Every year the PhD board proposes training activities for the benefit of the students; these courses are supported by Università degli Studi dell’Insubria.
Upcoming activities
- Topics in Low-Rank Factorization and Data Analysis
- Instructor: Giovanni Barbarino (University of Mons)
- Period: April 8, 10, 11, 15, and 17 (20 hours)
- Syllabus
- Generalized Locally Toeplitz Sequences: A Spectral Analysis Tool for Discretized Differential Equations
- Instructor: Carlo Garoni (Università di Roma Tor Vergata)
- Period: May 27th to June 7th, 2024 (20 hours), room V2.10
- Syllabus
- Introduction to Bayesian Statistics and (Markov Chain) Monte Carlo Simulation
- Instructor: Antonietta Mira (Università dell’Insubria and USI)
- Period: May 6th (9-13 and 14-16), May 7th & 15th (9-13 and 14-17), room V2.10
- Syllabus
- Early design of Internet of Things networks towards real deployment
- Instructor: Alessandra Rizzardi (Università dell’Insubria)
- Period: June 2024, 12 hours
- Description: The Internet of Things (IoT) is expanding at a rapid rate, and it is becoming increasingly important to understand how to early design and prototyping the network infrastructure and the related protocols and mechanisms, in order to promptly assess the performance (e.g., network and computational load, latency, storage occupancy, power consumption). In this way, the deployment phase can be improved and speeded up. The course, which will be entirely held in laboratory, practically explores the functionalities of an event-driven programming tool for wiring together hardware devices, APIs and online services in the IoT context. Also, security related requirements are investigated and integrated within the envisioned IoT architectures.
- Deep Learning for Signal and Image Processing
- Instructor: Ignazio Gallo (Università dell’Insubria)
- Period: June 2024, 16 hours
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Description: The course will present recent Deep Learning (DL) approaches for multi-dimensional signal processing and image analysis. Concerning traditional pattern recognition algorithms, DL methods have the advantage of automatically extracting distinctive data representations from multidimensional signals, thus reducing the need for domain expertise in a specific field.DL approaches represent the state of the art in several fields, such as industrial monitoring, medical imaging, biometric recognition, object classification, and ambient intelligence. However, choosing the best DL model for a specific application is still a challenging design aspect. The course will present an overview of a few DL approaches for signal and image processing, such as Convolutional Neural Networks, and Transformer Networks and some application examples for heterogenous scenarios.
Past activities
- Mathematics for Signal processing: New results and open challenges (A. Cicone, 12h, 2024)
- Topological Data Analysis (G. Bazzoni and M. Semplice, 21h, 2023)
- Advanced topics in cryptography (A. Trombetta, 12h, 2021)
- The Joint Spectral Radius Theoretical and numerical aspects and applications (A. Cicone, 16h, 2021)
- Early design of Internet of Things networks towards real deployment (A. Rizzardi, 12h, 2021)
- Graph-Laplacian and approximation of second-order linear differential operators (D. Bianchi, 12h, 2021)
- Nonlinear and nonstationary signal decomposition and analysis Theoretical and numerical aspects and applications (A. Cicone, 16h, 2020)
- Systems, Modelling, Simulations. Systems Thinking, Learning Organizations and System Dynamics Modeling analysis (H. Sedehi, 20h)
- (Markov chain) Monte Carlo simulation (A. Mira, 20h, 2019)
- Maximum Principle and Detours (I. Capuzzo, in collaboration with RISM)
- Regularization by filtering and variational methods: theoretical and numerical aspects (A. Buccini, 16h, 2019)
- Foundations of Modal Logic (A. Frigeri, 18h, 2019)
- Fractional diffusion equations: spectral study and design of fast iterative solvers (M. Mazza, 12h, 2019)
- Statistical Learning Theory and Applications (L. Rosasco and S. Villa, 12h, 2019)