On the response of nanoelectrode capacitive biosensors to DNA and PNA strands. - Federico Pittino; Federico Passerini; Pierpaolo Palestri; Luca Selmi; Frans Widdershoven (IWASI, 2013)

Numerical simulation of the position and orientation effects on the impedance response of nanoelectrode array biosensors to DNA and PNA strands. - Federico Pittino; Federico Passerini; Luca Selmi; Frans Widdershoven (Microelectron. J., 2014)

Prospects of nanoelectronic biosensing with high-frequency impedance spectroscopy. - Federico Pittino (2015)

Dealing with network changes in cellular fingerprint positioning systems. - Andrea Viel; Paolo Gallo; Angelo Montanari; Donatella Gubiani; Andrea Dalla Torre; Federico Pittino; Chris Marshall (ICL-GNSS, 2017)

A Scalable Framework for Online Power Modelling of High-Performance Computing Nodes in Production. - Federico Pittino; Francesco Beneventi; Andrea Bartolini; Luca Benini (HPCS, 2018)

Map matching with sparse cellular fingerprint observations. - Andrea Viel; Donatella Gubiani; Paolo Gallo; Angelo Montanari; Andrea Dalla Torre; Federico Pittino; Chris Marshall (UPINLBS, 2018)

Robust online identification of thermal models for in-production HPC clusters with machine learning-based data selection. - Federico Pittino; Roberto Diversi; Luca Benini; Andrea Bartolini (CoRR, 2018)

Positioning Indoors with LTE Communications Signals of Different Bandwidth. - Chris Marshall; Andrea Dalla Torre; Marco Driusso; Alessandro Pin; Federico Pittino; Roberto Rinaldo (IPIN, 2019)

Prediction of Time-to-Solution in Material Science Simulations Using Deep Learning. - Federico Pittino; Pietro Bonfà; Andrea Bartolini; Fabio Affinito; Luca Benini; Carlo Cavazzoni (PASC, 2019)

A map-matching algorithm dealing with sparse cellular fingerprint observations. - Andrea Dalla Torre; Paolo Gallo; Donatella Gubiani; Chris Marshall; Angelo Montanari; Federico Pittino; Andrea Viel (Geo spatial Inf. Sci., 2019)

An original approach to positioning with cellular fingerprints based on decision tree ensembles. - Andrea Viel; Andrea Brunello; Angelo Montanari; Federico Pittino (J. Locat. Based Serv., 2019)

Virtual Sensing of Temperatures in Indoor Environments: A Case Study. - Andrea Brunello; Martin Kraft; Angelo Montanari; Federico Pittino; Andrea Urgolo (ICDM (Workshops), 2020)

Automatic Anomaly Detection on In-Production Manufacturing Machines Using Statistical Learning Methods. - Federico Pittino; Michael Puggl; Thomas Moldaschl; Christina Hirschl (Sensors, 2020)

Robust Identification of Thermal Models for In-Production High-Performance-Computing Clusters With Machine Learning-Based Data Selection. - Federico Pittino; Roberto Diversi; Luca Benini; Andrea Bartolini (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

Virtual Sensing and Sensors Selection for Efficient Temperature Monitoring in Indoor Environments. - Andrea Brunello; Andrea Urgolo; Federico Pittino; András Montvay; Angelo Montanari (Sensors, 2021)

Statistical Methods for Degradation Estimation and Anomaly Detection in Photovoltaic Plants. - Vesna Dimitrievska; Federico Pittino; Wolfgang Mühleisen; Nicole Diewald; Markus Hilweg; András Montvay; Christina Hirschl (Sensors, 2021)

Hierarchical concept Bottleneck models for vision and their application to explainable fine classification and tracking. - Federico Pittino; Vesna Dimitrievska; Rudolf Heer (Eng. Appl. Artif. Intell., 2023)

Machine learning and data augmentation methods for multispectral capacitance images of nanoparticles with nanoelectrodes array biosensors. - Federico Lombardo; Federico Pittino; Daniele Goldoni; Luca Selmi (Eng. Appl. Artif. Intell., 2024)