Study and do research with us




Theses with international collaborations:

Theses on risk and resilience assessment of complex systems and critical infrastructures:

Guided probabilistic risk assessment of complex systems using reinforcement learning optimization (with UCLA, USA)

Resilience assessment and management of power grids in response to extreme weather conditions (heat wave, storm, flood, wildfire, etc.) (with UCLA, USA)

Development of a neural network for Critical Heat Flux predictions (with CEA, France)

Real-Time Condition-Informed Safety Assessment of a Microreactor (with MIT, USA)

Inverse Uncertainty Quantification with Deep Learning Surrogate Models of Accident Scenarios in Nuclear Microreactors (with MIT, USA)

Development of a Digital Twin of a Nuclear Microreactor: on the Multi-fidelity
Uncertainty Quantification (with MIT, USA)

Advanced methods of dynamic risk assessment for energy systems (with Leibniz University of Hannover, Germany)

Safety analysis of nuclear power plants: quantification of the uncertainty in nuclear thermal-hydraulic codes based on heterogeneous experimental data (ATRIUM Consortium)

Data adequacy assessment in thermal-hydraulic experimental tests of Intermediate Break Loss of Coolant Accident (IBLOCA) (ATRIUM Consortium)

Advanced uncertainty quantification models for the prediction of critical/safety parameters in nuclear power systems by artificial intelligence (EGMUP Task force on AI/ML)

Interpretability and explainability of artificial intelligence models for the prediction of the critical/safety parameters in nuclear power systems (EGMUP Task force on AI/ML)

Theses on reliability assessment:

Development and implementation of Tools for the Availability and Reliability Assessment of the CERN Complex Technical Infrastructure Systems (with CERN, Switzerland)

Theses on Prognostics and Health Management for Predictive Maintenance:

Artificial Intelligence-Based Prescriptive Maintenance by Federated Learning (with CNR and CERN)

Development of State-of-Health Indicators for Researchable Batteries Using Deep-Transfer Learning Methods (with Ecole Polytechnique, France)

Deep Transfer Learning Methods for Prognostics and Health Management (PHM) of Batteries (with Tsinghua University, China)

Theses with industrial partners (with possibility of stage)

Theses on risk and resilience assessment of complex systems and critical infrastructures:

Electrical network resilience (with ARAMIX Srl, Italy)

Benchmark of dynamic methods for Probabilistic Safety Assessment of nuclear power plants (EDF, Paris)

Theses on reliability assessment:

Theses on Prognostics and Health Management for Predictive Maintenance:

Analisi previsionale del possibile impatto dei cambiamenti climatici sull’efficienza tecnica e la resistenza strutturale degli impianti eolici e fotovoltaici (EDISON Spa) (con borsa di studio/ with scholarship)


Development of an Artificial Intelligence-based Virtual Meter Tool for Carbon Capture and Storage Applications (with ENI, Italy)

Theses internal at LASAR:

Theses on risk and resilience assessment of complex systems and critical infrastructures:

Large Language Models for Risk Assessment of Industrial Systems

Ecology network analysis methods for balancing efficiency and resilience of critical systems and infrastructures

Resilience of energy production plants exposed to Natural-Technological (Natech) scenarios of increasing frequency and severity in the climate change context

Methods for the evaluation and optimization of the resilience of systems, plants and infrastructures

Uncertainty quantification methods within the risk analysis of energy systems exposed to NaTech hazards and accident scenarios

Advanced methods for the risk assessment of industrial facilities and plants in the oil&gas and energy sectors

Climate change impact on the risk assessment of energy production plants

Enabling the Resilience of Integrated Energy Systems to Tsunami by Early Warning Hazard Nowcasting

Theses on Prognostics and Health Management for Predictive Maintenance:

Deep Learning Methods for Extracting Information from Text Documents in Prognostics and Health Management Applications

Development and implementation of diagnostic techniques for the classification of abnormal conditions in industrial plants using transparent rules

Physics-informed Neural Networks for Fault Prognostics of Equipment

Transfer Learning Methods for Reliability Predictions in Nuclear Power Systems

Development of eXplainable Artificial Intelligence (XAI) methods for time series analysis

Causality-Enhanced Artificial Intelligence for Explainable Predictive Maintenance in the Industry

Kolmogorov-Arnold Networks for Fault Diagnostics in Industrial Systems

Federated Learning Networks in Predictive Maintenance

Theses on Reliability Assessment

Graph Neural Networks for Predictions in Critical Infrastructures