Prof. Dr. Francesca Venturini
Prof. Dr. Francesca Venturini
ZHAW
School of Engineering
Forschungsschwerpunkt Angewandte Optik
Technikumstrasse 9
8400 Winterthur
Work at ZHAW
Position
- Head team Spectroscopy
- Deputy head team Applied Optics
- Professor of applied optics
- Coordinator of the MSE Profile Photonics
- Reviewer for Springer Nature, Elsevier, Optica, MDPI, Royal Society of Chemistry
- Reviewer for the European Research Council
Focus
Optics, laser spectroscopy, fluorescence spectroscopy, Raman spectroscopy, absorption spectroscopy, sensor development, gas sensing, fiber optic, non-linear optics, solid state physics, superconductivity, magnet technology
Teaching
- Physics 1 and 2
- Case Studies Stock and Flow - Systeme 1 and 2
- MSE: Optical Engineering and Metrology
- CAS Digitale Technologien und Innovation
Experience
- Expert for Innosuisse
Innosuisse
01 / 2023 - today - Cofounder and CTO
TOELT GmbH
11 / 2018 - today - Professor of applied optics
ZHAW
12 / 2017 - today - Researcher and lecturer
ZHAW
09 / 2013 - 11 / 2017 - Head of product development R&D
Mettler-Toledo AG
06 / 2011 - 08 / 2013 - Senior project manager R&D
Mettler-Toledo AG
08 / 2008 - 05 / 2011 - Project manager R&D
Bruker BioSpin AG
08 / 2003 - 07 / 2008
Education and Continuing education
Education
- PhD / Physics
Technische Universität München, München, DE
09 / 1998 - 04 / 2003 - Graduate studies
The George Washington University, Washington DC, USA
08 / 1997 - 07 / 1998 - Master of Science (M.Sc.) / Physics
Università degli Studi di Firenze, IT
10 / 1992 - 07 / 1997
Continuing Education
- CAS in Higher Education
Pädagogische Hochschule Zurich, PHZH
01 / 2016 - PGCert Business Administration
The Open University Business School, UK
11 / 2007
Network
Membership of networks
- SPIE International society for optics and photonics
- Optica - Optical Society of America
- IEEE - Institute of Electrical and Electronics Engineers
- Photonics 21
- German Physical Society
- Swiss Physical Society
ORCID digital identifier
Social media
Projects
- Raman SERDS for Plastic Detection / Project leader / ongoing
- Supramolecular Luminescent Chemosensorsfor PFAS detection / Project leader / ongoing
- LED Flash / Project leader / ongoing
- Internet of Things # Amfora. A Swiss Digital Solution for Global Foodservice / Team member / ongoing
- DEEPWine: Virtual oenologist based on deep learning and optical spectroscopy / Project leader / completed
- A diagnostic tool for NMR CryoProbes / Deputy project leader / completed
- Raman for Process Analytics / Project leader / completed
- Sensitivity improvement techniques for Raman scattering measurements / Project leader / completed
- NeO2-Sens / Project leader / completed
- Raman spectroscopy for material analysis / Project leader / completed
- ARES - AI for fluoREscence Spectroscopy in oil / Project leader / completed
- Self-learning optical sensor / Project leader / completed
- Optical gas sensor with ceramic cell / Project leader / completed
- StereO2 – Low-power optical oxygen sensor / Project leader / completed
- Miniaturized gas sensor / Project leader / completed
- Feasibility study and sensor improvements / Project leader / completed
Publications
Articles in scientific journal, peer-reviewed
- Michelucci, U., & Venturini, F. (2026). The infinite-dimensional nature of spectroscopy and why models succeed, fail, and mislead. The Analyst. https://doi.org/10.1039/d6an00346j
- Di Maria, M., Planeta, D., Venturini, F., Torregrossa, F., & Crupi, P. (2026). How can we sustainably assess the shelf life of EVOO? A systematic review on analytical strategies and food waste reduction. Frontiers in Nutrition, 12(1722145). https://doi.org/10.3389/fnut.2025.1722145
- Venturini, F., Michelucci, U., Magnus, I., & Smeesters, L. (2025). Multi-mycotoxin detection using fluorescence spectroscopy and machine learning. Food Control, 181(111728). https://doi.org/10.1016/j.foodcont.2025.111728
- Smeesters, L., Venturini, F., Paulus, S., Mahlein, A.-K., Perpetuini, D., Cardone, D., Merla, A., Gac, B., Perrin, S., Trégoat, D., Poffo, L., Fournier, A., Bonifazi, G., Serranti, S., Liao, W., Osseiran, N., Vanwolleghem, M., Peretti, R., Bandyopadhyay, A., et al. (2025). 2025 photonics for agrifood roadmap : towards a sustainable and healthier planet. Journal of Physics: Photonics, 7(3), 32501. https://doi.org/10.1088/2515-7647/adbea9
- El Ghazouali, S., Gucciardi, A., Venturini, F., Venturi, N., Rueegsegger, M., & Michelucci, U. (2024). FlightScope : an experimental comparative review of aircraft detection algorithms in satellite imagery. Remote Sensing, 16(24), 4715. https://doi.org/10.3390/rs16244715
- Michelucci, U., & Venturini, F. (2024). Deep learning domain adaptation to understand physico-chemical processes from fluorescence spectroscopy small datasets and application to the oxidation of olive oil. Scientific Reports, 14(22291). https://doi.org/10.1038/s41598-024-73054-y
- Ahmad, A., Liew, A. X. W., Venturini, F., Kalogeras, A., Candiani, A., Di Benedetto, G., Ajibola, S., Cartujo, P., Romero, P., Lykoudi, A., De Grandis, M. M., Xouris, C., Lo Bianco, R., Doddy, I., Elegbede, I., D’Urso Labate, G. F., García del Moral, L. F., & Martos, V. (2024). AI can empower agriculture for global food security : challenges and prospects in developing nations. Frontiers in Artificial Intelligence, 7(1328530). https://doi.org/10.3389/frai.2024.1328530
- Venturini, F., Fluri, S., Mejari, M., Baumgartner, M., Piga, D., & Michelucci, U. (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, 191(115679). https://doi.org/10.1016/j.lwt.2023.115679
- Eggertson, E. C., & Venturini, F. (2023). Resonant Raman spectroscopy of carotenoids in aging of extra virgin olive oil. Sensors, 23(17), 7621. https://doi.org/10.3390/s23177621
- Michelucci, U., & Venturini, F. (2023). New metric formulas that include measurement errors in machine learning for natural sciences. Expert Systems with Applications, 224(120013). https://doi.org/10.1016/j.eswa.2023.120013
- Venturini, F., Fluri, S., & Baumgartner, M. (2023). Dataset of fluorescence EEM and UV spectroscopy data of olive oils during ageing. Data, 8(5), 81. https://doi.org/10.3390/data8050081
- Venturini, F., Sperti, M., Michelucci, U., Gucciardi, A., Martos, V. M., & Deriu, M. A. (2022). Extraction of physicochemical properties from the fluorescence spectrum with 1D convolutional neural networks : application to olive oil. Journal of Food Engineering, 336(111198). https://doi.org/10.1016/j.jfoodeng.2022.111198
- Michelucci, U., & Venturini, F. (2021). Estimating neural network’s performance with bootstrap : a tutorial. Machine Learning and Knowledge Extraction, 3(2), 357–373. https://doi.org/10.3390/make3020018
- Michelucci, U., Sperti, M., Piga, D., Venturini, F., & Deriu, M. A. (2021). A model-agnostic algorithm for Bayes error determination in binary classification. Algorithms, 14(11), 301. https://doi.org/10.3390/a14110301
- Venturini, F., Sperti, M., Michelucci, U., Herzig, I., Baumgartner, M., Caballero, J. P., Jimenez, A., & Deriu, M. A. (2021). Exploration of Spanish olive oil quality with a miniaturized low-cost fluorescence sensor and machine learning techniques. Foods, 10(5), 1010. https://doi.org/10.3390/foods10051010
- Venturini, F., Michelucci, U., & Baumgartner, M. (2020). Dual oxygen and temperature luminescence learning sensor with parallel inference. Sensors, 20(17), 4886. https://doi.org/10.3390/s20174886
- Michelucci, U., & Venturini, F. (2019). Multi-task learning for multi-dimensional regression : application to luminescence sensing. Applied Sciences, 9(22). https://doi.org/10.3390/app9224748
- Michelucci, U., Baumgartner, M., & Venturini, F. (2019). Optical oxygen sensing with artificial intelligence. Sensors, 19(4), 777. https://doi.org/10.3390/s19040777
- Venturini, F., Baumgartner, M., & Borisov, S. (2018). Mn4+-doped magnesium titanate : a promising phosphor for self-referenced optical temperature sensing. Sensors, 18(2/668). https://doi.org/10.3390/s18020668
- Chelwani, N., Baum, A., Böhm, T., Opel, M., Venturini, F., Tassini, L., Erb, A., Berger, H., Forró, L., & Hackl, R. (2018). Magnetic excitations and amplitude fluctuations in insulating cuprates. Physical Review B, 97(2). https://doi.org/10.1103/PhysRevB.97.024407
- Michelucci, U., & Venturini, F. (2017). Novel semi-parametric algorithm for interference-immune tunable absorption spectroscopy gas sensing. Sensors, 17(10), 2281. https://doi.org/10.3390/s17102281
- Venturini, F., Schönherr, V., Rey, J., & Adolfsson, E. (2017). Characterization of light-gas interaction in strongly-scattering nanoporous materials and its implications for tunable diode laser absorption spectroscopy. Applied Physics B, 123(4), 123–136. https://doi.org/10.1007/s00340-017-6705-z
- Venturini, F., Bürgi, R., Borisov, S., & Klimant, I. (2015). Optical temperature sensing using a new thermographic phosphor. Sensors and Actuators A: Physical, 233, 324–329. https://doi.org/10.1016/j.sna.2015.07.009
- Munnikes, N., Muschler, B., Venturini, F., Tassini, L., Prestel, W., Ono, S., Ando, Y., Peets, D. C., Hardy, W. N., Liang, R., Bonn, D. A., Damascelli, A., Eisaki, H., Greven, M., Erb, A., & Hackl, R. (2011). Pair breaking versus symmetry breaking : origin of the Raman modes in superconducting cuprates. Physical Review B, 84(144523). https://doi.org/10.1103/PhysRevB.84.144523
- Prestel, W., Venturini, F., Muschler, B., Tütto, I., Hackl, R., Lambacher, M., Erb, A., Komiya, S., Ono, S., Ando, Y., Inosov, D., Zabolotnyy, V. B., & Borisenko, S. V. (2010). Quantitative comparison of single- and two-particle properties in the cuprates. The European Physical Journal Special Topics, 188(1), 163–171. https://doi.org/10.1140/epjst/e2010-01304-2
- Hackl, R., Tassini, L., Venturini, F., Erb, A., Hartinger, Ch., Kikugawa, N., & Fujita, T. (2006). Raman study of ordering phenomena in copper–oxygen systems. Journal of Physics and Chemistry of Solids, 67(1-3), 289–293. https://doi.org/10.1016/j.jpcs.2005.10.126
- Tassini, L., Venturini, F., Zhang, Q.-M., Hackl, R., Kikugawa, N., & Fujita, T. (2005). Dynamical properties of charged stripes in La(2-x)SrxCuO4. Physical Review Letters, 95(117002). https://doi.org/10.1103/PhysRevLett.95.117002
- Zhang, Q., Venturini, F., Hackl, R., Hori, J., & Fujita, T. (2003). New electronic Raman scattering results in underdoped La2−xSrxCuO4. Physica C: Superconductivity and Its Applications, 286, 282–285. https://doi.org/10.1016/S0921-4534(02)02132-9
- Opel, M., & Venturini, F. (2002). Raman scattering in solids. European Pharmaceutical Review, 7(3), 76–82.
- Venturini, F., Opel, M., Devereaux, T. P., Freericks, J. K., Tüttő, I., Revaz, B., Walker, E., Berger, H., Forró, L., & Hackl, R. (2002). Observation of an unconventional metal-insulator transition in overdoped CuO2 compounds. Physical Review Letters, 89(10), 107003–107001. https://doi.org/10.1103/PhysRevLett.89.107003
- Michelucci, U., Venturini, F., & Kampf, A. (2002). Quantum interference phenomena between impurity states in d-wave superconductors. Journal of Physics and Chemistry of Solids, 63(12), 2283–2286. https://doi.org/10.1016/S0022-3697(02)00238-X
- Venturini, F., Opel, M., Hackl, R., Berger, H., Forró, L., & Revaz, B. (2002). Doping dependence of the electronic Raman spectra in cuprates. Journal of Physics and Chemistry of Solids, 63(12), 2345–2348. https://doi.org/10.1016/S0022-3697(02)00239-1
- Venturini, F., Zhang, Q.-M., Hackl, R., Lucarelli, A., Lupi, S., Ortolani, M., Calvani, P., Kikugawa, N., & Fujita, T. (2002). Raman scattering versus infrared conductivity : evidence for one-dimensional conduction in La(2-x)Sr(x)CuO(4). Physical Review B, 66(6). https://doi.org/10.1103/PhysRevB.66.060502
- Venturini, F., Hackl, R., & Michelucci, U. (2002). Comment on : nonmonotonic $d_{x^{2}-y^{2}}$ superconducting order parameter in Nd$_{2-x}$Ce$_x$CuO$_4$. Physical Review Letters, 90(14), 149701–149701. https://doi.org/10.1103/PhysRevLett.90.149701
- Opel, M., Nemetschek, R., Venturini, F., Hackl, R., Tutto, I., Berger, H., Forro, L., Erb, A., Revaz, B., & Walker, E. (2001). A light-scattering study of dynamical carrier properties in cuprate systems. Ferroelectrics, 249(1), 155–164. https://doi.org/10.1080/00150190108214977
- Venturini, F., Michelucci, U., Devereaux, T. P., & Kampf, A. P. (2000). Collective spin fluctuation mode and raman scattering in superconducting cuprates. Physical Review B, 62, 15204–15207. https://doi.org/10.1103/PhysRevB.62.15204
- Opel, M., Venturini, F., Hackl, R., Revaz, B., Berger, H., & Forrò, L. (2000). Superconducting gap and pseudogap in Bi-2212. Physica B: Condensed Matter, 284-288, 669–670. https://doi.org/10.1016/S0921-4526(99)02344-3
- Opel, M., Götzinger, M., Hoffmann, C., Nemetschek, R., Philipp, R., Venturini, F., Hackl, R., Erb, A., & Walker, E. (1999). Pseudogap and superconducting gap in YBa2Cu3o6+x : a raman study. Journal of Low Temperature Physics, 117(3-4), 347–351. https://doi.org/10.1023/A:1022513531861
- Opel, M., Nemetschek, R., Venturini, F., Hackl, R., Erb, A., Walker, E., Berger, H., & Forrò, L. (1999). Raman spectroscopy in YBa2Cu3O6+x and Bi2Sr2(CaxY1-x)Cu2O8+d : pseudogap and superconducting gap. Physica Status Solidi B, 215(1), 471–476. doi.org/10.1002/(SICI)1521-3951(199909)215:1<471::AID-PSSB471>3.0.CO;2-K
Books, peer-reviewed
Venturini, F. (2003). Raman scattering study of electronic correlations in cuprates : observation of an unconventional metal insulator transition [Doctoral dissertation]. Mensch-und-Buch-Verlag.
Book chapters, peer-reviewed
- Hackl, R., Tassini, L., Venturini, F., Hartinger, C., Erb, A., Kikugawa, N., & Fujita, T. (2005). Ordering phenomena in cuprates. In B. Kramer (Ed.), Advances in solid state physics (Vol. 45, pp. 227–238). Springer. https://doi.org/10.1007/11423256_18
- Venturini, F. (2003). Evidence for a metal-insulator transition in overdoped Cuprates : new Raman results. In B. Kramer (Ed.), Advances in solid state physics (pp. 253–266). Springer. https://doi.org/10.1007/978-3-540-44838-9_18
Written conference contributions, peer-reviewed
- Venturini, F. (2025). Innovative sensor technologies for agrifood quality assessment [Conference paper]. SMSI 2025 Conference Proceedings, 188–189. https://doi.org/10.5162/SMSI2025/D2.1
- Venturini, F., Fluri, S., Mejari, M., Baumgartner, M., Piga, D., & Michelucci, U. (2024). Machine learning-enhanced fluorescence spectroscopy for the quality assessment of extra virgin olive oil during ageing [Conference paper]. In F. Berghmans & I. Zergioti (Eds.), Optical Sensing and Detection VIII (p. 129991F). SPIE. https://doi.org/10.1117/12.3016879
- Gucciardi, A., El Ghazouali, S., Michelucci, U., & Venturini, F. (2024). Machine learning feature extraction for predicting the ageing of olive oil [Conference paper]. In T. Bocklitz (Ed.), Data Science for Photonics and Biophotonics (p. 130110A). SPIE. https://doi.org/10.1117/12.3017680
- Mathys, M., Gebbers, P., & Venturini, F. (2024, April 9). Probing carotenoids in the skin using resonant Raman spectroscopy. SPIE Photonics Europe, Strasbourg, France, 7-11 April 2024. https://spie.org/photonics-europe/presentation/Probing-carotenoids-in-the-skin-using-resonant-Raman-spectroscopy/13010-48?enableBackToBrowse=true
- Schmid, C., Laurenzi, E., Michelucci, U., & Venturini, F. (2023). Explainable AI for the olive oil industry [Conference paper]. In K. Hinkelmann, F. J. López-Pellicer, & A. Polini (Eds.), Perspectives in Business Informatics Research (pp. 158–171). Springer. https://doi.org/10.1007/978-3-031-43126-5_12
- Michelucci, U., Fluri, S., Baumgartner, M., & Venturini, F. (2023). Deep learning super resolution for high-speed excitation emission matrix measurements [Conference paper]. In B. Jalali & K.-i. Kitayama (Eds.), AI and Optical Data Sciences IV (Vol. 12438). SPIE. https://doi.org/10.1117/12.2647589
- Venturini, F., Michelucci, U., Sperti, M., Gucciardi, A., & Deriu, M. A. (2023). Understanding the learning mechanism of convolutional neural networks applied to fluorescence spectra [Conference paper]. In B. Jalali & K.-i. Kitayama (Eds.), AI and Optical Data Sciences IV (Vol. 124380). SPIE. https://doi.org/10.1117/12.2647809
- Sperti, M., Gucciardi, A., Michelucci, U., Venturini, F., & Deriu, M. Agostino. (2022). Chemical analysis of olive oils from fluorescence spectra thanks to one-dimensional convolutional neural networks [Conference paper]. SPIE Photonics Europe, Strasbourg, France, 3-7 April 2022, 121391K. https://doi.org/10.1117/12.2621666
- Arnaud, G., Michelucci, U., Venturini, F., Sperti, M., Martos, V. M., & Deriu, M. A. (2022). Compact optical fluorescence sensor for food quality control using artificial neural networks: application to olive oil [Conference paper]. In F. Berghmans & I. Zergioti (Eds.), Optical Sensing and Detection VII (p. 121391J). Society of Photo-Optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.2621588
- Venturini, F., Michelucci, U., Sperti, M., Gucciardi, A., & Deriu, M. A. (2022). One-dimensional convolutional neural networks design for fluorescence spectroscopy with prior knowledge : explainability techniques applied to olive oil fluorescence spectra [Conference paper]. In F. Berghmans & I. Zergioti (Eds.), Optical Sensing and Detection VII (p. 1213917). Society of Photo-Optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.2621646
- Gucciardi, A., Michelucci, U., Venturini, F., Sperti, M., Martos, V. M., & Deriu, M. A. (2022, April 6). Compact optical fluorescence sensor for food quality control using artificial neural networks: application to olive oil. SPIE Photonics Europe, Strasbourg, France, 3-7 April 2022. https://doi.org/10.1117/12.2621588
- Sperti, M., Michelucci, U., Venturini, F., Gucciardi, A., & Deriu, M. A. (2022, April 6). Chemical analysis of olive oils from fluorescence spectra thanks to one-dimensional convolutional neural networks. SPIE Photonics Europe, Strasbourg, France, 3-7 April 2022. https://spie.org/EPE/conferencedetails/optical-sensing-detection
- Venturini, F., Michelucci, U., & Baumgartner, M. (2021). New approach for temperature-immune oxygen sensing based on Pt-TFPP [Conference paper]. OSA Technical Digest, SW5H. https://doi.org/10.1364/SENSORS.2021.SW5H.2
- Venturini, F., Michelucci, U., & Baumgartner, M. (2021). Implementation of multi-task learning neural network architectures for robust industrial optical sensing [Conference poster]. In P. Lehmann, W. Osten, & A. Albertazzi Gonçalves Jr. (Eds.), Optical Measurement Systems for Industrial Inspection XII. Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.2593469
- Venturini, F., Michelucci, U., & Baumgartner, M. (2021). Implementation of multi-task learning neural network architectures for robust industrial optical sensing [Conference paper]. In P. Lehmann, W. Osten, & A. Albertazzi Gonçalves Jr. (Eds.), Optical Measurement Systems for Industrial Inspection XII (p. 117822H). Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.2593469
- Michelucci, U., & Venturini, F. (2021). New autonomous intelligent sensor design approach for multiple parameter inference [Conference paper]. Engineering Proceedings, 2(1), 96. https://doi.org/10.3390/engproc2020002096
- Venturini, F., Michelucci, U., & Baumgartner, M. (2020). Dual oxygen and temperature sensing with single indicator using multi-task-learning neural networks [Conference paper]. Proceedings Volume 11354 : Optical Sensing and Detection VI, 113541C. https://doi.org/10.1117/12.2554941
- Venturini, F., Michelucci, U., & Baumgartner, M. (2020). Deep-learning for multi-parameter luminescence sensing : demonstration of dual sensor. Proceedings Frontiers in Optics / Laser Science.
- Venturini, F., Michelucci, U., & Baumgartner, M. (2020, January 27). Multi-task learning approach for optical luminescence sensing. Applied Machine Learning Days (AMLD), Lausanne, 25-29 January 2020.
- Venturini, F., Baumgartner, M., & Michelucci, U. (2019). New approach for luminescence sensing based on machine learning [Conference paper]. In B. Jalali & K.-i. Kitayama (Eds.), Proceedings Volume 10937 : Optical Data Science II (Issue 109370H). SPIE. https://doi.org/10.1117/12.2508969
- Venturini, F., Baumgartner, M., & Borisov, S. M. (2018). New opportunities for optical temperature sensing with Mn4+-doped magnesium titanate. Advanced Photonics 2018. https://doi.org/10.1364/BGPPM.2018.JTu2A.63
- Venturini, F., Schönherr, V., & Adolfsson, E. (2017). Ultracompact oxygen sensor using nanoporous materials as strongly-scattering multipass cell for tunable diode laser absorption spectroscopy. The European Conference on Lasers and Electro-Optics 2017.
- Venturini, F., & Michelucci, U. (2017). Novel algorithm for calibration-free absorption spectroscopy sensor [Conference paper]. Proceedings, 1(833). https://doi.org/10.3390/proceedings1080833
- Venturini, F., Schönherr, V., Rey, J., & Adolfsson, E. (2016). Characterization of light-gas interaction in strongly-scattering nanoporous materials and its implications for tunable diode laser absorption spectroscopy. International Conference on Field Laser Applications in Industry and Research (FLAIR 2016), Aix-Les-Bains, Frankreich, 12.-16. September 2016.
- Borisov, S., Klimant, I., Bürgi, R., & Venturini, F. (2015). Temperature sensing and sensor design using a new thermographic phosphor for a wide range of applications. Proceedings 2015 European Conference on Lasers and Electro-Optics - European Quantum Electronics Conference.
- Borisov, S., Klimant, I., Schönherr, V., Bürgi, R., & Venturini, F. (2015). Investigation of the Luminescence Emission of Chromium(III)-Doped Yttrium Aluminum Borate for the Design of an Optical Temperature Sensor. MAF 14, the 14th Conference on Methods and Applications in Fluorescence, Würzburg, Germany, 13-16 September 2015.
- Venturini, F., Michelucci, U., Devereaux, T. P., & Kampf, A. P. (2000). Collective modes and electronic raman scattering in the cuprates [Conference paper]. Physica C: Superconductivity and Its Applications, 340, 2265–2266. https://doi.org/10.1016/S0921-4534(00)00972-2
- Minardi, F., Knight, D. J. E., Arie, A., Pavone, F. S., Venturini, F., & Inguscio, M. (1997). Frequency doubling of 1083 nm diode-laser radiation for locking to iodine absorption [Conference paper]. In Z. Zhang (Ed.), Laser Spectroscopy: Xiii International Conference : Hangzhou, China 2-7 June 1997. World Scientific.
Other publications
Venturini, F., Sperti, M., Michelucci, U., Gucciardi, A., & Martos, V. (2023). Dataset of fluorescence spectra and chemical parameters of olive oils. SPIE Photonics West, San Francisco, USA, 28 January - 2 February 2023. https://doi.org/10.48550/arXiv.2301.04471
Oral conference contributions and abstracts
- Venturini, F. (2025). Overcoming intrinsic limitations of fluorescence spectroscopy data in food quality and safety with machine learning and deep learning [Conference presentation]. Optica Sensing Congress 2025 (AIS, Sensors, QSM), AM2E. https://doi.org/10.1364/AIS.2025.AM2E.3
- Venturini, F. (2025, May 6). Innovative sensor technologies for agrifood quality assessment. Sensor and Measurement Science International, Nuremberg, Germany, 6-8 May 2025.
- Gucciardi, A., El Ghazouali, S., Michelucci, U., & Venturini, F. (2024, April 11). Machine learning feature extraction for predicting the ageing of olive oil. SPIE Photonics Europe, Strasbourg, France, 7-11 April 2024. https://doi.org/10.1117/12.3017680
- Venturini, F., Fluri, S., Mejari, M., Baumgartner, M., Piga, D., & Michelucci, U. (2024, April 10). Machine learning-enhanced fluorescence spectroscopy for the quality assessment of extra virgin olive oil during ageing. SPIE Photonics Europe, Strasbourg, France, 7-11 April 2024. https://doi.org/10.1117/12.3016879
- Venturini, F., Michelucci, U., Sperti, M., Gucciardi, A., & Deriu, M. A. (2023, February 1). Understanding the learning mechanism of convolutional neural networks applied to fluorescence spectra. SPIE Photonics West, San Francisco, USA, 28 January - 2 February 2023.
- Venturini, F., Michelucci, U., Sperti, M., Gucciardi, A., & Deriu, M. A. (2022, April 7). One-dimensional convolutional neural networks design for fluorescence spectroscopy with prior knowledge : explainability techniques applied to olive oil fluorescence spectra. SPIE Photonics Europe, Strasbourg, France, 3-7 April 2022. https://spie.org/photonics-europe/presentation/One-dimensional-convolutional-neural-networks-design-for-fluorescence-spectroscopy-with/12139-60
- Venturini, F., Michelucci, U., & Baumgartner, M. (2021, July 21). New approach for temperature-immune oxygen sensing based on Pt-TFPP. OSA Optical Sensors and Sensing Congress, Online, 19-23 July 2021. https://osa.zoom.us/rec/play/MvNgUQyUZcCHsaYidUEieFhKJSC_0H951ohgwMQLgaJu2hOUG4Cp8c6EbckrxwSFPVgA4icXYkOKpYHl.bke5ll04aQIuRasd?continueMode=true&_x_zm_rtaid=rEeKPUbBRbuPidh8EtTeUQ.1630395453945.87ac6bdfd1c3781b0e74319831d7e46a&_x_zm_rhtaid=928
- Venturini, F., Michelucci, U., & Baumgartner, M. (2020). Deep-learning for multi-parameter luminescence sensing : demonstration of dual sensor. OSA Frontiers in Optics / Laser Science, Online, 14-17 September 2020.
- Venturini, F., Michelucci, U., & Baumgartner, M. (2020, April 1). Dual oxygen and temperature sensing with single indicator using multi-task-learning neural networks. SPIE Photonics Europe, Digital Forum, France, 6 - 10 April 2020.
- Venturini, F. (2020, January 22). Applications of ML to oxygen sensing. Deep Learning Meets (Astro)physics : A One Day Tutorial on Neural Nets, Deep Learning and TensorFlow 2.0, with Applications to (Astro)physics and Science, ETHZ, Institute for Particle Physics and Astrophysics, Zurich (Switzerland), 22 January 2020. https://sites.google.com/view/dl-meets-astrophysics-2020/
- Venturini, F., & Baumgartner, M. (2019). New approach for luminescence sensing based on machine learning. SPIE OPTO, San Francisco, USA, 2-7 February 2019.
- Venturini, F. (2016, March 31). Progress in NIR spectroscopy and its industrial applications. Swiss Photonics Optical Sensing Workshop : From THz to X-Ray - Inventing the Future, Zurich (Switzerland), 31 March 2016. https://www.swissphotonics.net/workshops/workshop-datenbank?2914
- Venturini, F., Dumont, E., Fuchs, H. U., & Maurer, W. (2014). From forces of nature to the physics of dynamical systems. 9th International Conference on Conceptual Change, Bologna, Italy, 26-29 August 2014.
Research data
Venturini, Francesca; Sperti, Michela; Michelucci, Umberto; Gucciardi, Arnaud; Martos, Vanessa; Deriu, Marco Agostino, 2022. Dataset of fluorescence spectra and chemical parameters of olive oils. Mendeley Data. Available from: https://doi.org/10.17632/thkcz3h6n6.6
Patents and patent applications
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Bergström, Pär Wilhelm; Tazreiter, Martin; Kondziella, Ralph; Venturini, Francesca; Hertel, Martin,
2025.
Patent number US12480865 B2
(2025-11-25)
.
Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DUS12480865B2
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Venturini, Francesca; Bergstroem, Paer; Hertel, Martin,
2022.
Patent number US11327008 B2
(2022-05-10)
.
Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DUS11327008B2
-
Fischer, Milan; Ulmer, Lilya; Venturini, Francesca,
2020.
Patent number EP3333568 B1
(2020-06-24)
.
Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DEP3333568B1
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Venturini, Francesca; Mock, Patrick; Schauwecker, Robert,
2017.
Horizontal magnet arrangement with radial access.
Patent number DE102007013349 B4
(2017-11-02)
.
Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DDE102007013349B4
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Venturini, Francesca; Vanoni, Claudio,
2017.
Messverfahren für einen optochemischen Sensor.
Patent number EP2887054 B1
(2017-02-22)
.
Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DEP2887054B1
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Vanoni, Claudio; Venturini, Francesca; Kleinlogel, Christoph,
2015.
Method of operating an optochemical sensor.
Patent number US9103795 B2
(2015-08-11)
.
Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DUS9103795B2
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Venturini, Francesca; Schauwecker, Robert; Bovier, Pierre-Alain,
2013.
Superconductive magnet assembly with hysteresis-free magnetic coils.
Patent number EP1990648 B1
(2013-08-14)
.
Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DEP1990648B1
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Allgaeuer, Mario; Ehrismann, Philippe; Meier, Dario; Ufheil, Joachim; Vayhinger, Marcus; Venturini, Francesca,
2013.
A Sensor utilizing a clamping mechanism.
Patent number WO2013083759 A1
(2013-06-13)
.
Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DWO2013083759A1
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Radanovic, Dragan; Venturini, Francesca,
2013.
Patent number EP2573548 A1
(2013-03-27)
.
Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DEP2573548A1