Electromagnetism, Electronics, Telecommunications and Interactive Cognitive Environments curriculum themes:
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- AI models for rehabilitation robotics (tutor Prof. P. Gastaldo)
- Edge/cloud big data management and machine learning (tutor Prof. R. Berta)
- Cybersecurity solutions for critical infrastructure (tutor Prof. M. Marchese)
- Machine learning for resource allocation in satellite networks (tutor Prof. F. Patrone)
- Energy Efficiency in the Beyond 5G edge-cloud continuum (tutor Prof. R. Bolla)
- Advanced Orchestration techniques for 5/6G Service-Based Meshes (tutor Prof. R. Bruschi)
- Simulations and experiments of electromagnetic problems involving biological tissues or materials in motion (tutor Prof. M. Raffetto)
- Design and development of new generation haptic interfaces for virtual touch (tutor Prof. L. Seminara)
- Novel inversion techniques for electromagnetic imaging and antenna diagnostics (tutor Prof. A. Randazzo)
- Human Machine Interface based on Electronic Skin for Upper-limb Prosthetics (tutor Prof. M. Valle)
- Probabilistic graphical models and machine learning methods for remote sensing image analysis (tutor Prof. B. Serpico, Prof. G. Moser)
- Data driven self-awareness models for AI enabled wireless communications (tutor Prof. C. Regazzoni, Prof. L. Marcenaro)
- Emergent and incremental collective-awareness in multiple heterogeneous autonomous agents (tutor Prof. C. Regazzoni, Prof. L. Marcenaro)
- Integrated circuits with scalable power supply voltages for wireless sensor nodes (WSN) powered by energy harvesters (tutor Prof. D. Caviglia, Prof. O. Aiello)
- CSI and AI based techniques for radio signals analysis in ambient intelligence applications (tutor Prof. A. Sciarrone)
- IoT solutions in e-Health applications for home assistance and care (tutor Prof. F. Lavagetto)
- Explainable Artificial Intelligence (tutor Prof. F. Bellotti)
- Architectures to support Machine Learning (tutor Prof. A. De Gloria)
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Computer Vision, Pattern Recognition and Machine Learning:
- Theme A: 3D scene understanding with geometrical and deep learning reasoning
- Theme B: Deep Learning for Multi-modal scene understanding
- Theme C: Self-Supervised and Unsupervised Deep Learning
- Theme D: Visual Reasoning with Knowledge and Graph Neural Networks for scene understanding