Le nuove descrizioni dei corsi saranno pubblicate nel piano di studi ufficiale a partire da giugno 2025. Se quelle pagine sono ancora vuote, qui puoi trovare un elenco degli argomenti principali del corso.
Machine learning and neural networks
- Statistical learning
- Principal component analysis
- Deep convolutional neural networks and transformers
- Applications of deep learning
- State-space models and Kalman filter
Machine learning for health
- Review of linear algebra and basics on optimization methods.
- Regression techniques: linear regression applied to score of Parkinson's disease; lecture about Parkinson's disease.
- Clustering techniques: k-means, hierarchical trees, and DBSCAN applied to body images like CTScan or pictures of skin moles; lectures about teledermatology, MRI, CTScan, etc.
- Classification techniques: sensitivity, specificity, prevalence, incidence, ROC applied to tests based on blood markers; lecture about COVID.
- Decision trees and information theory applied to detection of Chronic Kidney Disease; lecture about Chronic Kidney Disease.
- Independent component analysis (ICA) applied to EEG; lectures about heart and brain physiology, EEG and ECG.
- Lectures about machine learning techniques in smart aging, fitness, lean in health care, management of emergencies.
Advanced machine learning for imaging and video
- Graph Neural Networks
- Transformer-based architectures
- Multimodal vision foundation models
- Neural networks for computational imaging (super-resolution, denoising, ...)
- Generative models for image and video synthesis (GANs, Denoising Diffusion Models)
- Continual learning and personalization of visual generative models (Finetuning, Adapters, LoRA, ...)
Satellite systems for positioning and maps
- Fundamentals of Satellite-Based Positioning, Navigation, and Timing (PNT)
- Global Navigation Satellite Systems (GNSS): Principles and Operation
- Sources of Measurement Errors and Data Uncertainty
- Overview of GNSS Systems and Signal Structures
- Architecture of GNSS Receivers
- Practical Applications with Real GNSS Measurements [Hands-on]
- Receiver State Estimation (Position and Velocity) [Hands-on]
- GNSS Positioning for Real-Time Applications
- Geodesy, Cartography, and Digital Mapping Data
- Mobile Mapping Systems (MMS): Concepts and Technologies
- Real-Time Kinematic (RTK) Surveying Techniques
- Data Processing, Error Mitigation, and Statistical Analysis
- Practical Examples in Geodesy and Cartography
Intelligent building optimisation
- Smart building: concepts, scenarios and technological solutions
- ICT optimisation techniques for building indoor environmental quality and energy savings
- White box, grey box, and black box modelling for the built environment supporting digital twins
- Surrogate modelling production and applications
- User comfort domains, GUI, smart sensoring and actuating, data gathering and elaborations
- Building Management System (BMS) and middleware platform development