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Information on didactic, research and institutional assignments on this page are certified by the University; more information, prepared by the professor, are available on the personal web page and in the curriculum vitae indicated on this webpage.
Information on professor
ProfessorBaraldi Piero
QualificationFull professor full time
Belonging DepartmentDipartimento di Energia
Scientific-Disciplinary SectorING-IND/19 - Nuclear Power Plants
Curriculum VitaeDownload CV (772.8Kb - 13/04/2022)
OrcIDhttps://orcid.org/0000-0003-4232-4161

Contacts
Professor's office hours
DepartmentFloorOfficeDayTimetableTelephoneFaxNotes
energia----MondayFrom 15:00
To 17:00
6345----
E-mailpiero.baraldi@polimi.it
Professor's personal websitewww.lasar.polimi.it

Data source: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano

List of publications and reserach products for the year 2024
No product yet registered in the year 2024


List of publications and reserach products for the year 2023 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A Method based on Natural Language Processing for Periodically Estimating Variations of Performance of Safety Barriers in Hydrocarbon Production Assets (Show >>)
Exploiting Explanations to Detect Misclassifications of Deep Learning Models in Power Grid Visual Inspection (Show >>)
Optimization Method for an Improved Training of Physics Informed Neural Networks (Show >>)
Prediction of the Number of Defectives in a Production Batch of Semiconductor Devices (Show >>)
Journal Articles
Deep Multiadversarial Conditional Domain Adaptation Networks for Fault Diagnostics of Industrial Equipment (Show >>)
Guest Editorial: Special Issue of ESREL2020 PSAM15 (Show >>)
Maintenance optimization in industry 4.0 (Show >>)
Optimal operation and maintenance of energy storage systems in grid-connected microgrids by deep reinforcement learning (Show >>)
The Aramis Data Challenge to prognostics and health management methods for application in evolving environments (Show >>)


List of publications and reserach products for the year 2022 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Contributions on scientific books
Optimal Management of the Flow of Parts for Gas Turbines Maintenance by Reinforcement Learning and Artificial Neural Networks (Show >>)
Conference proceedings
A Taxonomy for Modelling Reports of Process Safety Events in the Oil and Gas Industry (Show >>)
An Unsupervised Method for Anomaly Detection in Multi-Stage Production Systems Based on LSTM Autoencoders (Show >>)
Estimation of the Case Temperature of Insulated Gate Bipolar Temperatures in Induction Cooktops by Deep Neural Network (Show >>)
Monitoring Degradation of Insulated Gate Bipolar Transistors in Induction Cooktops by Artificial Neural Networks (Show >>)
Prediction of the Remaining Useful Life of MOSFETs Used in Automotive Inverters by an Ensemble of Neural Networks (Show >>)
Wrapper Selection of Features for Fault Diagnostics of Truss Structures (Show >>)
Journal Articles
A Niching Augmented Evolutionary Algorithm for the Identification of Functional Dependencies in Complex Technical Infrastructures From Alarm Data (Show >>)
A Novel Metric to Evaluate the Association Rules for Identification of Functional Dependencies in Complex Technical Infrastructures (Show >>)
A dynamic event tree for a blowout accident in an oil deep-water well equipped with a managed pressure drilling condition monitoring and operation system (Show >>)
A framework based on Natural Language Processing and Machine Learning for the classification of the severity of road accidents from reports (Show >>)
A method for fault detection in multi-component systems based on sparse autoencoder-based deep neural networks (Show >>)
A novelty-based multi-objective evolutionary algorithm for identifying functional dependencies in complex technical infrastructures from alarm data (Show >>)
A two-stage estimation method based on Conceptors-aided unsupervised clustering and convolutional neural network classification for the estimation of the degradation level of industrial equipment (Show >>)
Deep Multi-adversarial Conditional Domain Adaptation Networks for Fault Diagnostics of Industrial Equipment (Show >>)
Generative Adversarial Networks With AdaBoost Ensemble Learning for Anomaly Detection in High-Speed Train Automatic Doors (Show >>)
Optimization of the Operation and Maintenance of renewable energy systems by Deep Reinforcement Learning (Show >>)


List of publications and reserach products for the year 2021 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A Method based on Gaussian Process Regression for Modelling Burn-in of Semiconductor Devices (Show >>)
A Natural Language Processing Method for the Identification of the Factors Influencing Road Accident Severity (Show >>)
Damage Detection in Truss Structures Supporting Pipelines and Auxiliary Equipment in Power Plants (Show >>)
Natural Language Processing and Bayesian Networks for the Analysis of Process Safety Events (Show >>)
Journal Articles
A machine learning-based methodology for multi-parametric solution of chemical processes operation optimization under uncertainty (Show >>)
A method for fault diagnosis in evolving environment using unlabeled data (Show >>)
A multi-branch deep neural network model for failure prognostics based on multimodal data (Show >>)
A novel association rule mining method for the identification of rare functional dependencies in Complex Technical Infrastructures from alarm data (Show >>)
A semi-supervised method for the characterization of degradation of nuclear power plants steam generators (Show >>)
Association rules extraction for the identification of functional dependencies in complex technical infrastructures (Show >>)
Bootstrapped ensemble of artificial neural networks technique for quantifying uncertainty in prediction of wind energy production (Show >>)
Deep reinforcement learning based on proximal policy optimization for the maintenance of a wind farm with multiple crews (Show >>)
Identification of critical components in the complex technical infrastructure of the large hadron collider using relief feature ranking and support vector machines (Show >>)


List of publications and reserach products for the year 2020 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A coevolutionary optimization approach with deep sparse autoencoder for the extraction of equipment degradation indicators (Show >>)
A method for inferring casual dependencies among abnormal behaviours of components in complex technical infrastructures (Show >>)
A methodology for the identification of the critical components of the electrical distribution network of cern’s large hadron collider (Show >>)
A novel degradation state indicator for steam generators of nuclear power plants (Show >>)
Agent-based modeling and reinforcement learning for optimizing energy systems operation and maintenance: the pathmind solution (Show >>)
An ensemble of echo state networks for predicting the energy production of wind plants (Show >>)
An unsupervised method for the reconstruction of maintenance intervention times (Show >>)
Data-driven extraction of association rules of dependent abnormal behaviour groups (Show >>)
Data-driven identification of critical components in complex technical infrastructures using Bayesian additive regression trees (Show >>)
Deep reinforcement learning for optimizing operation and maintenance of energy systems equipped with phm capabilities (Show >>)
Fault detection based on optimal transport theory (Show >>)
Fault diagnostics by conceptors-aided clustering (Show >>)
Fault prognostics in presence of event-based measurements (Show >>)
Multi-objective evolutionary algorithm for the identification of rare functional dependencies in complex technical infrastructures (Show >>)
Text mining for the automatic classification of road accident reports (Show >>)
The aramis data challenge: Prognostics and health management in evolving environments (Show >>)
Journal Articles
A Feature Selection-based Approach for the Identification of Critical Components in Complex Technical Infrastructures: Application to the CERN Large Hadron Collider (Show >>)
A Novel Concept Drift Detection Method for Incremental Learning in Nonstationary Environments (Show >>)
A data-driven framework for identifying important components in complex systems (Show >>)
A novel method for maintenance record clustering and its application to a case study of maintenance optimization (Show >>)
Challenges to IoT-Enabled Predictive Maintenance for Industry 4.0 (Show >>)
Dynamic Surrogate Modeling for Multistep-ahead Prediction of Multivariate Nonlinear Chemical Processes (Show >>)
Ensemble empirical mode decomposition and long short-term memory neural network for multi-step predictions of time series signals in nuclear power plants (Show >>)
Fault prognostics by an ensemble of Echo State Networks in presence of event based measurements (Show >>)
Industrial equipment reliability estimation: A Bayesian Weibull regression model with covariate selection (Show >>)
Partially observable Markov decision processes for optimal operations of gas transmission networks (Show >>)
manifesti v. 3.5.13 / 3.5.13
Area Servizi ICT
01/03/2024