https://www.unibo.it/sitoweb/andrea.acquaviva/avvisi/it-IT� Copyright 2004-2026 - Universit� di Bologna9b1ba3b9https://www.unibo.it/sitoweb/andrea.acquaviva/avvisi/9b1ba3b9<p>Topic: Artificial Intelligence (AI) applied to Compilers</p> <ul> <li>Development of a <strong>stochastic deep neural networks</strong> for algorithm partitioning on <strong>heterogeneous compute units</strong></li> <li>Development of synthetic code benchmarks for training of <strong>deep neural networks</strong> for programming <strong>language modelling</strong></li> <li>Exploration and comparison of <strong>AI-based programming language modelling</strong> techniques </li> </ul> <p>Topic: IoT for Structural Health Monitoring (SHM)</p> <ul> <li>Development of a <strong>sensor placement</strong> technique for bridge SHM</li> <li>Study of <strong>AI capable sensor </strong>data fusion techniques for SHM</li> <li>Simulation of SHM systems with <strong>IoT Sensors-in-the-Loop</strong><br /> </li> </ul> <p>Topic: Brain-inspired computational models</p> <ul> <li>Brain-inspired <strong>Spiking Neural Network </strong>(SNN) models applied to monitoring of <strong>High Performance Computing (HPC) clusters</strong></li> <li>Study of <strong>SNN applied to monitoring of HPC clusters</strong> for anomaly detection </li> <li>Applying event based <strong>SNN models</strong> on time-series data from <strong>SHM sensors</strong></li> <li>Study of <strong>SNN learning models</strong> efficiency on <strong>neuromorphic platforms</strong></li> </ul>Sat, 04 Jul 2020 15:00:35 +02002020-07-04T17:44:20+02:00