Michelucci Umberto HSLU I

Prof. Dr. Umberto Michelucci Umberto Michelucci - (PGCE, Postgraduate Certificate in Higher Education)

Themenfeldverantwortliche*r Weiterbildung Applied Data Intelligence

Michelucci Umberto HSLU I

Hochschule Luzern – Informatik

Raum 8. Stock, shared
Campus Zug-Rotkreuz
Suurstoffi 1
6343 Rotkreuz


Weiterbildung

Themenfeldverantwortliche*r Weiterbildung Applied Data Intelligence

Leiter Programm

Dozent

+41 41 349 31 44

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Biografie

Umberto Michelucci studied Theoretical Physics in Italy, the United States, Germany and England, focusing on simulations and the theory of high temperature superconductors. He obtained his PhD in Machine Learning applied to Physics from the Portsmouth University in England. He worked in various industries for many years, gaining industrial experience in various fields. He also founded and directed the AI Center of Excellence at Helsana Versicherung AG in Zürich. He is also the co-founder of the company TOELT LLC, that focuses on large international research project with a strong AI component. He is working often with Google and NVIDIA on various project. He has many years of teaching at various levels, Bachelor, Master, PhD and for continuing education. He also holds a Postgraduate Certificate in Higher Education. He is Professor at HSLU. He is also the co-founder of the HSLU Applied AI Center.

He has written four books on Deep Learning with Springer Nature. His fourth, “Mathematical Concepts for Machine Learning in Science” just came out beginning 2024.

He is also in the Stanford 2% top scientist worldwide list.

Personal Website: https://umbertomichelucci.me/

Associations / Membershipts

  • IEEE Member

  • Swiss Mathematical Society

Education

  • PhD in Machine Learning applied to Physics

  • Master in Theoretical Physics

  • Postgraduate Certificate in Higher Education

Awards

Interviews

Research

My main interests lie in Applied & Computational Mathematics with focus on Scientific Machine Learning, Inverse Problems & Uncertainty Quantification.

  • Inverse problems & scientific estimation (recover latent scientific quantities from indirect/noisy measurements; study identifiability, stability, and consistency, with spectroscopy, sensing, medical/remote imaging as testbeds).

  • Uncertainty quantification for reliable ML (metrics and validation approaches that explicitly incorporate label/measurement noise; bootstrap and related tools for realistic performance assessment).

  • Fundamental limits & model-agnostic bounds.

  • Algorithms to estimate Bayes error / intrinsic task difficulty.

  • Learning in function spaces (learning & Statistics in Infinite-Dimensional Spaces).

  • Operator/function-valued learning and generalization on spectra, curves, and fields.

  • Structure- and domain-informed ML (explainability with physics/chemistry priors).

  • Domain adaptation and interpretable models that map spectral features to physico-chemical mechanisms; small-datasets.

  • Scientific sensing & instrumentation with ML (ML-enhanced, often multitask, sensors; super-resolution for fast spectroscopy; end-to-end design and analysis).

  • Open benchmarks/datasets for satellite vision and medical imaging to make evaluation reproducible and failure modes visible.

  • Effects of label/input/algorithmic noise and model misspecification; design of estimators and training schemes that are stable to perturbations and measurement error.

  • Functional Theory and Random Matrix Theory and their relations to the mathematical foundations of machine learning.

  • Computational astrophysics. I have an on-going cooperation with INAF (Istituto Nazionale Astrofisica, Italy) in Bologna and Milano. Projects are on scientifically informed algorithm development, uncertainty and error estimation of deep learning algorithms applied to astrophysics, spectral model-agnostic feature extraction, etc.

  • Computational food technology. I am working on algorithms to extract chemical information from various food types (as maize, olive oil, wine, etc.) from optical measurements, in particular fluorescence and Raman spectroscopy (in collaboration with Prof. Dr. Venturini). I am also interested in developing explainable ML approaches, to study if algorithms really learns from the chemistry of the samples, or from other aspects that are not related to physics or chemistry.

Talks and Conferences

  • 2nd Workshop on Machine Learning in Infinite Dimensions - Sept. 2025 ETH Zürich - Poster "Infinite-Dimensional Nature of Spectroscopy and Why Models Succeed, Fail and Mislead"

  • Talk @ Spital Emmental (AIMED) - August 2025 - "Mehrwert und Umgang mit KI im Alltag"

  • Talk @ Italian Astrophysics National Institute (INAF) (Bologna) - Jan 2025 - "Machine Learning in Science: Opportunities, Challenges, and New Frontiers Making Science, not pseudo-science"

  • Talk @ Politecnico di Torino (POLITO) (Turin, Italy) - Jan 2025 - "Artificial Intelligence Projects in Bioengineering and Medicine Generating Impact"

  • Invited Lecture @ Uni St. Gallen, (St. Gallen) - Jan 2025 - "Road to become an AI Company Challenges and chances for SMEs"

  • Talk @ FFHS (Zürich) - Jan 2025 - "Generative KI und Digitalisierung in Bildung und Forschung: Herausforderungen, Chancen und ethische Überlegungen"

  • Talk @ Virtuial AI Summit (Online, Berlin) - "The AI-Ready Company: Strategies for Future-Proofing Your Business"

  • Talk @ European Space Agency (ESA) (Madrid) - April 2024 - "Precision Recognition: Training Deep Learning Algorithms for Multiscale Vehicle Detection in Satellite Imagery"

Summer Schools

  • Organiser and lecturer for the summer school "Machine and Deep Learning @ INAF-IASF Milano" (Italian Astrophysics National Institute) - Jan 2025

Fächer
  • Computational Mathematics
  • Applied Statistics
  • Computer Vision
  • Deep Learning
  • Scientific Teaching
  • Programming for Computational Mathematics
Lehr- und Forschungsschwerpunkte
  • Applied Machine Learning and Deep Learning (Theory)
  • Scientific Machine Learning
  • Statistics and Machine Learning in Infinite Dimensions
  • Mathematics und Statistics in general
  • Scientific Computing
  • Image Processing & Computer Vision
  • High performance computing and GPU programming

Masters and PhDs

Selected Masters Tutored

1) Joshua Hügli, "3D Reconstruction of Trapezium Bone from 2D X-Rays", 2025
2) Dr. Nathalie Alexander, "Fractal Dimension Analysis of Pediatric Brain Structures: Developmental Curves Across Age" 2025.
3) Marta Martinozzi, "Automatic Anomaly Detection in sensor data for ICU patients" (in collaboration with the Emmental Hospital), 2025.
4) Sarp Koc, "Drone Aerial Imaging Analysis in Smart Agriculture", 2025
5) Morteza Kiani Haftlang, "Computer Vision Framework for 3D Cancer Detection: Comprehensive assessment of self-supervised deep learning architectures", 2024
6) Matthias De Paolis, "Deep Learning-based Detection of Photovoltaic Installations: A Case Study in the Canton of Zurich", 2024
6) Julia Netzel, "Statistical Stability of Super-Resolution for Astronomical Imaging", 2023 (ETH)
7) Christian Schmid, "Value Generation with Computer Vision Techniques in the Olive Oil Industry - a Knowledge Graph Framework", 2023

PhD Students Tutored

1) Arnaud Gucciardi, "Brain Symmetry and Structure in Children MRI Imaging", 2025
2) Dr. Michela Sperti, "Predicting Personalized Pathological Risks and Dynamics in Cardiology How to Exploit Data-Driven Approaches in Clinical Decision Support Systems", (collaboration with the Politecnico di Torino, Italy) 2025

Projekte

Forschungsprojekte

  • AI for All

Publikationen und Präsentationen

Publikationen und Präsentationen - Buch/Katalog

  • Michelucci, Umberto (2024). Fundamental Mathematical Concepts for Machine Learning in Science. Switzerland: Springer Verlag.
  • Michelucci, Umberto (2022). Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python. Berkeley, CA: Apress.
  • Michelucci, Umberto (2019). Advanced applied deep learning: convolutional neural networks and object detection. New York: Apress.
  • Michelucci, Umberto (2018). Applied Deep Learning- A Case-Based Approach to Understanding Deep Neural Networks. New York: Springer nature.

Publikationen und Präsentationen - Artikel, Rezension; peer reviewed

  • Michelucci, Umberto & Venturini, Francesca (01.04.2025). New Statistical Framework for Extreme Error Probability in High-Stakes Domains for Reliable Machine Learning. arXiv preprint, 2025, doi: 10.48550/arXiv.2503.24262
  • Michelucci, Umberto (20.03.2025). 2025 photonics for agrifood roadmap: towards a sustainable and healthier planet (multiple Authors). Journal of Physics: Photonics, 2025, doi: 10.1088/2515-7647/adbea9
  • Loddo, Fabio; Piga, Dario; El Ghazouali, Safouane & Michelucci, Umberto (2024). BenchCloudVision: A Benchmark Analysis of Deep Learning Approaches for Cloud Detection and Segmentation in Remote Sensing Imagery. arXiv, 2024, 1-1. doi: 10.48550/arXiv.2402.13918
  • Gucciardi, Arnaud; El Ghazouali, Safouane; Venturini, Francesca; Groznik, Vida & Michelucci, Umberto (2024). Symbrain: A large-scale dataset of MRI images for neonatal brain symmetry analysis. arXiv, 2024, 1-1. doi: 10.48550/arXiv.2401.11814
  • El Ghazouali, Safouane; Mhirit, Youssef; Oukhrid, Ali; Michelucci, Umberto & Nouira, Hichem (2024). FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything. Sensors, 2024(24/9), 2889-2889. doi: 10.3390/s24092889
  • Venturini, Francesca; Fluri, silvan & Michelucci, Umberto (2024). Shedding light on the ageing of extra virgin olive oil: Probing the impact of temperature with fluorescence spectroscopy and machine learning techniques. LWT - Food Science and Technology (Formerly: Lebensmittel-Wissenschaft und -Technologie), 2024, 1-1.
  • El Ghazouali, Safouane; Gucciardi, Arnaud & Michelucci, Umberto (2024). Class-Conditional self-reward mechanism for improved Text-to-Image models. arXiv, 2024, 1-1. doi: arXiv:2405.13473
  • Gucciardi, Arnaud; El Ghazouali, Safouane; Michelucci, Umberto & Venturini, Francesca (2024). Machine learning feature extraction for predicting the ageing of olive oil. Proceedings Volume 13011, Data Science for Photonics and Biophotonics, 2024(130110A), 1-1. doi: 10.1117/12.3017680
  • El Ghazouali, Safouane; Gucciardi, Arnaud; Venturini, Francesca; Venturi, Nicola; Ruegsegger, Michael & Michelucci, Umberto (2024). FlightScope: A Deep Comprehensive Review of Aircraft Detection Algorithms in Satellite Imagery. arXiv, 2024, 1-1. doi: arXiv:2404.02877
  • Michelucci, Umberto (2024). Machine learning-enhanced fluorescence spectroscopy for the quality assessment of extra virgin olive oil during ageing. Optical Sensing and Detection VIII, 2024(12999), 235-239.
  • Michelucci, Umberto & Venturini, Francesca (2023). New metric formulas that include measurement errors in machine learning for natural sciences. Expert Systems with Applications, 2023, 1. doi: https://doi.org/10.1016/j.eswa.2023.120013
  • Michelucci, Umberto (2023). Understanding the learning mechanism of convolutional neural networks applied to fluorescence spectra. AI and Optical Data Sciences IV, 2023, 178-184.
  • Michelucci, Umberto (2023). Deep learning super resolution for high-speed excitation emission matrix measurements. AI and Optical Data Sciences IV, 2023, 127-137.
  • Michelucci, Umberto (2023). Extraction of physicochemical properties from the fluorescence spectrum with 1D convolutional neural networks: Application to olive oil. Journal of Food Engineering, 2023, 336.
  • Schmid, Christian; Laurenzi, Emanuele; Michelucci, Umberto & Francesca, Venturini (2023). Explainable AI for the olive oil industry. International Conference on Business Informatics Research, 2023, 1-1.
  • Michelucci, Umberto & Venturini, Francesca (2022). New Metric Formulas that Include Measurement Errors in Machine Learning for Natural Sciences. Expert Systems with Applications, 2022, 1. doi: 10.48550/ARXIV.2209.15588
  • Venturini, Francesca; Michelucci, Umberto; Sperti, Michela; Gucciardi, Arnaud; Martose, Vanessa M. & Deriu, Marco A. (2022). Physico-chemical properties extraction from the fluorescence spectrum with 1D-convolutional neural networks: application to olive oil. Journal of Food Engineering, 2022, 336. doi: 10.48550/ARXIV.2203.07229
  • Arnaud, Gucciardi; Michelucci, Umberto; Venturini, Francesca; Sperti, Michela & Deriu, Marco Agostino (2022). Compact optical fluorescence sensor for food quality control using artificial neural networks: application to olive oil. Optical Sensing and Detection VII, 2022, 80. doi: 10.1117/12.2621588
  • Milleville, Kenzo; Thirukokaranam Chandrasekar, Krishna Kumar; Blyau, Thibault; Michelucci, Umberto; Iannello, AURORA & Verstockt, Steven (2022). Extraction and classification of historical stamp cards using computer vision. DH Benelux 2022-ReMIX: Creation and alteration in DH (hybrid), 2022, 1–4.
  • Sperti, Michela; Michelucci, Umberto; Venturini, Francesca; Gucciardi, Arnaud & Deriu, Marco Agostino . (2022). Chemical analysis of olive oils from fluorescence spectra thanks to one-dimensional convolutional neural networks. Optical Sensing and Detection VII, 2022, 81. doi: 10.1117/12.2621666
  • Venturini, Francesca; Michelucci, Umberto; Sperti, Michela; Gucciardi, Arnaud & Deriu, Marco Agostino (2022). One-dimensional convolutional neural networks design for fluorescence spectroscopy with prior knowledge: explainability techniques applied to olive oil fluorescence spectra. Optical Sensing and Detection VII, 2022, 60. doi: 10.1117/12.2621646
  • Venturini, Francesca; Baumgartner, Michael & Michelucci, Umberto (2021). Implementation of multi-task learning neural network architectures for robust industrial optical sensing. Optical Measurement Systems for Industrial Inspection XII, 2021, 90. doi: 10.1117/12.2593469
  • Venturini, Francesca & Michelucci, Umberto (2021). New Autonomous Intelligent Sensor Design Approach for Multiple Parameter Inference. 7th International Electronic Conference on Sensors and Applications, 2021, 96. doi: 10.3390/engproc2020002096
  • Venturini, Francesca; Baumgartner, Michael & Michelucci, Umberto (2021). New Approach for Temperature-Immune Oxygen Sensing based on Pt-TFPP. OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES), 2021, SW5H.2. doi: 10.1364/SENSORS.2021.SW5H.2
  • Venturini, Francesca; Sperti, Michela; Michelucci, Umberto; Herzig, Ivo; Baumgartner, Michael; Caballero, Josep Palau; Jimenez, Arturo & Deriu, Marco Agostino (2021). Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques. Foods, 2021(5), 1010. doi: 10.3390/foods10051010
  • Halasz, Geza; Sperti, Michela; Michelucci, Umberto; Villani, Matteo; Agostoni, Piergiuseppe; Biagi, Andrea; Rossi, Luca; Botti, Andrea; Mari, Chiara; Maccarini, Marco; Pura, Filippo; Roveda, Loris; Nardecchia, Alessia; Mottola, Emanuele; Nolli, Massimo; Salvioni, Elisabetta; Mapelli, Massimo; Deriu, Marco Agostino; Piga, Dario & Piepoli, Massimo (2021). A Machine Learning Approach for Mortality Prediction in COVID-19 Pneumonia: Development and Evaluation of the Piacenza Score. Journal of Medical Internet Research, 2021(5), e29058. doi: 10.2196/29058
  • Michelucci, Umberto; Sperti, Michela; Piga, Dario; Venturini, Francesca & Deriu, Marco A. (2021). A Model-Agnostic Algorithm for Bayes Error Determination in Binary Classification. Algorithms, 2021(11), 301. doi: 10.3390/a14110301
  • D'Ascenzo, Fabrizio; De Filippo, Ovidio; Gallone, Guglielmo; Mittone, Gianluca; Deriu, Marco Agostino; Iannaccone, Mario; Ariza-Solé, Albert; Liebetrau, Christoph; Manzano-Fernández, Sergio; Quadri, Giorgio; Kinnaird, Tim; Campo, Gianluca; Simao Henriques, Jose Paulo; Hughes, James M; Dominguez-Rodriguez, Alberto; Aldinucci, Marco; Morbiducci, Umberto; Patti, Giuseppe; Raposeiras-Roubin, Sergio; Abu-Assi, Emad; De Ferrari, Gaetano Maria; Piroli, Francesco; Saglietto, Andrea; Conrotto, Federico; Omedé, Pierluigi; Montefusco, Antonio; Pennone, Mauro; Bruno, Francesco; Bocchino, Pier Paolo; Boccuzzi, Giacomo; Cerrato, Enrico; Varbella, Ferdinando; Sperti, Michela; Wilton, Stephen B.; Velicki, Lazar; Xanthopoulou, Ioanna; Cequier, Angel; Iniguez-Romo, Andres; Munoz Pousa, Isabel; Cespon Fernandez, Maria; Caneiro Queija, Berenice; Cobas-Paz, Rafael; Lopez-Cuenca, Angel; Garay, Alberto; Blanco, Pedro Flores; Rognoni, Andrea; Biondi Zoccai, Giuseppe; Biscaglia, Simone; Nunez-Gil, Ivan; Fujii, Toshiharu; Durante, Alessandro; Song, Xiantao; Kawaji, Tetsuma; Alexopoulos, Dimitrios; Huczek, Zenon; Gonzalez Juanatey, Jose Ramon; Nie, Shao-Ping; Kawashiri, Masa-aki; Colonnelli, Iacopo; Cantalupo, Barbara; Esposito, Roberto; Leonardi, Sergio; Grosso Marra, Walter; Chieffo, Alaide; Piga, Dario; Malavolta, Marta; Gili, Sebastiano; Mennuni, Marco; Montalto, Claudio; Oltrona Visconti, Luigi; Arfat, Yasir & Michelucci, Umberto (2021). Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets. The Lancet, 2021(10270), 199-207. doi: 10.1016/S0140-6736(20)32519-8
  • Venturini, Francesca; Baumgartner, Michael & Michelucci, Umberto (2020). Dual Oxygen and Temperature Luminescence Learning Sensor with Parallel Inference. Sensors, 2020(17), 4886. doi: 10.3390/s20174886
  • Venturini, Francesca; Baumgartner, Michael & Michelucci, Umberto (2020). Dual oxygen and temperature sensing with single indicator using multi-task-learning neural networks. Optical Sensing and Detection VI, 2020, 52. doi: 10.1117/12.2554941
  • Venturini, Francesca; Baumgartner, Michael & Michelucci, Umberto (2019). New approach for luminescence sensing based on machine learning. Optical Data Science II, 2019, 14. doi: 10.1117/12.2508969
  • Venturini, Francesca & Michelucci, Umberto (2019). Multi-Task Learning for Multi-Dimensional Regression: Application to Luminescence Sensing. Applied Sciences, 2019(22), 4748. doi: 10.3390/app9224748
  • Venturini, Francesca & Michelucci, Umberto (2017). Novel Algorithm for Calibration-Free Absorption Spectroscopy Sensor. Proceedings of the 5th International Symposium on Sensor Science (I3S 2017), 2017, 833. doi: 10.3390/proceedings1080833
  • Venturini, F.; Hackl, R.; Michelucci, U. & Michelucci, Umberto (2003). 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, 2003(14), 149701. doi: 10.1103/PhysRevLett.90.149701
  • Pimenov, A.; Pronin, A. V.; Loidl, A.; Michelucci, U.; Kampf, A. P.; Krasnosvobodtsev, S. I.; Nozdrin, V. S.; Rainer, D. & Michelucci, Umberto (2000). Anisotropic conductivity of Nd 1.85 Ce 0.15 CuO 4 − δ films at submillimeter wavelengths. Physical Review B, 2000(14), 9822-9826. doi: 10.1103/PhysRevB.62.9822
  • Michelucci, U.; Kampf, A. P.; Pimenov, A. & Michelucci, Umberto (2000). Anisotropic conductivity in superconducting NCCO. arxiv Archive, 2000, 1. doi: 10.48550/ARXIV.COND-MAT/0010409
  • Venturini, F.; Michelucci, U.; Devereaux, T. P.; Kampf, A. P. & Michelucci, Umberto (2000). Collective Spin Fluctuation Mode and Raman Scattering in Superconducting Cuprates. Physical Review B, 2000(22), 15204-15207. doi: 10.1103/PhysRevB.62.15204

Publikationen und Präsentationen - Artikel, Rezension; not peer reviewed

  • El Ghazouali, Safouane & Michelucci, Umberto (2025). VisioFirm: Cross-Platform AI-assisted Annotation Tool for Computer Vision. arXiv preprint, 2025,
  • Kiani Haftlang, Morteza; Malmir, Mohammadhossein; Parand, Foroutan; Michelucci, Umberto & El Ghazouali, Safouane (2025). Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers. arXiv preprint,
  • Michelucci, Umberto (2023). On the High Symmetry of Neural Network Functions. arXiv preprint, 2023,
  • Venturini, Francesca; Michelucci, Umberto; Sperti, Michela; Gucciardi, Arnaud; Martos, Vanessa M. & Deriu, Marco A. (2023). Dataset of Fluorescence Spectra and Chemical Parameters of Olive Oils. arxiv Archive, 2023, 1. doi: 10.48550/ARXIV.2301.04471
  • Michelucci, Umberto (2022). On the High Symmetry of Neural Network Functions. arxiv Archive, 2022, 1. doi: 10.48550/ARXIV.2211.06603
  • Michelucci, Umberto (2022). An Introduction to Autoencoders. arxiv Archive, 2022, 1. doi: 10.48550/ARXIV.2201.03898
  • Michelucci, Umberto & Venturini, Francesca (2021). Estimating Neural Network’s Performance with Bootstrap: A Tutorial. Machine Learning and Knowledge Extraction, 2021(2), 357-373. doi: 10.3390/make3020018
  • Venturini, Francesca; Baumgartner, Michael & Michelucci, Umberto (2019). Optical Oxygen Sensing with Artificial Intelligence. Sensors, 2019(4), 777. doi: 10.3390/s19040777

Publikationen und Präsentationen - Buchkapitel/Gesetzeskommentar/Lexikonartikel

  • Michelucci, Umberto (2025). Infinite-Dimensional Nature of Spectroscopy and Why Models Succeed, Fail, and Mislead. Infinite-Dimensional Nature of Spectroscopy and Why Models Succeed, Fail, and Mislead. Zürich: 2nd Workshop on Machine Learning in Infinite Dimensions.

Publikationen und Präsentationen - Hochschulschrift (Bachelor/Master/Dissertation/Habilitation)

  • Alexander, Nathalie & Michelucci, Umberto (2025). Fractal Dimension Analysis of Pediatric Brain Structures: Developmental Curves Across Age (nicht veröffentlichte Master-/Lizentiats-/Diplomarbeit). Hochschule Luzern, Schweiz.
  • kalbermatten, diego & Michelucci, Umberto (2023). Smart Shelf – Führen der Inventur mithilfe Computer Vision & Deep Learning (nicht veröffentlichte Bachelorarbeit). HSLU, Schweiz.
  • Birbaumer, Mirko; Michelucci, Umberto & Schmid, Ralph (2022). IoT-based Attention Tracking in a Real-World Scenario (nicht veröffentlichte Master-/Lizentiats-/Diplomarbeit). HSLU Zentralschweiz, Schweiz.

bedeutende Leistung - Preise und Ehrungen

  • Michelucci, Umberto (01.01.2024). Google Developer Expert für Expertise in Machine Learning.
(PGCE, Postgraduate Certificate in Higher Education) - Umberto Michelucci
(PGCE, Postgraduate Certificate in Higher Education) - Umberto Michelucci
(PGCE, Postgraduate Certificate in Higher Education) - Umberto Michelucci
(PGCE, Postgraduate Certificate in Higher Education) - Umberto Michelucci
(PGCE, Postgraduate Certificate in Higher Education) - Umberto Michelucci
(PGCE, Postgraduate Certificate in Higher Education) - Umberto Michelucci
(PGCE, Postgraduate Certificate in Higher Education) - Umberto Michelucci