Foto del docente

Michele Lombardi

Professore associato

Dipartimento di Informatica - Scienza e Ingegneria

Settore scientifico disciplinare: ING-INF/05 SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI

Didattica

Ultime tesi seguite dal docente

Tesi di Laurea

  • Asymmetries in Adversarial Settings
  • Pianificazione di attività per robot di collaudo tramite metodi di ottimizzazione combinatoria
  • Reti Neurali ed Equazioni Differenziali Ordinarie: una Rassegna

Tesi di Laurea Magistrale

  • A procedure for modular forecasting at scale with constraints for business time series
  • Artificial intelligence algorithms to support neuropsychologists in configuring cognitive stimulation exercises for Parkinsonian patients
  • Bank Transaction Reconciliation using Machine Learning Methods
  • Cryptomining detection on cloud environments through containerised application profiling and classification
  • Deep Learning and Constrained Optimization for Epidemic Control
  • Design and Analysis of a Gearbox Predictive Maintenance System
  • Empirical Model Learning for Constrained Black Box Optimization
  • Evaluation Metrics and Transfer Learning for Sales Prediction
  • Extending the Moving Targets Method for Injecting Constraints in Machine Learning
  • ICE Emissions Estimation through Machine-learning techniques to support real-world R&D experiments
  • Optimizing Pairs Trading Strategy via Deep Learning techniques and Technical Indicators: An empirical study on the S&P 500
  • Overcoming selection bias in the medical field: a case study on liver transplant
  • Promo Detection: Time Series Classification methods applied on CPG data
  • QAL-BP: An Augmented Lagrangian Quantum Approach for the Bin Packing Problem
  • Real-Time Pump and Dump Event Detection for Cryptocurrencies
  • Redesign of the Data Processing Pipeline for a Criminal Procedure Handling Problem
  • Smart sampling approaches for Decision-Focused Learning
  • Transformers Architectures for Time Series Forecasting
  • Trend Prediction in Financial Time Series: a Model and a Software Framework.

Ultimi avvisi

Al momento non sono presenti avvisi.