Estefanía Serral Asensio

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Professor at KU Leuven

KU Leuven
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Belgium

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Estefanía Serral Asensio is a Lecturer and researcher at KU Leuven in Belgium. Her research focuses on customer outcome management in smart manufacturing, Internet of Things (IoT) adoption, and integrating IoT sensor data into event stream logs. She is actively involved in advancing knowledge in these areas through her recent publications.

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Jeroen Belien

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KU Leuven

PhD Student Position in Operations Management and Information Systems – KU Leuven

This fully funded PhD position at KU Leuven offers an exciting opportunity to conduct research in Operations Management and Information Systems, focusing on data-driven and mechanistic modelling for microclimate and pest/disease prediction in protected soft fruit production systems. The project is supervised by Prof. Jeroen Belien (Operations Management research group) and Prof. Estefanía Serral Asensio (Information Systems Engineering Research Group), with co-supervision from the Research center for fruit growing (pcfruit vzw). The research will be based at KU Leuven’s Faculty of Economics and Business, campus Brussels, and will integrate fundamental and applied expertise. The main objective is to develop practical prediction models for protected cultivation systems in soft fruit production, including strawberries, raspberries, and blackberries. The project adopts a results-oriented approach, combining sensor-based climate data analysis, model development, and real-world validation. Key research activities include simulating microclimate conditions using sensor data, developing and refining models for pest and fungal disease risks, and establishing relationships between outdoor weather and indoor microclimate conditions in various protected cropping systems (tunnels, rain shelters, greenhouses). Two modelling approaches will be explored: mechanistic (white-box) models using regression techniques, and data-driven (black-box) models such as neural networks to capture complex, non-linear interactions. Model interpretability will be enhanced using explainable AI techniques like SHAP, LIME, and ICE plots. The project also aims to integrate phenological models with AI approaches to predict pest occurrence and fungal infection risks, trained on field observations, sensor data, and crop development information, and validated through real-world case studies. The outcome will be robust, hybrid prediction systems that combine biological understanding with advanced AI methods, providing improved decision support for growers. The candidate may also guide Bachelor and Master students, participate in teaching, and supervise exams (maximum load 20%). The position offers a dynamic and pleasant working environment in Brussels and Leuven, with active involvement in international-level scientific research. Participation in seminars and international conferences is expected. Applicants should have a master’s degree in Engineering, Business Engineering, Mathematics, Data Science, Operations Research, Operations Management, Computer Science, Artificial Intelligence, or a similar field, with excellent academic results. Strong mathematical and programming skills, independent research ability, teamwork, and excellent English communication are required. Knowledge of Dutch is an asset but not mandatory. Enrollment in the PhD program (21 ECTS coursework) and limited teaching duties are expected. The offer includes a full-time PhD position for up to four years (subject to yearly positive evaluation), competitive salary (university scale 43), health and liability insurance, free public transport, access to sports and cultural facilities at special rates, Ecocheques, and numerous opportunities for personal growth, including conference participation and doctoral schools. KU Leuven provides a socially tolerant and inclusive environment, embracing diversity and equal opportunity. Applications should be submitted via KU Leuven’s online platform, including a letter of motivation, CV, and university diploma copies and transcripts. For further information, contact Prof. Jeroen Belien ([email protected]) or Prof. Estefanía Serral Asensio ([email protected]).

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Collaborators (6)

Yannis Bertrand

Assistant professor

Universiteit Hasselt

BELGIUM

Marcin Pietrasik

University of Maastricht

NETHERLANDS

Irene Vanderfeesten

Eindhoven University of Technology

NETHERLANDS

Ralph Bergmann

University of Trier

GERMANY

Marco Comuzzi

Associate Professor

Institute of Science and Technology

SOUTH KOREA

Anna Wilbik

University of Maastricht

NETHERLANDS
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