Dr. Simone Ulzega

Persönliches Profil

Tätigkeit an der ZHAW

Senior Wissenschaftliche Mitarbeiter

www.zhaw.ch/ias

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

Mathematical and computational methods for complex systems dynamics, high-performance computing

Aus- und Fortbildung

M.Sc., Physik / Quantenoptik, Università di Milano (Italien)
Doktorat, Atomphysik, Université de Fribourg (Schweiz)

Beruflicher Werdegang

Postdoc, EPFL, Lausanne, biomolecular NMR spectroscopy, protein dynamics, high-performance computing.

F&E Wissenschaftler, Bruker BioSpin AG, Fällanden, measurements methods and software for NMR spectroscopy.

Wissenschaftler, Eawag, Dübendorf, complex systems dynamics in environmental sciences, mathematical and computational methods, high-performance computing.

Projekte

• Feature Learning for Bayesian Inference / Teammitglied / Projekt laufend
• Maschinelles Lernen für NMR-Spektroskopie / Teammitglied / Projekt abgeschlossen
• Data mining in neurological medicine / ProjektleiterIn / Projekt abgeschlossen
• Digitale Simulation zur individualisierten Fertigung von 3D Nanofaserfilter und Integration in Vollschutzanzug für Pandemiefälle / Teammitglied / Projekt abgeschlossen
• BISTOM - Bayesian Inference with Stochastic Models / ProjektleiterIn / Projekt abgeschlossen
• A cloud-based IoT approach for food safety and quality prediction / Teammitglied / Projekt abgeschlossen
• Advanced Bayesian inference with stochastic hydrological models / Teammitglied / Projekt abgeschlossen

Publikationen

• Bacci, Marco; Sukys, Jonas; Reichert, Peter; Ulzega, Simone; Albert, Carlo,

  2023.

  A comparison of numerical approaches for statistical inference with stochastic models.

  Stochastic Environmental Research and Risk Assessment.

  Verfügbar unter: https://doi.org/10.1007/s00477-023-02434-z

• Ulzega, Simone; Albert, Carlo,

  2023.

  Bayesian parameter inference in hydrological modelling using a Hamiltonian Monte Carlo approach with a stochastic rain model.

  Hydrology and Earth System Sciences.

  27(15), S. 2935-2950.

  Verfügbar unter: https://doi.org/10.5194/hess-27-2935-2023

• Castelnovo, Anna; Amacker, Julian; Maiolo, Massimo; Amato, Ninfa; Pereno, Matteo; Riccardi, Silvia; Danani, Andrea; Ulzega, Simone; Manconi, Mauro,

  2022.

  High-density EEG power topography and connectivity during confusional arousal.

  Cortex.

  (155), S. 62-74.

  Verfügbar unter: https://doi.org/10.1016/j.cortex.2022.05.021

• Albert, Carlo; Ulzega, Simone; Ozdemir, Firat; Perez-Cruz, Fernando; Mira, Antonietta,

  2022.

  Learning summary statistics for Bayesian inference with autoencoders.

  SciPost Physics Core.

  5(3), S. 043.

  Verfügbar unter: https://doi.org/10.21468/SciPostPhysCore.5.3.043

• Albert, Carlo; Ferriz-Mas, Antonio; Gaia, Filippo; Ulzega, Simone,

  2021.

  Can stochastic resonance explain recurrence of Grand Minima?.

  The Astrophysical Journal Letters.

  916(2), S. L9.

  Verfügbar unter: https://doi.org/10.3847/2041-8213/ac0fd6

• Maiolo, Massimo; Ulzega, Simone; Gil, Manuel; Anisimova, Maria,

  2020.

  Accelerating phylogeny-aware alignment with indel evolution using short time Fourier transform.

  NAR Genomics and Bioinformatics.

  2(4), S. lqaa092.

  Verfügbar unter: https://doi.org/10.1093/nargab/lqaa092

• Weyland, Mathias S.; Thumser-Henner, Pauline; Nytko, Katarzyna J.; Rohrer Bley, Carla; Ulzega, Simone; Petri-Fink, Alke; Lattuada, Marco; Füchslin, Rudolf Marcel; Scheidegger, Stephan,

  2020.

  Holistic view on cell survival and DNA damage : how model-based data analysis supports exploration of dynamics in biological systems.

  Computational and Mathematical Methods in Medicine.

  2020.

  Verfügbar unter: https://doi.org/10.1155/2020/5972594

• Albert, Carlo; Ulzega, Simone; Stoop, Ruedi,

  2016.

  Boosting Bayesian parameter inference of nonlinear stochastic differential equation models by Hamiltonian scale separation.

  Physical Review E.

  93(4).

  Verfügbar unter: https://doi.org/10.1103/PhysRevE.93.043313

• Cousin, Samuel; Charlier, Cyril; Kadeřávek, Pavel; Marquardsen, Thorsten; Tyburn, Jean-Max; Bovier, Pierre-Alain; Ulzega, Simone; Speck, Thomas; Wilhelm, Dirk; Engelke, Frank; Maas, Werner; Sakellariou, Dimitrios; Bodenhausen, Geoffrey; Pelupessy, Philippe; Ferrage, Fabien,

  2016.

  High-resolution two-field nuclear magnetic resonance spectroscopy.

  Physical Chemistry Chemical Physics.

  18(48), S. 33187-33194.

  Verfügbar unter: https://doi.org/10.1039/C6CP05422F

• Ulzega, Simone; Albert, Carlo,

  2019.

  Bayesian inference for solar dynamo models [Poster].

  In:

  1st Swiss “Workshop on Machine Learning for Environmental and Geosciences” (MLEG2019), Dübendorf, 16-17 January 2019.

• Weyland, Mathias; Thumser-Henner, Pauline; Rohrer Bley, Carla; Ulzega, Simone; Petri-Fink, Alke; Lattuada, Marco; Scheidegger, Stephan; Füchslin, Rudolf Marcel,

  2019.

  Dynamic DNA damage and repair modelling : bridging the gap between experimental damage readout and model structure [Paper].

  In:

  Cagnoni, Stefano; Mordonini, Monica; Pecori, Riccardo; Roli, Andrea; Villani, Marco, Hrsg.,

  Artificial Life and Evolutionary Computation.

  XIII International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Parma, Italy, 10-12 September 2018.

  Cham:

  Springer.

  S. 127-137.

  Communications in Computer and Information Science ; 900.

  Verfügbar unter: https://doi.org/10.1007/978-3-030-21733-4_10

• Ulzega, Simone; Albert, Carlo,

  2019.

  Bayesian parameter inference with stochastic solar dynamo models [Poster].

  In:

  Platform for Advanced Scientific Computing (PASC19), Zurich, 12-14 June 2019.

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Verfügbar unter: https://doi.org/10.21256/zhaw-3225

• Ulzega, Simone,

  2018.

  Calibrating stochastic models for understanding solar activity.

  Transfer.

  2018(1), S. 8.

  Verfügbar unter: https://doi.org/10.21256/zhaw-3851

• Ulzega, Simone,

  2017.

  Boosting Bayesian parameter inference of stochastic differential equation models [Poster].

  In:

  Life in Numbers 3, Wädenswil, 31 August 2017.

• Ulzega, Simone,

  2017.

  Boosting parameter inference with stochastic models using molecular dynamics and high-performance computing.

• Ulzega, Simone; Albert, Carlo; Beer, Jürg,

  2023.

  Shedding light on the sun through the calibration of solar dynamo models on millennial records of solar activity.

  In:

  5th Swiss SCOSTEP Workshop, Windisch, Switzerland, 15-16 May 2023.

  Verfügbar unter: http://scostep2023.cs.technik.fhnw.ch/pres/ulzega_scostep_2023.pdf

• Ulzega, Simone; Albert, Carlo,

  2023.

  Boosting Bayesian parameter inference of SDE models by Hamiltonian scale separation : a real-world case study in urban hydrology.

  In:

  3rd biennial meeting of the ISBA Section on Bayesian Computation (Bayes Comp), Levi, Finnland, 15-17 March 2023.

• Ulzega, Simone; Albert, Carlo,

  2022.

  Bayesian parameter inference in hydrological modelling using a Hamiltonian Monte Carlo approach with a stochastic rain model.

  In:

  EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022.

  Verfügbar unter: https://doi.org/10.5194/egusphere-egu22-8729

• Albert, Carlo; Gaia, Filippo; Ulzega, Simone,

  2020.

  Can stochastic resonance explain the amplification of planetary tidal forcing?.

  In:

  EGU General Assembly 2020, Online, 4-8 May 2020.

  Verfügbar unter: https://presentations.copernicus.org/EGU2020/EGU2020-15185_presentation.pdf

• Albert, Carlo; Ulzega, Simone,

  2020.

  Stochastic resonance could explain recurrence of Grand Minima.

  In:

  EGU General Assembly 2020, online, 4-8 May 2020.

  Verfügbar unter: https://doi.org/10.5194/egusphere-egu2020-15185

• Ulzega, Simone; Albert, Carlo,

  2019.

  Bayesian inference methods for the calibration of stochastic dynamo models.

  In:

  4th Solar Dynamo Thinkshop, Rome, Italy, 25 - 26 November 2019.

• Albert, Carlo; Ulzega, Simone,

  2019.

  Can stochastic resonance explain the amplification of planetary tidal forcing?.

  In:

  4th Solar Dynamo Thinkshop, Rome, Italy, 25 - 26 November 2019.

• Ulzega, Simone; Albert, Carlo,

  2018.

  Bayesian parameter inference with stochastic solar dynamo models.

  In:

  NDES 2018, 26th Nonlinear Dynamics of Electronic Systems Conference, Acireale, Italy, June, 11-13 2018.

• Ulzega, Simone; Albert, Carlo; Abreu, Josè; Beer, Jürg,

  2018.

  Is there a planetary influence on solar activity? Some insights from nonlinear dynamics and Bayesian statistics.

  In:

  Biannual Workshop on Solar Physics, Freiburg, Germany, 7-9 May 2018.

• Ulzega, Simone,

  2018.

  A Hamiltonian Monte Carlo method for boosting Bayesian parameter inference of stochastic differential equation models.

  In:

  Kick-off Workshop for SDSC-ETH BISTOM project at Eawag, Dübendorf, Germany, 10 January 2018.

• Weyland, Mathias; Thumser-Henner, Pauline; Rohrer Bley, Carla; Ulzega, Simone; Petri-Fink, Alke; Lattuada, Marco; Scheidegger, Stephan; Füchslin, Rudolf Marcel,

  2018.

  Dynamic DNA damage and repair modeling : bridging the gap between experimental damage readout and model structure.

  In:

  XIII International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Parma, Italy, 10-12 September 2018.

• Ulzega, Simone,

  2017.

  A Hamiltonian Monte Carlo method for boosting Bayesian parameter inference of stochastic differential equation models.

  In:

  NDES 2017, 25th Nonlinear Dynamics of Electronic Systems Conference, Zernez, 5-7 June 2017.

Publikationen vor Tätigkeit an der ZHAW

C. Albert, S. Ulzega, R. Stoop, Boosting Bayesian Parameter Inference of Nonlinear Stochastic Differential Equation Models by Hamiltonian Scale Separation, Phys. Rev. E 93, 043313 (2016)

N. Salvi, S. Ulzega, F. Ferrage, G. Bodenhausen, Timescales of slow motions in ubiquitin explored by heteronuclear double resonance, J. Am. Chem. Soc. 134, 2481 (2012)

V. Vitzthum, M. A. Caporini, S. Ulzega, G. Bodenhausen, Broadband excitation and indirect detection of nitrogen-14 in rotating solids using Delays Alternating with Nutation (DANTE), J. Magn. Reson. 212, 234 (2011)

S. Ulzega, N. Salvi, T. F. Segawa, F. Ferrage, G. Bodenhausen, Control of cross relaxation of multiple-quantum coherences induced by fast chemical exchange under heteronuclear double-resonance irradiation, ChemPhysChem 12, 333 (2011)

S. Ulzega, New tools in BioNMR: indirect detection of nitrogen-14 in solids, Chimia (invited contribution) 64(3), 157 (2010)

S. Ulzega, M. Verde, F. Ferrage, G. Bodenhausen, Heteronuclear double resonance in NMR spectroscopy: relaxation of multiple-quantum coherences, J. Chem. Phys. 131, 224503 (2009)

S. Cavadini, A. Abraham, S. Ulzega, G. Bodenhausen, Evidence for dynamics on a 100 ns time-scale from single- and double-quantum nitrogen-14 NMR in solid peptides, J. Am. Chem. Soc. 130(33), 10850 (2008)

P. Moroshkin, A. Hofer, S. Ulzega, A. Weis, Impurity-stabilized solid 4He below the solidification pressure of pure helium, Nature Physics 3, 786-789 (2007)

S. Ulzega, A. Hofer, P. Moroshkin, R. Müller-Siebert, D. Nettels, A. Weis, Measurement of the forbidden electric tensor polarizability of Cs atoms trapped in solid 4He, Phys. Rev. A 75, 042505 (2007)

S. Ulzega, A. Hofer, P. Moroshkin, A. Weis, Reconciliation of experimental and theoretical electric tensor polarizabilities of the Cs ground state, Europhys. Lett. 76(6), 1074 (2006)

P. Moroshkin, A. Hofer, S. Ulzega, A. Weis, Spectroscopy of atomic and molecular defects in solid 4He using optical, microwave, radio frequency, magnetic and electric fields, Low Temp. Phys. 32(11), 981 (2006)

D. Nettels, A. Hofer, P. Moroshkin, R. Müller-Siebert, S. Ulzega, A. Weis, Discovery of dumbbell-shaped Cs*He_n exciplexes in solid 4He, Phys. Rev. Lett. 94, 063001 (2005)

Zurück