PhD Student in Ingegneria dell’Informazione at Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Firenze. My research interests are machine learning, neural networks, large-scale and non-linear optimization.


  • On the convergence of inexact augmented Lagrangian methods for problems with convex constraints. G. Galvan & M. Lapucci. Operations Research Letters 2019. (https://doi.org/10.1016/j.orl.2019.03.006)
  • An Alternating Augmented Lagrangian method for constrained nonconvex optimization. G. Galvan, M. Lapucci, T. Levato & M. Sciandrone. Optimization Methods and Software 2019.  (https://doi.org/10.1080/10556788.2019.1576177)
  • Biomarkers of erosive arthritis in systemic lupus erythematosus: Application of machine learning models. Ceccarelli F, Sciandrone M, Perricone C, Galvan G, Cipriano E, et al. PLOS ONE 2018. (https://doi.org/10.1371/journal.pone.0207926)
  • Machine learning methods for short-term bid forecasting in the renewable energy market: A case study in ItalyCocchi GGalli LGalvan GSciandrone MCantù MTomaselli GWind Energy2018;115. (https://doi.org/10.1002/we.2166)
  • Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models.  Ceccarelli F, Sciandrone M, Perricone C, Galvan G, Morelli F, et al. PLOS ONE 2017.(https://doi.org/10.1371/journal.pone.0174200).

My ORCID number: 0000-0002-0384-0334.


  • ISMP 18 – An Alternating Augmented Lagrangian method for constrained nonconvex optimization. (slides.pdf)

Phone: +39 3349486905
E-mail: giulio.galvan@gmail.com