applied Statistics) and economics (Economic Modelling). She has been PI of the EPSRC-funded project “Optimisation Models for Interpretable Analytics”.
Emilia Martínez Serrano

Emilia Martínez Serrano

Repsol Technology Lab, Spain

University degree in Mathematics at University of Oviedo (Spain), master degree in Information Systems at EOI Business School and AMP at IE Business School. She has combined the academic and professional scopes into her professional career. After 10 years of working in consultancy, she understands multiple industries, such as food, trade, telecommunications, education, energy, transportation and others. This allows her to directly apply methods to diverse real scenarios, proving high adaptation skills. She has over 14 years of experience in such a leader company as REPSOL. She has being working in IT for Trading, Gas and Power business until 2018 when she has joined to Technology Corporative Area. Currently, she is SR Manager of Optimization Tech & Experimentation in Repsol TechnologyLab leading Optimization Processes, Advanced Mathematics & Labs teams.
Laust Hvas Mortensen

Laust Hvas Mortensen

University of Copenhagen & Statistics Denmark, Denmark

Professor of epidemiology at the University of Copenhagen and head of the Data Science Lab at Statistics Denmark, which is the Danish statistical institution. His work covers various fields in epidemiology, but has increasingly focused on large scale studies based on the Danish administrative registers across multiple disciplines. He has a particular interest in developing and promoting new ways of creating value by reusing data collected for other purposes. Visiting positions at Duke University and Stanford University.
Prashanth Nadukandi

Prashanth Nadukandi

Repsol Technology Lab, Spain

Received the B.Tech degree in civil engineering from IIT Guwahati, India, in 2005, and the PhD degree in computational mechanics from the UPC-BarcelonaTech, Spain, in 2011. He worked at CIMNE-Barcelona as a Research Engineer (2009), Research Scientist (2011) and as an Assistant Research Professor from 2014 to 2016. He held a Marie Skłodowska-Curie Individual Fellowship in Mathematics, University of Manchester, UK, from 2016 to 2018. Since 2018, he has been the Numerical Methods Technical Advisor with the Advanced Mathematics department, Repsol Technology Lab, Spain. Currently, he works at the interface of computational mechanics and machine learning for applications in the energy industry.
Laura Palagi

Laura Palagi

Sapienza University of Rome, Italy

Laura Palagi is Full Professor in Operations Research at Sapienza University of Rome, Italy. She has an MSc in Electronic Engineering (1990) and a Ph.D. in OR (1996) from Sapienza University of Rome. Her research has focused mainly on algorithms for nonlinear continuous optimization problems, focusing on those arising in training machine learning (Deep Network and Support Vector Machines) and on mixed-integer nonlinear problems. She has been interested both in the theoretical aspects of Mathematical Programming and Machine Learning and in the application, particularly in the health field. She authored more than 50 papers in top OR journals, including Mathematical Programming, Siam Journal on Optimization, Computational Optimization and Application, Mathematics for OR, European Journal of Operations Research, Optimization Methods and Software. She was a founding member of the Italian start-up ACTOR Srl (Analytics, Control Technologies and Operations Research) in 2011. She is currently a member of the Italian Operations research society (AIRO). She is a member elected to the managing board of EUROPT (The Continuous Optimization Working Group of EURO).
Miguel Ángel Pérez Cutiño

Miguel ángel Pérez Cutiño

Virtualmech S.L., Spain

Miguel Angel Pérez Cutiño is a Data Scientis and Deep Learning specialist at VirtualMech. He has a bachelor's degree in computer science from the University of Havana (2018); a Msc in Logic, Computing and Artificial Intelligence from the University of Seville (2021), and he is currently working at Virtualmechanics s.l. and doing an Industrial PhD in Mathematics from the University of Seville. His research has focused on a wide variety of topics related to Artificial Intelligence, such as the classification of animals from wild sounds, the identification of people from aerial robots, and automatic fault detection from unbalance data in the railway and energy sector. He has been involved in european projects such as GRIFFIN, and spanish projects such as OPTIDRON. His main interests lies in the intersection of Computer Vision, Deep Learning, and discrete mathematics.
Pepa Ramírez Cobo

Pepa Ramírez Cobo

Faculty of Sciences of the University of Cádiz, Spain

Pepa Ramírez-Cobo is an Associate Professor at the University of Cádiz, and Associate Researcher at IMUS. She has a BSc in Mathematics from Universidad Autónoma de Madrid, a MSc in Applied Mathematics for Social Sciences from Université Paris-Dauphine, and a PhD in Quantitative Methods for Business and Economy from Universidad Carlos III de Madrid. She has been research visitor as a Fullbright fellow at the Department of Biomedical Engineering, Georgia Institute of Technology (Atlanta), and also at the Gipsa-Lab (Grenoble) through a CNRS contract. On top of her works in statistical estimation for stochastic processes, she has conducted research in several Data Science problems related to signal processing, environment, and interpretable and cost-sensitive learning methods. She has co-supervised five doctoral theses and published a total of 35 ISI JCR papers on top journals as Biostatistics, Annals of Applied Statistics, Bayesian Analysis, European Journal of Operational Research, Reliability Engineering & System Safety, Computers & Operations Research or Advances in Data Analysis and Classification. She has actively participated in a number of research and transfer projects.
Edwin Reynolds

Edwin Reynolds

TESCO, UK.

Edwin Reynolds is a Data Scientist at Tesco, the largest retailer in the UK. During his 18 months there, he has worked on applying advanced mathematical optimisation techniques across a variety of business areas. Before joining Tesco, he obtained a PhD from Lancaster University, focusing on integer programming decomposition methods for problems in railway disruption management.
Natalia Rezanova

Natalia Rezanova

Novo Nordisk A/S, Denmark

Natalia Rezanova is a Senior Operations Data Scientist in a Danish pharmaceutical company Novo Nordisk A/S, where she develops mathematical modelling-based applications within supply chain optimization, personnel, and production planning. After finishing her PhD in Operations Research from the Technical University of Denmark, Natalia has been mainly focusing on OR applications within transportation: crew rostering in the airline industry (Jeppesen), vehicle routing problems (AMCS) and passenger railway transportation (Danish State Railways), with focus on rolling stock and crew rostering and scheduling. Natalia’s interests lie within mixed integer linear programming modelling, but also in developing heuristic and metaheuristic approaches to solve optimization problems.
Dolores Romero Morales

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 Data Science, Supply Chain Optimization and Revenue Management. 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, Omega 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.
Juan Sebastián Valverde García

Juan Sebastián Valverde García

Virtualmech S.L., Spain

Dr. Valverde is Scientific Advisor at Virtualmechanics sl. He was formerly Chief Technology Officer for 8 years and founding member of the company. He received his PhD. at University of Seville in the Advanced Design in Mechanical Engineering program and did a postdoc at University of California Berkeley under the Fulbright program. He has worked in the academy at both University of Seville (Mechanical Engineering Dept. and Applied Mathematics Dept.) and University of Cádiz (Physics of Condensed Matter). Dr. Valverde is specialized in coupled field simulation applied to Renewable Energy and Thermal Energy Storage as well as vehicle and mechatronic system dynamics. He has recently started working on Data Analytics and AI applied to Automatic Fault Detection at industrial environments. Dr Valverde has been PI at many research projects publicly funded by EU programs and Spanish government where multidisciplinary groups of companies and universities have managed large budgets (~M€). He has developed his industrial research both at low TRL and medium TRL projects, including the management and construction of pilot plants and infrastructures (www.socratces.eu).
Rocío Vega Martínez

Rocío Vega Martínez

Reganosa, Spain

Undergraduate degree in mathematics from the University of Oviedo (2015), with a scholarship during the last year in a company in the energy sector. Interuniversity Master in Industrial Mathematics at Universidad Carlos III (2017), with contract in the area of applied mathematics as a research assistant. PhD in Mathematical Engineering (international doctorate, Cum Laude, 2021).Thesis on mathematical models applied to biomedicine, with research stay at the Courant Institute in New York, short stays at the Fields Institute in Toronto and at the University of Colorado, talks at international conferences and two articles published in prestigious journals. Lecturer at UC3M (2017-2021) and institutional representative of the university giving outreach talks (2018-2021). Since 2021, researcher and current Digitalization manager at Reganosa, a company that operates and maintain energy infrastructures and provides energy-related services. I work on the development of digital tools, with a solid mathematical basis, that help to improve energy efficiency and move towards decarbonization.
EPS @ the beach

EPS @ the beach

EPS @ the heart of Seville

EPS @ the heart of Seville

The final version of the program can be found here Download the pdf

Scientific committee

Bart Baesens

Prof. Bart Baesens

Faculty of Economics and Business of the Katholieke Universiteit Leuven, Belgium

Emilio Carrizosa

Prof. Emilio Carrizosa

Institute of Mathematics of the University of Seville, Spain

Vanesa Guerrero

Dr. Vanesa Guerrero

Department of Statistics of the University Carlos III of Madrid, Spain

Belén Martín-Barragán

Dr. Belén Martín-Barragán

Business School of the University of Edinburgh, UK

Emilia Martínez Serrano

Emilia Martínez Serrano

Repsol Technology Lab, Spain.

Dario Pacino

Dr. Dario Pacino

Technical University of Denmark, Denmark

Federico Perea Rojas-Marcos

Dr. Federico Perea Rojas-Marcos

University of Seville, Spain

Nils Ploug

Mr. Nils Ploug

Director of Social Statistics at Statistics Denmark, Denmark

Dolores Romero Morales

Prof. Dolores Romero Morales

Copenhagen Business School, Denmark

Richard Weber

Prof. Richard Weber

University of Chile, Chile

Organizing committee

Víctor Blanco

Dr. Víctor Blanco

Institute of Mathematics of the University of Granada, Spain

Rafael Blanquero

Dr. Rafael Blanquero

Institute of Mathematics of the University of Seville, Spain

Emilio Carrizosa

Prof. Emilio Carrizosa

Institute of Mathematics of the University of Seville, Spain

Antonia Castaño

Dr. Antonia Castaño

Faculty of Sciences of the University of Cádiz, Spain

Dolores Jiménez

Prof. Dolores Jiménez Gamero

Institute of Mathematics of the University of Seville, Spain

Salvador Pineda

Dr. Salvador Pineda

Department of Electrical Engineering of the University of Malaga, Spain

Pepa Ramírez Cobo

Dr. Pepa Ramírez Cobo

Faculty of Sciences of the University of Cádiz, Spain

Alfonso Suarez

Dr. Alfonso Suárez Llorens

Faculty of Sciences of the University of Cádiz, Spain

Venue

Location info and gallery

Seville, Spain

Institute of Mathematics of the University of Seville

Celestino Mutis building, first floor

Avenida de la Reina Mercedes

Sponsors

With the support of

This PhD School has been financed in part by EURO, DORS, SEIO, ECMI, math-in, Copenhagen Business, Universidad de Sevilla, and research projects EC H2020 MSCA RISE NeEDS (Grant agreement ID: 822214), FQM-329, US-1381178 (Proyectos I+D+i FEDER Andalucía), P18-FR-2369 (Junta de Andalucía, Spain) and PID2019-110886RB-I00 (funded by MCIN/AEI/10.13039/501100011033, Spain). This support is gratefully acknowledged.