Last week, students from the third promotion of the Intelligent Field Robotic Systems (IFRoS) master’s program (2023-2025) had the privilege to participate in an advanced research training hosted at the Faculty of Electrical Engineering and Computing (FER) at the University of Zagreb (UNIZG). Taking place from December 9th to 12th, the seminar was part of the AeroSTREAM project and covered critical topics such as Non-Linear Model Predictive Control for Multi-Rotors, GNSS data fusion for Unmanned Aerial Systems, and solving vehicle routing problems using Google OR-Tools. The lectures and training sessions were delivered by experts from institutions and companies, including CATEC and SAXION/University of Twente. In addition to lectures, students engaged in hands-on training sessions that strengthened their expertise in aerial robotics and navigation systems.
The seminar proved to be a valuable opportunity for the IFRoS students to network with leading academics and researchers in robotics and aerospace technologies while deepening their practical and theoretical understanding of advanced robotics systems.
In parallel, the fourth promotion of IFRoS students (2024-2026), who are currently in their first year at the University of Girona, also participated in an enriching event. From December 10th to 12th, they attended a seminar on Explainable Artificial Intelligence (XAI), co-organized by Dr. Sebastian Lapuschkin (Head of the Explainable Artificial Intelligence at Fraunhofer Heinrich Hertz Institute (HHI) in Berlin) and Professor Rafael Garcia, University of Girona. This collaborative event included students from other prestigious programs such as the Master in Intelligent Robotic Systems (MIRS) and the Erasmus Mundus Joint master Degree in Medical Imaging and Application (MAIA).
The seminar emphasized the need for explainable AI in fostering trust, verification, legal compliance, and system improvement, while also providing hands-on practice for students. Explainable AI refers to techniques that make machine learning (ML) and artificial intelligence (AI) systems transparent and interpretable for humans. Unlike black-box models that deliver predictions without revealing their internal processes, XAI provides clear explanations, which are critical for ensuring trust, accountability, and fairness. It is particularly essential in sectors such as healthcare, finance, and autonomous vehicles, where understanding decisions is crucial. XAI not only supports legal and ethical compliance but also helps improve model performance by detecting biases and ensuring auditable decisions. Despite its benefits, XAI faces challenges, including the complexity of deep learning models, trade-offs between accuracy and interpretability, and scalability for large datasets. Nevertheless, as research progresses, XAI will play a pivotal role in developing trustworthy, ethical, and transparent AI systems.
Day 1 focused on introducing XAI, highlighting its motivation, and discussing the difference between “black-box” models and explainable AI systems, alongside a research outlook on emerging trends.
Days 2 and 3 shifted focuses to practical implementation, exploring the main approaches of XAI through hands-on training on different datasets. Students gained valuable insights into real-world applications of XAI methods and how these can be effectively applied to interpret model decisions.
These two initiatives demonstrate IFRoS’s dedication to providing state-of-the-art training and fostering collaborations with top experts in robotics and artificial intelligence. The program continues to equip its students with cutting-edge skills and experiences, preparing them to lead innovations in robotics and AI industries.
We would like to express our gratitude to all the invited scholars and organizers for his valuable time and dedicated efforts in making this seminar a resounding success.
Want to enjoy robotic and AI seminars like these and grow not only professionally but also personally? Join the IFRoS family!
IFRoS is a leading Europe-based master’s program designed to prepare the next generation of innovators in robotics, artificial intelligence, and aerospace, marine and self-driving technologies.
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