Bio
Luigi Bibbò is a researcher affiliated with the University Mediterranea of Reggio Calabria, Italy, where he contributes to the DIIES department. With a Master’s degree in Electronic Engineering and a PhD focus on Artificial Intelligence and Neural Networks, his work spans cutting-edge fields including embedded intelligence, renewable energy systems, MEMS and IoT for health monitoring, and geomatics for landslide risk management. He has authored notable works such as 'The Silk, Versatile Material for Biological, Optical, and Electronic Fields: Review' and 'Neural Network Design using a Virtual Reality Platform,' reflecting his interdisciplinary expertise. Luigi has also held a post-doctoral researcher position at Shenzhen University in Optoelectronics Engineering, further broadening his international research experience. With a strong publication record and active involvement in engineering research, he continues to advance knowledge in electronic engineering and artificial intelligence applications.
Educational Journey
Mediterranea University of Reggio Calabria
Masterâ€TMs degree of Electronic Engineering • Artificial Intelligence, Neural Network
Experience
Reseacher
2019 - Present • DIIESPost-doc Researcher
2016 - Present • Optoelectronics EngineeringResearch
Neural Network Design using a Virtual Reality Platform
The evolution of Deep Learning (DL), a subset of machine learning, has made their use very effective in many artificial intelligence (AI) fields. In parallel Virtual Reality is going wide in many applications thanks to the proliferation of cameras in mobile devices and improved processing efficiency. Data visualization in deep learning is a fundamental element for which it can benefit from the advantages offered by the visualization of the VR for the development of the models. In addition, the researchers can widely use the editing of images and videos in the machine learning process to design a convolutional network suitable for image recognition. In this study, we want to demonstrate the usefulness of this approach in collecting data within virtual reality to train and optimize a convolutional neural network used to recognize human activities (HAR).
The Silk, Versatile Material for Biological, Optical, and Electronic Fields: Review
Silk, seen as a material, is a fiber made from silkworm cocoons and spiders. They have standard structural components and hierarchical structures. Different manufacturing techniques allow obtaining silk in films, fibers, hydrogels, microspheres, and sponges. We can tune the properties through the structure of secondary proteins. The paper explores the application in biomedical, optics, and electronic fields by analyzing the technological trend.
