Foto del docente

Michela Milano

Full Professor

Department of Computer Science and Engineering

Academic discipline: ING-INF/05 Information Processing Systems

Head of Centro Interdipartimentale Alma Mater Research Institute for Human-Centered Artificial Intelligence — (Alma AI)

Teaching

Recent dissertations supervised by the teacher.

First cycle degree programmes dissertations

  • Anomaly prediction with Temporal Convolutional Networks and Data Augmentation in High Performance Computing systems

Second cycle degree programmes dissertations

  • A Deep Learning approach for predicting COSMO-Model's execution time
  • A study on Automatic Lyrics Transcription and Synchronization using an end-to-end Automatic Speech Recognition architecture
  • Analisi di dati e sviluppo di modelli predittivi per sistemi di saldatura
  • Analysis of song lyrics' writing style for practical applications using machine learning
  • Anomaly detection su turbine eoliche tramite deep autoencoder
  • Anomaly Prediction in Production Supercomputer with Convolution and Semi-supervised autoencoder
  • Automated Configuration of Offline/Online Algorithms: an Empirical Model Learning Approach
  • Domain Adaptation and Fusion for Domain-Specific Traffic Sign Detection
  • Fault Detection in Industry 4.0 with Deep Learning Approaches
  • Integration of Local and Aggregated Optimization for the Virtual Management of Distributed Energy Resources
  • Lyrics Instrumentalness: An Automatic System for Vocal and Instrumental Recognition in Polyphonic Music with Deep Learning
  • Progettazione ed implementazione di una control room real time per i servizi di raccolta di una multiservizi
  • Realizzazione di un sistema per l'estrazione di articoli scientifici in base a query utente in linguaggio naturale
  • Robust optimization models for the characterization of customer flexibility: a case study on Virtual Power Plants.
  • Time series forecasting for smart waste management
  • Towards predictive maintenance in High Performance Computing using Deep autoencoder networks: a preliminary study on Marconi100 supercomputer
  • Tree ensemble methods for Predictive Maintenance: a case study

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