Peer Reviewed Publications

Books

Papers

2021

  • F. Venturini, U. Michelucci, and M. Baumgartner, “Implementation of multi-task learning neural network architectures for robust industrial optical sensing,” in Optical measurement systems for industrial inspection xii, 2021, p. 117822H.
    [BibTeX]
    @inproceedings{venturini2021implementation,
    title={Implementation of multi-task learning neural network architectures for robust industrial optical sensing},
    author={Venturini, Francesca and Michelucci, Umberto and Baumgartner, Michael},
    booktitle={Optical Measurement Systems for Industrial Inspection XII},
    volume={11782},
    pages={117822H},
    year={2021},
    organization={International Society for Optics and Photonics}
    }

  • F. Venturini, M. Sperti, U. Michelucci, I. Herzig, M. Baumgartner, J. P. Caballero, A. Jimenez, and M. A. Deriu, “Exploration of spanish olive oil quality with a miniaturized low-cost fluorescence sensor and machine learning techniques,” Foods, vol. 10, iss. 5, 2021. doi:10.3390/foods10051010
    [BibTeX] [Abstract] [Download PDF]

    Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud, for example through adulteration, creates new challenges and an increasing demand for developing new quality assessment methodologies that are easier and cheaper to perform. As of today, the determination of olive oil quality is performed by producers through chemical analysis and organoleptic evaluation. The chemical analysis requires advanced equipment and chemical knowledge of certified laboratories, and has therefore limited accessibility. In this work a minimalist, portable, and low-cost sensor is presented, which can perform olive oil quality assessment using fluorescence spectroscopy. The potential of the proposed technology is explored by analyzing several olive oils of different quality levels, EVOO, virgin olive oil (VOO), and lampante olive oil (LOO). The spectral data were analyzed using a large number of machine learning methods, including artificial neural networks. The analysis performed in this work demonstrates the possibility of performing the classification of olive oil in the three mentioned classes with an accuracy of 100%. These results confirm that this minimalist low-cost sensor has the potential to substitute expensive and complex chemical analysis.

    @Article{foods10051010,
    AUTHOR = {Venturini, Francesca and Sperti, Michela and Michelucci, Umberto and Herzig, Ivo and Baumgartner, Michael and Caballero, Josep Palau and Jimenez, Arturo and Deriu, Marco Agostino},
    TITLE = {Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques},
    JOURNAL = {Foods},
    VOLUME = {10},
    YEAR = {2021},
    NUMBER = {5},
    ARTICLE-NUMBER = {1010},
    URL = {https://www.mdpi.com/2304-8158/10/5/1010},
    PubMedID = {34066453},
    ISSN = {2304-8158},
    ABSTRACT = {Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud, for example through adulteration, creates new challenges and an increasing demand for developing new quality assessment methodologies that are easier and cheaper to perform. As of today, the determination of olive oil quality is performed by producers through chemical analysis and organoleptic evaluation. The chemical analysis requires advanced equipment and chemical knowledge of certified laboratories, and has therefore limited accessibility. In this work a minimalist, portable, and low-cost sensor is presented, which can perform olive oil quality assessment using fluorescence spectroscopy. The potential of the proposed technology is explored by analyzing several olive oils of different quality levels, EVOO, virgin olive oil (VOO), and lampante olive oil (LOO). The spectral data were analyzed using a large number of machine learning methods, including artificial neural networks. The analysis performed in this work demonstrates the possibility of performing the classification of olive oil in the three mentioned classes with an accuracy of 100%. These results confirm that this minimalist low-cost sensor has the potential to substitute expensive and complex chemical analysis.},
    DOI = {10.3390/foods10051010}
    }

  • G. Halasz, M. Sperti, M. Villani, U. Michelucci, P. Agostoni, A. Biagi, L. Rossi, A. Botti, C. Mari, M. Maccarini, and others, “A machine learning approach for mortality prediction in covid-19 pneumonia: development and evaluation of the piacenza score,” Journal of medical internet research, vol. 23, iss. 5, p. e29058, 2021.
    [BibTeX] [Download PDF]
    @article{halasz2021machine,
    title={A Machine Learning Approach for Mortality Prediction in COVID-19 Pneumonia: Development and Evaluation of the Piacenza Score},
    author={Halasz, Geza and Sperti, Michela and Villani, Matteo and Michelucci, Umberto and Agostoni, Piergiuseppe and Biagi, Andrea and Rossi, Luca and Botti, Andrea and Mari, Chiara and Maccarini, Marco and others},
    journal={Journal of Medical Internet Research},
    volume={23},
    number={5},
    pages={e29058},
    year={2021},
    publisher={JMIR Publications Inc., Toronto, Canada},
    URL={https://www.jmir.org/2021/5/e29058}
    }

  • U. Michelucci and F. Venturini, “Estimating neural network’s performance with bootstrap: a tutorial,” Machine learning and knowledge extraction, vol. 3, iss. 2, p. 357–373, 2021. doi:10.3390/make3020018
    [BibTeX] [Abstract] [Download PDF]

    Neural networks present characteristics where the results are strongly dependent on the training data, the weight initialisation, and the hyperparameters chosen. The determination of the distribution of a statistical estimator, as the Mean Squared Error (MSE) or the accuracy, is fundamental to evaluate the performance of a neural network model (NNM). For many machine learning models, as linear regression, it is possible to analytically obtain information as variance or confidence intervals on the results. Neural networks present the difficulty of not being analytically tractable due to their complexity. Therefore, it is impossible to easily estimate distributions of statistical estimators. When estimating the global performance of an NNM by estimating the MSE in a regression problem, for example, it is important to know the variance of the MSE. Bootstrap is one of the most important resampling techniques to estimate averages and variances, between other properties, of statistical estimators. In this tutorial, the application of resampling techniques (including bootstrap) to the evaluation of neural networks’ performance is explained from both a theoretical and practical point of view. The pseudo-code of the algorithms is provided to facilitate their implementation. Computational aspects, as the training time, are discussed, since resampling techniques always require simulations to be run many thousands of times and, therefore, are computationally intensive. A specific version of the bootstrap algorithm is presented that allows the estimation of the distribution of a statistical estimator when dealing with an NNM in a computationally effective way. Finally, algorithms are compared on both synthetically generated and real data to demonstrate their performance.

    @Article{make3020018,
    AUTHOR = {Michelucci, Umberto and Venturini, Francesca},
    TITLE = {Estimating Neural Network’s Performance with Bootstrap: A Tutorial},
    JOURNAL = {Machine Learning and Knowledge Extraction},
    VOLUME = {3},
    YEAR = {2021},
    NUMBER = {2},
    PAGES = {357--373},
    URL = {https://www.mdpi.com/2504-4990/3/2/18},
    ISSN = {2504-4990},
    ABSTRACT = {Neural networks present characteristics where the results are strongly dependent on the training data, the weight initialisation, and the hyperparameters chosen. The determination of the distribution of a statistical estimator, as the Mean Squared Error (MSE) or the accuracy, is fundamental to evaluate the performance of a neural network model (NNM). For many machine learning models, as linear regression, it is possible to analytically obtain information as variance or confidence intervals on the results. Neural networks present the difficulty of not being analytically tractable due to their complexity. Therefore, it is impossible to easily estimate distributions of statistical estimators. When estimating the global performance of an NNM by estimating the MSE in a regression problem, for example, it is important to know the variance of the MSE. Bootstrap is one of the most important resampling techniques to estimate averages and variances, between other properties, of statistical estimators. In this tutorial, the application of resampling techniques (including bootstrap) to the evaluation of neural networks’ performance is explained from both a theoretical and practical point of view. The pseudo-code of the algorithms is provided to facilitate their implementation. Computational aspects, as the training time, are discussed, since resampling techniques always require simulations to be run many thousands of times and, therefore, are computationally intensive. A specific version of the bootstrap algorithm is presented that allows the estimation of the distribution of a statistical estimator when dealing with an NNM in a computationally effective way. Finally, algorithms are compared on both synthetically generated and real data to demonstrate their performance.},
    DOI = {10.3390/make3020018}
    }

  • F.D’Ascenzo, D. O. Filippo, G. Gallone, G. Mittone, M. A. Deriu, M. Iannaccone, A. Ariza-Solé, C. Liebetrau, S. Manzano-Fernández, G. Quadri, T. Kinnaird, G. Campo, J. S. Henriques, J. Hughes, A. Dominguez-Rodriguez, M. Aldinucci, U. Morbiducci, G. Patti, S. Raposeiras-Roubin, E. Abu-Assi, D. G. M. Ferrari, F. Piroli, A. Saglietto, F. Conrotto, P. Omedé, A. Montefusco, M. Pennone, F. Bruno, P. P. Bocchino, G. Boccuzzi, E. Cerrato, F., O. Varbella, M. Sperti, S. B. Wilton, L. Velicki, I. Xanthopoulou, A. Cequier, A. Iniguez-Romo, M. I. Pousa, C. M. Fern, C. B. Queija, R. Cobas-Paz, A. Lopez-Cuenca, A. Garay, F. P. Blanco, A. Rognoni, B. G. Zoccai, S. Biscaglia, I. Nunez-Gil, T. Fujii, A., ro Durante, X. Song, T. Kawaji, D. Alexopoulos, Z. Huczek, J. R. G. Juanatey, S. -P. Nie, M. Kawashiri, I. Colonnelli, B. Cantalupo, R. Esposito, S. Leonardi, W. G. Marra, A. Chieffo, U. Michelucci, D. Piga, M. Malavolta, S. Gili, M. Mennuni, C. Montalto, L. O. Visconti, and Y. Arfat, “Machine learning-based prediction of adverse events following an acute coronary syndrome (praise): a modelling study of pooled datasets,” The lancet, vol. 397, iss. 10270, p. 199–207, 2021.
    [BibTeX] [Download PDF]
    @article{2021machine,
    title={Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets},
    author={F.D'Ascenzo and O. De Filippo and G. Gallone and G. Mittone and M.A. Deriu and M. Iannaccone and A. Ariza-Solé and C. Liebetrau and S. Manzano-Fernández and G. Quadri and T. Kinnaird and G. Campo and J. S. Henriques and J. Hughes and A. Dominguez-Rodriguez and M. Aldinucci and U. Morbiducci and G. Patti and S. Raposeiras-Roubin and E. Abu-Assi and G.M. De Ferrari and F. Piroli and A. Saglietto and F. Conrotto and P. Omedé and A. Montefusco and M. Pennone and F. Bruno and P. Paolo Bocchino and G. Boccuzzi and E. Cerrato and F. and O. Varbella and M. Sperti and S. B. Wilton and L. Velicki and I. Xanthopoulou and A. Cequier and A. Iniguez-Romo and I. Munoz Pousa and M. Cespon Fern and B. Caneiro Queija and R. Cobas-Paz and A. Lopez-Cuenca and A. Garay and P. Flores Blanco and A. Rognoni and G. Biondi Zoccai and S. Biscaglia and I. Nunez-Gil and T. Fujii and A. and ro Durante and X. Song and T. Kawaji and D. Alexopoulos and Z. Huczek and J. R. G. Juanatey and S.-P. Nie and M.-aki Kawashiri and I. Colonnelli and B. Cantalupo and R. Esposito and S. Leonardi and W. G. Marra and A. Chieffo and U. Michelucci and D. Piga and M. Malavolta and S. Gili and M. Mennuni and C. Montalto and L. O. Visconti and Y. Arfat},
    journal={The Lancet},
    volume={397},
    number={10270},
    pages={199--207},
    year={2021},
    url={https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)32519-8/fulltext}
    }

2020

  • U. Michelucci and F. Venturini, “New autonomous intelligent sensor design approach for multiple parameter inference,” Engineering proceedings, vol. 2, iss. 1, 2020. doi:10.3390/engproc2020002096
    [BibTeX] [Abstract] [Download PDF]

    The determination of multiple parameters via luminescence sensing is of great interest for many applications in different fields, like biosensing and biological imaging, medicine, and diagnostics. The typical approach consists in measuring multiple quantities and in applying complex and frequently just approximated mathematical models to characterize the sensor response. The use of machine learning to extract information from measurements in sensors have been tried in several forms before. But one of the problems with the approaches so far, is the difficulty in getting a training dataset that is representative of the measurements done by the sensor. Additionally, extracting multiple parameters from a single measurement has been so far an impossible problem to solve efficiently in luminescence. In this work a new approach is described for building an autonomous intelligent sensor, which is able to produce the training dataset self-sufficiently, use it for training a neural network, and then use the trained model to do inference on measurements done on the same hardware. For the first time the use of machine learning additionally allows to extract two parameters from one single measurement using multitask learning neural network architectures. This is demonstrated here by a dual oxygen concentration and temperature sensor.

    @Article{engproc2020002096,
    AUTHOR = {Michelucci, Umberto and Venturini, Francesca},
    TITLE = {New Autonomous Intelligent Sensor Design Approach for Multiple Parameter Inference},
    JOURNAL = {Engineering Proceedings},
    VOLUME = {2},
    YEAR = {2020},
    NUMBER = {1},
    ARTICLE-NUMBER = {96},
    URL = {https://www.mdpi.com/2673-4591/2/1/96},
    ISSN = {2673-4591},
    ABSTRACT = {The determination of multiple parameters via luminescence sensing is of great interest for many applications in different fields, like biosensing and biological imaging, medicine, and diagnostics. The typical approach consists in measuring multiple quantities and in applying complex and frequently just approximated mathematical models to characterize the sensor response. The use of machine learning to extract information from measurements in sensors have been tried in several forms before. But one of the problems with the approaches so far, is the difficulty in getting a training dataset that is representative of the measurements done by the sensor. Additionally, extracting multiple parameters from a single measurement has been so far an impossible problem to solve efficiently in luminescence. In this work a new approach is described for building an autonomous intelligent sensor, which is able to produce the training dataset self-sufficiently, use it for training a neural network, and then use the trained model to do inference on measurements done on the same hardware. For the first time the use of machine learning additionally allows to extract two parameters from one single measurement using multitask learning neural network architectures. This is demonstrated here by a dual oxygen concentration and temperature sensor.},
    DOI = {10.3390/engproc2020002096}
    }

  • F. Venturini, U. Michelucci, and M. Baumgartner, “Multi-task learning approach for optical luminescence sensing,” in Applied machine learning days (amld), lausanne, 25-29 january 2020, 2020.
    [BibTeX]
    @inproceedings{venturini2020multi,
    title={Multi-task learning approach for optical luminescence sensing},
    author={Venturini, Francesca and Michelucci, Umberto and Baumgartner, Michael},
    booktitle={Applied Machine Learning Days (AMLD), Lausanne, 25-29 January 2020},
    year={2020}
    }

  • F. Venturini, U. Michelucci, and M. Baumgartner, “Dual oxygen and temperature sensing with single indicator using multi-task-learning neural networks,” in Optical sensing and detection vi, 2020, p. 113541C.
    [BibTeX] [Download PDF]
    @inproceedings{venturini2020dual,
    title={Dual oxygen and temperature sensing with single indicator using multi-task-learning neural networks},
    author={Venturini, Francesca and Michelucci, Umberto and Baumgartner, Michael},
    booktitle={Optical Sensing and Detection VI},
    volume={11354},
    pages={113541C},
    year={2020},
    organization={International Society for Optics and Photonics},
    url={https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11354/113541C/Dual-oxygen-and-temperature-sensing-with-single-indicator-using-multi/10.1117/12.2554941.short}
    }

  • F. Venturini, U. Michelucci, and M. Baumgartner, “Dual oxygen and temperature luminescence learning sensor with parallel inference,” Sensors, vol. 20, iss. 17, p. 4886, 2020.
    [BibTeX] [Download PDF]
    @article{venturini2020dual,
    title={Dual oxygen and temperature luminescence learning sensor with parallel inference},
    author={Venturini, Francesca and Michelucci, Umberto and Baumgartner, Michael},
    journal={Sensors},
    volume={20},
    number={17},
    pages={4886},
    year={2020},
    publisher={Multidisciplinary Digital Publishing Institute},
    url={https://www.mdpi.com/1424-8220/20/17/4886/pdf}
    }

  • F. Venturini, U. Michelucci, and M. Baumgartner, “Deep-learning for multi-parameter luminescence sensing: demonstration of dual sensor,” in Frontiers in optics, 2020, p. FTu2B–5.
    [BibTeX] [Download PDF]
    @inproceedings{venturini2020deep,
    title={Deep-learning for multi-parameter luminescence sensing: demonstration of dual sensor},
    author={Venturini, Francesca and Michelucci, Umberto and Baumgartner, Michael},
    booktitle={Frontiers in Optics},
    pages={FTu2B--5},
    year={2020},
    organization={Optical Society of America},
    url={https://www.osapublishing.org/viewmedia.cfm?uri=FiO-2020-FTu2B.5&seq=0}
    }

  • F. Venturini, Pär. Bergström, and M. Hertel, Gas measurement systemGoogle patents, 2020.
    [BibTeX]
    @misc{venturini2020gas,
    title={Gas measurement system },
    author={Venturini, Francesca and Bergstr{\"o}m, P{\"a}r and Hertel, Martin},
    year={2020},
    month=mar # "~5",
    publisher={Google Patents},
    note={US Patent App. 16/677,769}
    }

2019

  • U. Michelucci, M. Baumgartner, and F. Venturini, “Optical oxygen sensing with artificial intelligence,” Sensors, vol. 19, iss. 4, p. 777, 2019.
    [BibTeX] [Download PDF]
    @article{michelucci2019optical,
    title={Optical oxygen sensing with artificial intelligence},
    author={Michelucci, Umberto and Baumgartner, Michael and Venturini, Francesca},
    journal={Sensors},
    volume={19},
    number={4},
    pages={777},
    year={2019},
    publisher={Multidisciplinary Digital Publishing Institute},
    url={https://www.mdpi.com/1424-8220/19/4/777/pdf}
    }

  • F. Venturini, M. Baumgartner, and U. Michelucci, “New approach for luminescence sensing based on machine learning,” in Optical data science ii, 2019, p. 109370H.
    [BibTeX] [Download PDF]
    @inproceedings{venturini2019new,
    title={New approach for luminescence sensing based on machine learning},
    author={Venturini, Francesca and Baumgartner, Michael and Michelucci, Umberto},
    booktitle={Optical Data Science II},
    volume={10937},
    pages={109370H},
    year={2019},
    organization={International Society for Optics and Photonics},
    url={https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10937/109370H/New-approach-for-luminescence-sensing-based-on-machine-learning/10.1117/12.2508969.short}
    }

  • U. Michelucci, Advanced applied deep learning: convolutional neural networks and object detection, Apress, 2019.
    [BibTeX] [Download PDF]
    @book{michelucci2019advanced,
    title={Advanced applied deep learning: convolutional neural networks and object detection},
    author={Michelucci, Umberto},
    year={2019},
    publisher={Apress},
    url={https://www.apress.com/gp/book/9781484249758}
    }

  • U. Michelucci and F. Venturini, “Multi-task learning for multi-dimensional regression: application to luminescence sensing,” Applied sciences, vol. 9, iss. 22, p. 4748, 2019.
    [BibTeX] [Download PDF]
    @article{michelucci2019multi,
    title={Multi-task learning for multi-dimensional regression: application to luminescence sensing},
    author={Michelucci, Umberto and Venturini, Francesca},
    journal={Applied Sciences},
    volume={9},
    number={22},
    pages={4748},
    year={2019},
    publisher={Multidisciplinary Digital Publishing Institute},
    url={https://www.mdpi.com/2076-3417/9/22/4748/pdf}
    }

2018

  • U. Michelucci, Applied deep learning, Apress, 2018.
    [BibTeX] [Download PDF]
    @book{michelucci2018applied,
    title={Applied Deep Learning},
    author={Michelucci, Umberto},
    journal={A Case-Based Approach to Understanding Deep Neural Networks},
    year={2018},
    publisher={APRESS},
    url={https://www.apress.com/gp/book/9781484237892}
    }

  • N. Chelwani, A. Baum, T. Böhm, M. Opel, F. Venturini, L. Tassini, A. Erb, H. Berger, L. Forró, and R. Hackl, “Magnetic excitations and amplitude fluctuations in insulating cuprates,” Physical review b, vol. 97, iss. 2, p. 24407, 2018.
    [BibTeX]
    @article{chelwani2018magnetic,
    title={Magnetic excitations and amplitude fluctuations in insulating cuprates},
    author={Chelwani, Nitin and Baum, Andreas and B{\"o}hm, Thomas and Opel, Matthias and Venturini, Francesca and Tassini, Leonardo and Erb, Andreas and Berger, Helmuth and Forr{\'o}, L{\'a}szl{\'o} and Hackl, Rudi},
    journal={Physical Review B},
    volume={97},
    number={2},
    pages={024407},
    year={2018},
    publisher={APS}
    }

  • F. Venturini, M. Baumgartner, and S. M. Borisov, “Mn4+-doped magnesium titanate—a promising phosphor for self-referenced optical temperature sensing,” Sensors, vol. 18, iss. 2, p. 668, 2018.
    [BibTeX]
    @article{venturini2018mn4+,
    title={Mn4+-Doped Magnesium Titanate—A Promising Phosphor for Self-Referenced Optical Temperature Sensing},
    author={Venturini, Francesca and Baumgartner, Michael and Borisov, Sergey M},
    journal={Sensors},
    volume={18},
    number={2},
    pages={668},
    year={2018},
    publisher={Multidisciplinary Digital Publishing Institute}
    }

  • F. Venturini, M. Baumgartner, and S. Borisov, “New opportunities for optical temperature sensing with mn4+-doped magnesium titanate,” in Bragg gratings, photosensitivity and poling in glass waveguides and materials, 2018, p. JTu2A–63.
    [BibTeX]
    @inproceedings{venturini2018new,
    title={New Opportunities for Optical Temperature Sensing with Mn4+-Doped Magnesium Titanate},
    author={Venturini, F and Baumgartner, M and Borisov, SM},
    booktitle={Bragg Gratings, Photosensitivity and Poling in Glass Waveguides and Materials},
    pages={JTu2A--63},
    year={2018},
    organization={Optical Society of America}
    }

  • M. Fischer, L. Ulmer, and F. Venturini, Optochemical sensorGoogle patents, 2018.
    [BibTeX]
    @misc{fischer2018optochemical,
    title={Optochemical sensor},
    author={Fischer, Milan and Ulmer, Lilya and Venturini, Francesca},
    year={2018},
    month=jun # "~14",
    publisher={Google Patents},
    note={US Patent App. 15/834,359}
    }

2017

  • U. Michelucci and F. Venturini, “Novel semi-parametric algorithm for interference-immune tunable absorption spectroscopy gas sensing,” Sensors, vol. 17, iss. 10, p. 2281, 2017.
    [BibTeX]
    @article{michelucci2017novel,
    title={Novel semi-parametric algorithm for interference-immune tunable absorption spectroscopy gas Sensing},
    author={Michelucci, Umberto and Venturini, Francesca},
    journal={Sensors},
    volume={17},
    number={10},
    pages={2281},
    year={2017},
    publisher={Multidisciplinary Digital Publishing Institute}
    }

  • F. Venturini and U. Michelucci, “Novel algorithm for calibration-free absorption spectroscopy sensor,” Multidisciplinary digital publishing institute proceedings, vol. 1, iss. 8, p. 833, 2017.
    [BibTeX]
    @article{venturini2017novel,
    title={Novel Algorithm for Calibration-Free Absorption Spectroscopy Sensor},
    author={Venturini, Francesca and Michelucci, Umberto},
    journal={Multidisciplinary Digital Publishing Institute Proceedings},
    volume={1},
    number={8},
    pages={833},
    year={2017}
    }

  • F. Venturini, V. Schönherr, J. Rey, and E. Adolfsson, “Characterization of strongly scattering nanoporous materials as miniaturized multipass cell for tunable diode laser absorption spectroscopy,” Applied physics b, vol. 123, iss. 4, p. 136, 2017.
    [BibTeX]
    @article{venturini2017characterization,
    title={Characterization of strongly scattering nanoporous materials as miniaturized multipass cell for tunable diode laser absorption spectroscopy},
    author={Venturini, F and Sch{\"o}nherr, V and Rey, JM and Adolfsson, Erik},
    journal={Applied Physics B},
    volume={123},
    number={4},
    pages={136},
    year={2017},
    publisher={Springer}
    }

  • F. Venturini, V. Schönherr, J. Rey, and E. Adolfsson, “Characterization of light-gas interaction in strongly-scattering nanoporous materials and its implications for tunable diode laser absorption spectroscopy,” Applied physics b, vol. 123, iss. 4, p. 123–136, 2017.
    [BibTeX]
    @article{venturini2017characterization,
    title={Characterization of light-gas interaction in strongly-scattering nanoporous materials and its implications for tunable diode laser absorption spectroscopy},
    author={Venturini, Francesca and Sch{\"o}nherr, Veit and Rey, Julien and Adolfsson, Erik},
    journal={Applied Physics B},
    volume={123},
    number={4},
    pages={123--136},
    year={2017},
    publisher={Springer}
    }

  • F. Venturini, V. Schönherr, and E. Adolfsson, “Ultracompact oxygen sensor using nanoporous materials as stronglyscattering multipass cell for tunable diode laser absorption spectroscopy,” in The european conference on lasers and electro-optics, 2017, p. CH_P_40.
    [BibTeX]
    @inproceedings{venturini2017ultracompact,
    title={Ultracompact oxygen sensor using nanoporous materials as stronglyscattering multipass cell for tunable diode laser absorption spectroscopy},
    author={Venturini, Francesca and Sch{\"o}nherr, Veit and Adolfsson, Erik},
    booktitle={The European Conference on Lasers and Electro-Optics},
    pages={CH\_P\_40},
    year={2017},
    organization={Optical Society of America}
    }

2016

  • E. Adolfsson, F. Venturini, V. Schönherr, and J. Rey, “Characterization oflight-gas interaction in strongly-scattering nanoporous materials and itsimplications for tunable diode laser absorption spectroscopy,” in 5th international conference: field laser applications in industry and research 2016 (flair 2016), september 12-16, 2016, aix-les-bains, france, 2016, p. 123–136.
    [BibTeX]
    @inproceedings{adolfsson2016characterization,
    title={Characterization oflight-gas interaction in strongly-scattering nanoporous materials and itsimplications for tunable diode laser absorption spectroscopy},
    author={Adolfsson, Erik and Venturini, Francesca and Sch{\"o}nherr, Veit and Rey, Julien},
    booktitle={5th International Conference: Field Laser Applications in Industry and Research 2016 (FLAIR 2016), September 12-16, 2016, Aix-les-Bains, France},
    volume={123},
    pages={123--136},
    year={2016}
    }

2015

  • F. Venturini, R. Buergi, S. Borisov, and I. Klimant, “Optical temperature sensing using a new thermographic phosphor,” Sensors and actuators a: physical, vol. 233, p. 324–329, 2015.
    [BibTeX]
    @article{venturini2015optical,
    title={Optical temperature sensing using a new thermographic phosphor},
    author={Venturini, F and Buergi, R and Borisov, SM and Klimant, I},
    journal={Sensors and Actuators A: Physical},
    volume={233},
    pages={324--329},
    year={2015},
    publisher={Elsevier}
    }

  • S. Borisov, I. Klimant, R. Bürgi, and F. Venturini, “Temperature sensing and sensor design using a new thermographic phosphor for a wide range of applications,” in 2015 european conference on lasers and electro-optics & european quantum electronics conference, 21–25 june 2015, 2015.
    [BibTeX]
    @inproceedings{borisov2015temperature,
    title={Temperature sensing and sensor design using a new thermographic phosphor for a wide range of applications},
    author={Borisov, Sergey and Klimant, Ingo and B{\"u}rgi, Ren{\'e} and Venturini, Francesca},
    booktitle={2015 European Conference on Lasers and Electro-Optics \& European Quantum Electronics Conference, 21--25 June 2015},
    year={2015},
    organization={Optical Society of America}
    }

  • C. Vanoni, F. Venturini, and C. Kleinlogel, Method of operating an optochemical sensorGoogle patents, 2015.
    [BibTeX]
    @misc{vanoni2015method,
    title={Method of operating an optochemical sensor},
    author={Vanoni, Claudio and Venturini, Francesca and Kleinlogel, Christoph},
    year={2015},
    month=aug # "~11",
    publisher={Google Patents},
    note={US Patent 9,103,795}
    }

  • S. Borisov, I. Klimant, V. Schönherr, R. Bürgi, and F. Venturini, “Investigation of the luminescence emission of chromium (iii)-doped yttrium aluminum borate for the design of an optical temperature sensor,” in Maf 14, the 14th conference on methods and applications in fluorescence, würzburg, germany, 13-16 september 2015, 2015.
    [BibTeX]
    @inproceedings{borisov2015investigation,
    title={Investigation of the Luminescence Emission of Chromium (III)-Doped Yttrium Aluminum Borate for the Design of an Optical Temperature Sensor},
    author={Borisov, Sergey and Klimant, Ingo and Sch{\"o}nherr, Veit and B{\"u}rgi, Ren{\'e} and Venturini, Francesca},
    booktitle={MAF 14, The 14th Conference on Methods and Applications in Fluorescence, W{\"u}rzburg, Germany, 13-16 September 2015},
    year={2015}
    }

  • F. Venturini, R. Bürgi, S. Borisov, and I. Klimant, “Temperature sensing and sensor design using a new thermographic phosphor for a wide range of applications,” in The european conference on lasers and electro-optics, 2015, p. CH_P_31.
    [BibTeX]
    @inproceedings{venturini2015temperature,
    title={Temperature Sensing and Sensor Design Using a New Thermographic Phosphor for a Wide Range of Applications},
    author={Venturini, F and B{\"u}rgi, R and Borisov, S and Klimant, I},
    booktitle={The European Conference on Lasers and Electro-Optics},
    pages={CH\_P\_31},
    year={2015},
    organization={Optical Society of America}
    }

2014

  • E. Dumont, H. Fuchs, W. Maurer, and F. Venturini, “From forces of nature to the physics of dynamical systems,” in The 9th international conference on conceptual change, bologna, italy, 2014.
    [BibTeX]
    @inproceedings{dumont2014forces,
    title={From forces of nature to the physics of dynamical systems},
    author={Dumont, Elisabeth and Fuchs, HU and Maurer, W and Venturini, F},
    booktitle={The 9th international conference on conceptual change, Bologna, Italy},
    year={2014}
    }

2013

  • M. Allgäuer, P. Ehrismann, D. Meier, J. Ufheil, M. Vayhinger, and F. Venturini, Sensor unit utilizing a clamping mechanismGoogle patents, 2013.
    [BibTeX]
    @misc{allgauer2013sensor,
    title={Sensor unit utilizing a clamping mechanism},
    author={Allg{\"a}uer, Mario and Ehrismann, Philippe and Meier, Dario and Ufheil, Joachim and Vayhinger, Marcus and Venturini, Francesca},
    year={2013},
    month=jun # "~13",
    publisher={Google Patents},
    note={US Patent App. 13/414,494}
    }

2011

  • N. Munnikes, B. Muschler, F. Venturini, L. Tassini, W. Prestel, S. Ono, Y. Ando, D. Peets, W. Hardy, R. Liang, and others, “Pair breaking versus symmetry breaking: origin of the raman modes in superconducting cuprates,” Physical review b, vol. 84, iss. 14, p. 144523, 2011.
    [BibTeX]
    @article{munnikes2011pair,
    title={Pair breaking versus symmetry breaking: Origin of the Raman modes in superconducting cuprates},
    author={Munnikes, N and Muschler, B and Venturini, Francesca and Tassini, L and Prestel, W and Ono, Shimpei and Ando, Yoichi and Peets, DC and Hardy, WN and Liang, Ruixing and others},
    journal={Physical Review B},
    volume={84},
    number={14},
    pages={144523},
    year={2011},
    publisher={APS}
    }

  • B. Muschler, N. Munnikes, F. Venturini, L. Tassini, W. Prestel, A. Erb, R. Hackl, S. Ono, Y. Ando, A. Damascelli, and others, “The energy scale in the cuprates: a raman study,” Verhandlungen der deutschen physikalischen gesellschaft, 2011.
    [BibTeX]
    @article{muschler2011energy,
    title={The energy scale in the cuprates: a Raman study},
    author={Muschler, B and Munnikes, N and Venturini, F and Tassini, L and Prestel, W and Erb, A and Hackl, R and Ono, Shimpei and Ando, Yoichi and Damascelli, A and others},
    journal={Verhandlungen der Deutschen Physikalischen Gesellschaft},
    year={2011}
    }

2010

  • W. Prestel, F. Venturini, B. Muschler, I. Tütto, R. Hackl, M. Lambacher, A. Erb, S. Komiya, S. Ono, Y. Ando, and others, “Quantitative comparison of single-and two-particle properties in the cuprates,” The european physical journal special topics, vol. 188, iss. 1, p. 163–171, 2010.
    [BibTeX]
    @article{prestel2010quantitative,
    title={Quantitative comparison of single-and two-particle properties in the cuprates},
    author={Prestel, W and Venturini, Francesca and Muschler, B and T{\"u}tto, I and Hackl, R and Lambacher, M and Erb, A and Komiya, Seiki and Ono, Shimpei and Ando, Yoichi and others},
    journal={The European Physical Journal Special Topics},
    volume={188},
    number={1},
    pages={163--171},
    year={2010},
    publisher={Springer}
    }

2009

  • F. Venturini, R. Schauwecker, and P. Bovier, Superconducting magnet arrangement with hysteresis free field coilGoogle patents, 2009.
    [BibTeX]
    @misc{venturini2009superconducting,
    title={Superconducting magnet arrangement with hysteresis free field coil},
    author={Venturini, Francesca and Schauwecker, Robert and Bovier, Pierre-Alain},
    year={2009},
    month=jul # "~28",
    publisher={Google Patents},
    note={US Patent 7,567,158}
    }

2008

  • F. Venturini, P. Mock, and R. Schauwecker, Horizontal magnet arrangement with radial accessGoogle patents, 2008.
    [BibTeX]
    @misc{venturini2008horizontal,
    title={Horizontal magnet arrangement with radial access},
    author={Venturini, Francesca and Mock, Patrick and Schauwecker, Robert},
    year={2008},
    month=sep # "~18",
    publisher={Google Patents},
    note={US Patent App. 12/076,093}
    }

2006

  • R. Hackl, L. Tassini, F. Venturini, A. Erb, C. Hartinger, N. Kikugawa, and T. Fujita, “Raman study of ordering phenomena in copper–oxygen systems,” Journal of physics and chemistry of solids, vol. 67, iss. 1-3, p. 289–293, 2006.
    [BibTeX]
    @article{hackl2006raman,
    title={Raman study of ordering phenomena in copper--oxygen systems},
    author={Hackl, R and Tassini, L and Venturini, F and Erb, A and Hartinger, Ch and Kikugawa, N and Fujita, T},
    journal={Journal of Physics and Chemistry of Solids},
    volume={67},
    number={1-3},
    pages={289--293},
    year={2006},
    publisher={Elsevier}
    }

2005

  • R. Hackl, L. Tassini, F. Venturini, C. Hartinger, A. Erb, N. Kikugawa, and T. Fujita, “Advances in solid state physics,” , 2005.
    [BibTeX]
    @article{hackl2005advances,
    title={Advances in Solid State Physics},
    author={Hackl, R and Tassini, L and Venturini, F and Hartinger, C and Erb, A and Kikugawa, N and Fujita, T},
    year={2005},
    publisher={Springer-Verlag}
    }

  • R. Hackl, L. Tassini, F. Venturini, C. Hartinger, A. Erb, N. Kikugawa, and T. Fujita, “Ordering phenomena in cuprates,” in Advances in solid state physics, Springer, 2005, p. 227–238.
    [BibTeX]
    @incollection{hackl2005ordering,
    title={Ordering Phenomena in Cuprates},
    author={Hackl, Rudi and Tassini, Leonardo and Venturini, Francesca and Hartinger, Christine and Erb, Andreas and Kikugawa, Naoki and Fujita, Toshitsu},
    booktitle={Advances in Solid State Physics},
    pages={227--238},
    year={2005},
    publisher={Springer}
    }

  • L. Tassini, F. Venturini, R. Hackl, A. Erb, Q. Zhang, N. Kikugawa, and T. Fujita, “Raman scattering from charge ordering fluctuations in cuprates,” Verhandlungen der deutschen physikalischen gesellschaft, vol. 40, iss. 2, p. 590, 2005.
    [BibTeX]
    @article{tassini2005raman,
    title={Raman scattering from charge ordering fluctuations in cuprates},
    author={Tassini, L and Venturini, F and Hackl, R and Erb, A and Zhang, Qing-Ming and Kikugawa, N and Fujita, T},
    journal={Verhandlungen der Deutschen Physikalischen Gesellschaft},
    volume={40},
    number={2},
    pages={590},
    year={2005}
    }

  • L. Tassini, F. Venturini, Q-M. Zhang, R. Hackl, N. Kikugawa, and T. Fujita, “Dynamical properties of charged stripes in la 2- x sr x cuo 4,” Physical review letters, vol. 95, iss. 11, p. 117002, 2005.
    [BibTeX]
    @article{tassini2005dynamical,
    title={Dynamical properties of charged stripes in La 2- x Sr x CuO 4},
    author={Tassini, L and Venturini, Francesca and Zhang, Q-M and Hackl, R and Kikugawa, N and Fujita, T},
    journal={Physical review letters},
    volume={95},
    number={11},
    pages={117002},
    year={2005},
    publisher={APS}
    }

2004

  • L. Tassini, F. Venturini, R. Hackl, Q. Zhang, N. Kikugawa, and F. Toshizo, “Raman study of charge ordering in la_2-xsr_xcuo_4,” Aps, vol. 2004, p. U14–009, 2004.
    [BibTeX]
    @article{tassini2004raman,
    title={Raman study of charge ordering in La\_2-xSr\_xCuO\_4},
    author={Tassini, Leonardo and Venturini, Francesca and Hackl, Rudi and Zhang, Qing-Ming and Kikugawa, Naoki and Toshizo, Fujita},
    journal={APS},
    volume={2004},
    pages={U14--009},
    year={2004}
    }

  • R. Hackl, F. Venturini, L. Tassini, A. Erb, T. P. Devereaux, I. Tüttö, and B. Revaz, “Evidence for a metal-insulator transition in overdoped cuprates: new raman results,” Aps, vol. 2004, p. K1–184, 2004.
    [BibTeX]
    @article{hackl2004evidence,
    title={Evidence for a metal-insulator transition in overdoped cuprates: new Raman results},
    author={Hackl, Rudi and Venturini, Francesca and Tassini, Leonardo and Erb, Andreas and Devereaux, Thomas P and T{\"u}tt{\"o}, Istv{\'a}n and Revaz, Bernard},
    journal={APS},
    volume={2004},
    pages={K1--184},
    year={2004}
    }

2003

  • F. Venturini, R. Hackl, and U. Michelucci, “Comment on “nonmonotonic d x 2- y 2 superconducting order parameter in n d 2- x c e x c u o 4”,” Physical review letters, vol. 90, iss. 14, p. 149701, 2003.
    [BibTeX]
    @article{venturini2003comment,
    title={Comment on “Nonmonotonic d x 2- y 2 Superconducting Order Parameter in N d 2- x C e x C u O 4”},
    author={Venturini, Francesca and Hackl, R and Michelucci, U},
    journal={Physical review letters},
    volume={90},
    number={14},
    pages={149701},
    year={2003},
    publisher={American Physical Society}
    }

  • Q. Zhang, F. Venturini, R. Hackl, J. Hori, and T. Fujita, “New electronic raman scattering results in underdoped la2- xsrxcuo4,” Physica c: superconductivity, vol. 386, p. 282–285, 2003.
    [BibTeX]
    @article{zhang2003new,
    title={New electronic Raman scattering results in underdoped La2- xSrxCuO4},
    author={Zhang, Qingming and Venturini, Francesca and Hackl, Rudi and Hori, Jun’ya and Fujita, Toshizo},
    journal={Physica C: Superconductivity},
    volume={386},
    pages={282--285},
    year={2003},
    publisher={Elsevier}
    }

  • F. Venturini, “Evidence for a metal-insulator transition in overdoped cuprates: new raman results,” in Advances in solid state physics, Springer, 2003, p. 253–266.
    [BibTeX]
    @incollection{venturini2003evidence,
    title={Evidence for a Metal-Insulator Transition in Overdoped Cuprates: New Raman Results},
    author={Venturini, Francesca},
    booktitle={Advances in Solid State Physics},
    pages={253--266},
    year={2003},
    publisher={Springer}
    }

  • Z. Qingming, F. Venturini, R. Hackl, J. Hori, and T. Fujita, “New electronic raman scattering results in underdoped la $\{$sub 2-x$\}$ sr $\{$sub x$\}$ cuo $\{$sub 4$\}$,” , 2003.
    [BibTeX]
    @article{qingming2003new,
    title={New electronic Raman scattering results in underdoped La $\{$sub 2-x$\}$ Sr $\{$sub x$\}$ CuO $\{$sub 4$\}$},
    author={Qingming, Zhang and Venturini, Francesca and Hackl, Rudi and Hori, Jun'ya and Fujita, Toshizo},
    year={2003}
    }

2002

  • U. Michelucci, F. Venturini, and A. P. Kampf, “Quantum interference phenomena between impurity states in d-wave superconductors,” Journal of physics and chemistry of solids, vol. 63, iss. 12, p. 2283–2286, 2002.
    [BibTeX]
    @article{michelucci2002quantum,
    title={Quantum interference phenomena between impurity states in d-wave superconductors},
    author={Michelucci, Umberto and Venturini, Francesca and Kampf, Arno P},
    journal={Journal of Physics and Chemistry of Solids},
    volume={63},
    number={12},
    pages={2283--2286},
    year={2002},
    publisher={Pergamon}
    }

2001

  • U. Michelucci and A. Kampf, “Interference phenomena between impurities in d-wave superconductors,” Verhandlungen der deutschen physikalischen gesellschaft, vol. 36, iss. 1, p. 422, 2001.
    [BibTeX]
    @article{michelucci2001interference,
    title={Interference phenomena between impurities in d-wave superconductors},
    author={Michelucci, U and Kampf, AP},
    journal={Verhandlungen der Deutschen Physikalischen Gesellschaft},
    volume={36},
    number={1},
    pages={422},
    year={2001}
    }

2000

  • U. Michelucci, “Anisotropic conductivity of nd1. 85ce0. 15cuo4-delta,” , 2000.
    [BibTeX]
    @article{michelucci2000anisotropic,
    title={Anisotropic conductivity of Nd1. 85Ce0. 15CuO4-delta},
    author={Michelucci, Umberto},
    year={2000}
    }

  • U. Michelucci, “Collective modes and electronic raman scattering in the cuprates,” , 2000.
    [BibTeX]
    @article{michelucci2000collective,
    title={Collective modes and electronic Raman scattering in the cuprates},
    author={Michelucci, Umberto},
    year={2000}
    }

  • A. Pimenov, A. V. Pronin, A. Loidl, U. Michelucci, A. P. Kampf, S. Krasnosvobodtsev, V. Nozdrin, and D. Rainer, “Anisotropic conductivity of nd 1.85 ce 0.15 cuo 4- $\delta$ films at submillimeter wavelengths,” Physical review b, vol. 62, iss. 14, p. 9822, 2000.
    [BibTeX]
    @article{pimenov2000anisotropic,
    title={Anisotropic conductivity of Nd 1.85 Ce 0.15 CuO 4- $\delta$ films at submillimeter wavelengths},
    author={Pimenov, Andrei and Pronin, Artem V and Loidl, Alois and Michelucci, Umberto and Kampf, Arno P and Krasnosvobodtsev, SI and Nozdrin, VS and Rainer, D},
    journal={Physical Review B},
    volume={62},
    number={14},
    pages={9822},
    year={2000},
    publisher={American Physical Society}
    }

  • U. Michelucci, “Collective spin fluctuation mode and raman scattering in superconducting cuprates,” , 2000.
    [BibTeX]
    @article{michelucci2000collective,
    title={Collective spin fluctuation mode and Raman scattering in superconducting cuprates},
    author={Michelucci, Umberto},
    year={2000}
    }

  • F. Venturini, U. Michelucci, T. Devereaux, and A. P. Kampf, “Collective spin fluctuation mode and raman scattering in superconducting cuprates,” Physical review b, vol. 62, iss. 22, p. 15204, 2000.
    [BibTeX]
    @article{venturini2000collective,
    title={Collective spin fluctuation mode and Raman scattering in superconducting cuprates},
    author={Venturini, Francesca and Michelucci, Umberto and Devereaux, TP and Kampf, Arno P},
    journal={Physical Review B},
    volume={62},
    number={22},
    pages={15204},
    year={2000},
    publisher={American Physical Society}
    }

  • F. Venturini, U. Michelucci, T. Devereaux, and A. P. Kampf, “Collective modes and electronic raman scattering in the cuprates,” Physica c: superconductivity, vol. 341, p. 2265–2266, 2000.
    [BibTeX]
    @article{venturini2000collective,
    title={Collective modes and electronic Raman scattering in the cuprates},
    author={Venturini, F and Michelucci, Umberto and Devereaux, TP and Kampf, Arno P},
    journal={Physica C: Superconductivity},
    volume={341},
    pages={2265--2266},
    year={2000},
    publisher={North-Holland}
    }

  • U. Michelucci, A. Kampf, and A. Pimenov, “Anisotropic conductivity in superconducting ncco,” Arxiv preprint cond-mat/0010409, 2000.
    [BibTeX]
    @article{michelucci2000anisotropic,
    title={Anisotropic conductivity in superconducting NCCO},
    author={Michelucci, U and Kampf, AP and Pimenov, A},
    journal={arXiv preprint cond-mat/0010409},
    year={2000}
    }