Poster Presentation Contestants
Andrea Bondin
Industry 4.0 requires graduates with advanced problem-solving and creative skills. Traditional teaching often prioritises theory, leaving engineers unprepared for practical demands Education 4.0 addresses this with student-centered, hands-on learning.
This project validates a Mixed Reality Virtual Learning Factory framework. Bridging academia and industry equips students with the skills needed for Industry 4.0 and 5.0. The framework’s success ensures a strong foundation for future advancements in engineering education.
Andrea Bezzina
This poster presents an innovative initiative exploring the potential of integrating Metaverse and immersive technologies into engineering education. It highlights how virtual environments can enhance problem-solving, critical thinking, and engagement in engineering training. The poster presents the results of the initial investigation, which were gathered from surveys targeting both students and educators. The findings provide valuable insights into improving learning outcomes and adapting engineering education to modern technological advancements.
Alexander Pahlitzsch
TenneT is revolutionizing Europe's energy landscape by harnessing offshore wind power from the North Sea. This ambitious project involves overcoming significant challenges in transmitting wind energy across vast distances to the mainland. By employing cutting-edge technologies like high-voltage direct current (HVDC) systems and innovative platforms anchored to the seabed, TenneT ensures efficient and sustainable energy delivery. My passion for offshore operations drives my enthusiasm for these massive platforms and the intricate network of cables that symbolize a greener future for Europe. This poster aims to showcase how TenneT is powering Europe with the limitless energy of the wind and the remarkable engineering behind this transformation
Alexander Ciszewicz
Electrocardiogram (ECG) interpretation is a critical component of cardiovascular diagnostics, yet traditional methods remain susceptible to human error and variability. This study explores the integration of Convolutional Neural Networks (CNNs) for ECG classification alongside Large Language Models (LLMs) for further analytical interpretation. Using the ECG Heartbeat Categorisation Dataset for training and validation, the CNN is designed to classify ECG signals into five distinct categories, while the PTB-XL dataset serves as an independent testing set to evaluate generalization.​​
Janela Trexy Aquino
This project explores the development of the open-source design of OpenFish: Biomimetic design of a soft robotic fish for high-speed locomotion. The aim of this project is to enhance its autonomous versatility for marine conservation and underwater exploration. The original design successfully replicates thunniform propulsion using a combination of active and passive tail segments driven by a DC motor and gearbox system. However, its reliance on tethered power and control significantly restricts mobility, limiting its practical applications. To Address these limitations, this project integrates an onboard battery and a microcontroller, enabling untethered operation and adaptive control.
David Soyele
Learn more about the proper form one should use when performing the split squat exercise through Squat Form Analysis, using OpenCV and Python to obtain results.​​