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* – indicates Corresponding Author
# – indicates a supervised Master student, PhD student or Postdoctoral collaborator

 

Journal articles

  1. Begu#, B., Panzeri#, S., Arnone, E., Carey, M., and Sangalli*, L.M. (2024),
    A nonparametric penalized likelihood approach to density estimation of space-time point patterns,
    Spatial Statistics, To appear.
    Code
  2. Palummo#, A., Arnone, E., Formaggia, L., and Sangalli*, L.M. (2024),
    Functional principal component analysis for incomplete space-time data ,
    Environmental and Ecological Statistics, DOI: 10.1007/s10651-024-00598-7.
    PDF      Code
  3. Clementi#, L., Arnone, E., Santambrogio, M., Franceschetti, S., Panzica, F. and Sangalli*, L.M. (2023),
    Anatomically compliant modes of variations: new tools for brain connectivity,
    Plos One, DOI: 10.1371/journal.pone.0292450.
    PDF     Code
  4. Arnone, E., Negri#, L., Panzica, F. and Sangalli*, L.M. (2023),
    Analyzing data in complicated 3D domains: smoothing, semiparametric regression and functional principal component analysis,
    Biometrics, DOI: 10.1111/biom.13845.
    PDF     Code
  5. Ferraccioli#, F., Sangalli, L.M., Finos, L. (2023),
    Nonparametric tests for semiparametric regression models,
    TEST, DOI: 10.1007/s11749-023-00868-9.
    PDF     Code
  6. Arnone, E., De Falco, C., Formaggia, L., Meretti, G., and Sangalli, L.M. (2023),
    Computationally efficient techniques for spatial regression with differential regularization,
    International Journal of Computer Mathematics, DOI: 10.1080/00207160.2023.2239944.
    PDF     Code
  7. Arnone#, E., Kneip, A., Nobile, F. and Sangalli*, L.M. (2022),
    Some first results on the consistency of spatial regression with partial differential equation regularization,
    Statistica Sinica, 32, 209-238.
    PDF     Postprint
  8. Arnone#, E., Sangalli*, L.M. and Vicini, A. (2022),
    Smoothing spatio-temporal data with complex missing data patterns,
    Statistical Modelling, DOI: 10.1177/1471082X211057959. 
    PDF     Postprint     Code 
  9. Ferraccioli#, F., Sangalli*, L.M., Finos, L. (2022),
    Some first inferential tools for spatial regression with differential regularization,
    Journal of Multivariate Analysis, DOI: 10.1016/j.jmva.2021.104866. 
    PDF     Postprint
  10. Scimone, R., Menafoglio, A., Sangalli, L.M. and Secchi, P. (2022),
    A look at the spatio-temporal mortality patterns in Italy during the COVID-19 pandemic through the lens of mortality densities,
    Spatial Statistics, doi:10.1016/j.spasta.2021.100541. 
    PDF     Postprint
  11. Elias#, A., Jimenez, R., Paganoni, A.M. and Sangalli*, L.M. (2022),
    Integrated Depths for Partially Observed Functional Data,
    Journal of Computational and Graphical Statistics, doi:10.1080/10618600.2022.2070171.   
    PDF     Postprint
  12. Ponti#, L., Perotto, S. and Sangalli, L.M. (2022),
    A PDE-regularized smoothing method for space-time data over manifolds with application to medical data,
    International Journal for Numerical Methods in Biomedical Engineering, 38, 12, e3650.  
    PDF     Code 
  13. Arnone#, E., Ferraccioli#, F., Pigolotti#, C., Sangalli*, L.M. (2022),
    A roughness penalty approach to estimate densities over two-dimensional manifolds,
    Computational Statistics and Data Analysis, 174, 107527. 
    PDF     Postprint     Code
  14. Ferraccioli#, F., Arnone#, E., Finos, L., Ramsay, J.O., Sangalli*, L.M. (2021),
    Nonparametric density estimation over complicated domains,
    Journal of the Royal Statistical Society Ser. B, Statistical Methodology, 83, 346-368. 
    PDF     Code 
  15. Sangalli*, L.M. (2021),
    Spatial regression with partial differential equation regularization,
    International Statistical Review, 89, 3, 505-531. 
    PDF     Code 
  16. Sangalli*, L.M. (2020),
    A novel approach to the analysis of spatial and functional data over complex domains,
    Quality Engineering, 32, 2, 181-190, 
    followed by discussions and a rejoinder by the author
    PDF     Postprint     Code
  17. Sangalli*, L.M. (2020),
    Rejoinder,
    Quality Engineering, 32, 2, 197-198. 
    PDF
  18. Arnone#, E., Azzimonti#, A., Nobile, F., and Sangalli*, L.M. (2019),
    Modelling spatially dependent functional data via regression with differential regularization,
    Journal of Multivariate Analysis, 170, 275-295.
    PDF     Postprint     Code 
  19. Bernardi#, M.S., Carey, M., Ramsay, J.O., and Sangalli*, L.M. (2018),
    Modeling spatial anisotropy via regression with partial differential regularization,
    Journal of Multivariate Analysis, 167, 15-30.
    PDF     Postprint     Code 
  20. Sangalli*, L.M. (2018),
    The role of Statistics in the era of Big Data,
    Statistics & Probability Letter, 136, 1-3.
    PDF
  21. Stefanucci#, M., Sangalli*, L.M., and Brutti, P. (2018),
    PCA-based discrimination of partially observed functional data, with an application to Aneurisk65 dataset,
    Statistica Neerlandica, 72 (3), 246-264.
    PDF     Data
  22. Ballestrero, A. et al. (2018),
    Vector boson scattering: Recent experimental and theory developments,
    Reviews in Physics, 3, 44-63.
    PDF
  23. Bernardi#, M.S., Sangalli*, L.M., Mazza#, G., Ramsay, J.O. (2017),
    A penalized regression model for spatial functional data with application to the analysis of the production of waste in Venice province,
    Stochastic Environmental Research and Risk Assessment, 31 (1), 23-38.
    PDF     Postprint     Code 
  24. Paganoni, A.M., Sangalli*, L.M. (2017),
    Functional regression models: Some directions of future research,
    Statistical Modelling, 17 (1), 94-99.
    PDF
  25. Parodi#, A.C.L., Sangalli, L.M., Vantini, S., Amati, B. Secchi, P., Morelli, M.J. (2017), 
    FunChIP: a R/Bioconductor package for functional classification of ChIP-seq data,
    Bioinformatics, 33 (16), 2570–2572.
    PDF
  26. Lila#, E., Aston, J.A.D., Sangalli, L.M. (2016),
    Smooth Principal Component Analysis over two-dimensional manifolds with an application to Neuroimaging, 
    Annals of Applied Statistics, 10 (4), 1854-1879.
    PDF     Postprint     Code 
  27. Ettinger#, B., Perotto, S., Sangalli*, L.M. (2016),
    Spatial regression models over two-dimensional manifolds,
    Biometrika, 103 (1), 71-88.
    PDF     Postprint     Supplementary material     Code 
  28. Wilhelm#, M., Sangalli*, L.M. (2016),
    Generalized Spatial Regression with Differential Regularization,
    Journal of Statistical Computation and Simulation, 86 (13), 2497-2518.
    PDF     Postprint     Code 
  29. Wilhelm#, M., Dede’, L., Sangalli, L.M., Wilhelm, P. (2016),
    IGS: an IsoGeometric approach for Smoothing on surfaces,
    Computer Methods in Applied Mechanics and Engineering, 302, 70-89. 
    PDF     Postprint
  30. Bernardi#, M.S., Pelucchi, M., Stagni, A. Sangalli, L.M., Cuoci, A., Frassoldati, A., Secchi, P. Faravelli, T. (2016), 
    Curve Matching, a generalized framework for models/experiments comparison: an application to n-heptane combustion kinetic mechanisms,
    Combustion and Flame, Volume 168, June 2016, Pages 186-203.
    PDF
  31. Nicolai, N., Sangalli, L.M., Necchi, A., Giannatempo, P., Paganoni, A.M., Colecchia, M., Piva, L., Catanzaro, M., Biasoni, D., Stagni, S., Torelli, T., Raggi, D., Farè, E., Pizzocaro, G., Salvioni, R. (2016),
    A combination of cisplatin and 5-fluorouracil plus a taxane in patients undergoing lymph-node dissection for nodal metastases from squamous cell carcinoma (SCC) of the penis: treatment outcome and survival analyses in neo-adjuvant and adjuvant settings,
    Clinical Genitourinary Cancer, doi:10.1016/j.clgc.2015.07.009
  32. Marron, J.S., Ramsay, J.O., Sangalli, L.M., Srivastava, A. (2015),
    Functional Data Analysis of Amplitude and Phase Variation,
    Statistical Science, 30 (4), 468-484. 
    PDF
  33. Azzimonti#, L., Sangalli*, L.M., Secchi, P., Domanin, M., Nobile, F. (2015),
    Blood flow velocity field estimation via spatial regression with PDE penalization,
    Journal of the American Statistical Association, Theory and Methods, 110 (511), 1057-1071.
    PDF     Postprint     Supplementary material      Code 
  34. Cremona#, M.A., Sangalli, L.M., Vantini, S., Dellino, G.I., Pelicci, P.G., Secchi, P., Riva, L. (2015),
    Peak shape clustering reveals biological insights,
    BMC Bioinformatics, DOI: 10.1186/s12859-015-0787-6.
    PDF
  35. Dassi, F., Ettinger#, B., Perotto, S., Sangalli, L.M. (2015),
    A mesh simplification strategy for a spatial regression analysis over the cortical surface of the brain,
    Applied Numerical Mathematics, Vol. 90, pp. 111-131.
    PDF     Postprint     Code 
  36. Azzimonti#, L., Nobile, F., Sangalli*, L.M., Secchi, P. (2014),
    Mixed Finite Elements for spatial regression with PDE penalization,
    SIAM/ASA Journal on Uncertainty Quantification, Vol. 2, No. 1, pp. 305-335.
    PDF     Postprint     Code  
  37. Marron, J.S., Ramsay, J.O., Sangalli, L.M., Srivastava, A. (2014),  
    Statistics of Time Warpings and Phase Variations,
    Electronic Journal of Statistics, Vol. 8, No. 2, 1697-1702.  
    PDF  
  38. Bernardi#, M., Sangalli*, L.M., Secchi, P., Vantini, S. (2014), 
    Analysis of Proteomics data: Block K-mean Alignment,
    Electronic Journal of Statistics, Vol. 8, No. 2, 1714-1723.  
    PDF     Code  
  39. Patriarca#, M., Sangalli, L.M., Secchi, P., Vantini, S. (2014), 
    Analysis of Spike Train Data: an Application of K-mean Alignment,
    Electronic Journal of Statistics, Vol. 8, No. 2, 1769-1775.  
    PDF     Code  
  40. Bernardi#, M., Sangalli, L.M., Secchi, P., Vantini, S. (2014), 
    Analysis of Juggling Data: an Application of K-mean Alignment,
    Electronic Journal of Statistics, Vol. 8, No. 2, 1817-1824.  
    PDF     Code  
  41. Sangalli*, L.M., Secchi, P., Vantini, S. (2014), 
    AneuRisk65: A dataset of three-dimensional cerebral vascular geometries,
    Electronic Journal of Statistics, Vol. 8, No. 2, 1879-1890.  
    PDF     Data
  42. Sangalli*, L.M., Secchi, P., Vantini, S. (2014), 
    Analysis of AneuRisk65 data: K-mean Alignment,
    Electronic Journal of Statistics, Vol. 8, No. 2, 1891-1904. 
    PDF     Data     Code  
  43. Sangalli*, L.M., Secchi, P., Vantini, S. (2014), 
    Rejoinder: Analysis of AneuRisk65 data,
    Electronic Journal of Statistics, Vol. 8, No. 2, 1937-1939. 
    PDF     Data     Code  
  44. Dalla Rosa#, M., Sangalli, L.M., Vantini, S. (2014), 
    Principal Differential Analysis of the Aneurisk65 Data Set,
    Advances in Data Analysis and Classification, Vol. 8, Issue 3, pp. 287-302.  
    PDF     Data
  45. Sangalli, L.M., Secchi, P., Vantini, S. (2014), 
    Object Oriented Data Analysis: a few methodological challenges. Discussion of the paper An Overview of Object Oriented Data Analysis by Marron, J.S. and Alonso A.M., 
    Biometrical Journal, Vol. 56, Issue 5, pp. 774-777.
    PDF
  46. Sangalli*, L.M., Ramsay, J.O., Ramsay, T.O. (2013),
    Spatial spline regression models,
    Journal of the Royal Statistical Society Ser. B, Statistical Methodology, 75, 4, 681-703.
    PDF     Postprint     Code 
  47. Sorensen, H., Goldsmith, J., Sangalli, L.M. (2013),
    An introduction with medical applications to functional data analysis,
    Statistics in Medicine, 32 (30), 5222-5240. 
    PDF     Postprint     Data
  48. Pigoli#, D., Sangalli* L.M. (2012),
    Wavelets in Functional Data Analysis: estimation of multidimensional curves and their derivatives,
    Computational Statistics and Data Analysis, 56, 1482-1498.
    PDF     Postprint  
  49. Ammirati, E., Cannistraci, C.V., Cristell, N.A., Vecchio, V., Palini, A.G., Tornvall, P., Paganoni, A.M., Miendlarzewska, E.A., Sangalli, L.M., Monello, A., Pernow, J., Björnstedt Bennermo, M., Marenzi, G., Hu, D., Uren, N.G., Ravasi, T., Cianflone, D., Manfredi, A.A., Maseri, A. (2012), 
    Identification and Predictive Value of IL6(+)IL10(+) and IL6(-)IL10(+) Cytokine Patterns in ST-Elevation Acute Myocardial Infarction,
    Circulation Research, 111, 1336-1348.
  50. Passerini, T., Sangalli, L.M., Vantini, S., Piccinelli, M., Bacigaluppi, S., Antiga, L., Secchi, P., Veneziani, A. (2012), 
    An Integrated CFD-Statistical Investigation of Parent Vasculature of Cerebral Aneurysms,
    Cardiovascular Engineering and Technology, Vol. 3, No. 1, pp. 26-40.  
    PDF     Data     Code  
  51. Castruccio#, S., Bonaventura L., Sangalli, L.M. (2012),
    A Bayesian approach to spatial prediction with flexible variogram models,
    Journal of Agricultural, Biological, and Environmental Statistics, Vol. 17, No. 2, pp 209-227. 
    PDF     Postprint
  52. de Lalla, C., Rinaldi, A., Montagna, D., Azzimonti, L., Bernardo, M.E., Sangalli, L.M., Paganoni, A.M., Maccario, R., Di Cesare-Merlone, A., Zecca, M., Locatelli, F., Dellabona, P., Casorati, G. (2011), 
    Invariant NKT cell reconstitution in pediatric leukemia patients given HLA-haploidentical stem cell transplantation defines distinct CD4+ and CD4- subset dynamics and correlates with the remission state, 
    The Journal of Immunology, Vol. 186, pp. 4490-4499.
  53. Roberts, G.O., Sangalli*, L.M. (2010), 
    Latent diffusion models for survival analysis, 
    Bernoulli, Vol. 16, pp. 435-458.
    PDF
  54. Sangalli, L.M., Secchi, P., Vantini, S., Vitelli, V. (2010),
    K-means alignment for curve clustering,
    Computational Statistics and Data Analysis, Vol. 54, pp. 1219-1233. 
    PDF     Postprint     Data   Code  
  55. Sangalli, L.M., Secchi, P., Vantini, S., Vitelli, V. (2010),
    Functional clustering and alignment methods with applications,
    Communications in Applied and Industrial Mathematics, Vol. 1, No. 1, pp. 205-224. 
    PDF     Data   Code  
  56. Sangalli, L.M., Secchi, P., Vantini, S., Veneziani, A. (2009),
    Efficient estimation of three-dimensional curves and their derivatives by free knot regression splines, applied to the analysis of inner carotid artery centrelines,
    Journal of the Royal Statistical Society Ser. C, Applied Statistics, Vol. 58, No. 3, pp. 285-306.
    PDF     Postprint     Data
  57. Sangalli, L.M., Secchi, P., Vantini, S., Veneziani, A. (2009),
    A Case Study in Exploratory Functional Data Analysis: Geometrical Features of the Internal Carotid Artery,
    Journal of the American Statistical Association, Vol. 104, No. 485, pp. 37-48. 
    PDF     Postprint     Data
  58. Colecchia, M., Nicolai, N., Secchi, P., Bandieramonte, G., Paganoni, A.M., Sangalli, L.M., Piva, L., Salvioni, R. (2009),
    pT1 Penile Squamous Cell Carcinoma of the Penis: a Clinicopathologic Study of 56 Cases Treated by CO2 Laser Therapy,
    Analytical and Quantitative Cytology and Histology, Vol. 31, No. 3, pp. 153-160.
  59. Sangalli*, L.M. (2006),
    Some developments of the normalized random measures with independent increments,
    Sankhya: The Indian Journal of Statistics, Vol. 68, No. 3, pp. 461-487.
    PDF

    Book chapters

  60. Arnone, E., Cunial#, E., Sangalli, L.M. (2023). Generalized Spatio-Temporal Regression with PDE Penalization. In: Classification and Data Science in the Digital Age. Springer, pp 29–34.
    PDF     Code
  61. Scimone, R., Menafoglio, A., Sangalli, L.M., Secchi, P. (2023). The Death Process in Italy Before and During the Covid-19 Pandemic: A Functional Compositional Approach. In: Classification and Data Science in the Digital Age. Springer, pp 333–341.
    PDF
  62. Bernardi#, M.S. and Sangalli*, L.M. (2021), Modelling spatially dependent functional data by spatial regression with differential regularization, 
    in Geostatistical Functional Data Analysis, Wiley Series in Probability and Statistics, Wiley, 260-285.
    PDF     Code
  63. Arnone#, E., Bernardi#, M.S., Sangalli, L.M., Secchi, P. (2020),
    Analysis of Telecom Italia Mobile Phone Data by Space-time Regression with Differential Regularization,
    in Functional and High-Dimensional Statistics and Related Fields,
    Springer, Springer Ser. Contribution to Statistics, 5-10. 
    PDF     Code
  64. Arnone#, E., Kneip, A. Nobile, F. Sangalli, L.M. (2020),
    Some Numerical Test on the Convergence Rates of Regression with Differential Regularization,
    in Functional and High-Dimensional Statistics and Related Fields,
    Springer, Springer Ser. Contribution to Statistics, 11-18. 
    PDF     Code
  65. Ferraccioli#, F., Sangalli, L.M., Arnone#, E., Finos, L. (2020),
    A Functional Data Analysis Approach to the Estimation of Densities over Complex Regions,
    in Functional and High-Dimensional Statistics and Related Fields,
    Springer, Springer Ser. Contribution to Statistics, 77-82. 
    PDF     Code
  66. Eleonora Arnone#, Laura Azzimonti#, Fabio Nobile, Laura M. Sangalli (2017), A time-dependent PDE regularization to model functional data defined over spatio-temporal domains,
    in Functional Statistics and Related Fields, Springer, Springer Ser. Contribution to Statistics, 41-44.
    Code
  67. Eardi Lila#, John A. D. Aston, Laura M. Sangalli* (2017), Functional data analysis of neuroimaging signals associated with cerebral activity in the brain cortex,
    in Functional Statistics and Related Fields, Springer, Springer Ser. Contribution to Statistics, 169-172.
    Code
  68. Laura M. Sangalli* (2015), 
    Estimating surfaces and spatial fields via regression models with differential regularization,
    in Advances In Complex Data Modeling And Computational Methods In Statistics, Springer, Series Contribution to Statistics, pp. 191-209.
    Code
  69. Bree Ettinger#, Tiziano Passerini, Simona Perotto, Laura M. Sangalli* (2013), 
    Spatial smoothing for data distributed over non-planar domains,
    in Complex Models and Computational Methods in Statistics, Springer, Series Contribution to Statistics, p. 123-136.
    Code
  70. Laura M. Sangalli, Piercesare Secchi, Simone Vantini and Valeria Vitelli (2012),
    Joint Clustering and Alignment of Functional Data: an Application to Vascular Geometries,
    in Advanced Statistical Methods for the Analysis of Large Data-Sets, Springer, pp 33-43.
  71. James O. Ramsay, Tim Ramsay and Laura M. Sangalli* (2011),
    Spatial Functional Data Analysis,
    in Recent Advances in Functional Data Analysis and Related Topics, Contributions to Statistics, Springer Physica-Verlag, pp. 269-276.
  72. Davide Pigoli# and Laura M. Sangalli (2011),
    Wavelets smoothing for multidimensional curves,
    in Recent Advances in Functional Data Analysis and Related Topics, Contributions to Statistics, Springer Physica-Verlag, pp. 255-262.
  73. Laura M. Sangalli, Piercesare Secchi, Simone Vantini (2008),
    Explorative functional data analysis for 3D-geometries of the Inner Carotid Artery,
    in Functional and Operatorial Statistics, Springer Physica-Verlag, pp. 289-296.
  74. R.V. Ramamoorthi and Laura M. Sangalli (2006),
    On a characterization of Dirichlet distribution, 
    Bayesian Statistics and its Applications, pp. 385-397.

    Conference proceedings in WOS/Scopus journals

  75. Clementi, L., Gregorio, C, Savare’, L., Ieva, F, Santambrogio, M.D. Sangalli, L.M., A functional Data Analysis Approach to Left Ventricular Remodeling Assessment, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2021, pp. 3505-3508.
  76. Giannatempo, P., Paganoni, A. M., Sangalli, L.M., Colecchia, M., Piva, L., Catanzaro, M., Torelli, T., Farè, E., Raggi, D., Biasoni, D., Stagni, S., Pizzocaro, G., Salvioni, R., Nicolai, N. (2014), 
    Survival analyses of adjuvant or neoadjuvant combination of a taxane plus cisplatin and 5-fluorouracil (T-PF) in patients with bulky nodal metastases from squamous cell carcinoma of the penis (PSCC): Results of a single high-volume center,
    Journal Of Clinical Oncology,
    32, suppl 4, abstr 377.
  77. Nicolai, N., Sangalli, L.M., Necchi, A., Giannatempo, P., Paganoni, A.M., Colecchia, M., Piva, L., Catanzaro, M., Biasoni, D., Stagni, S., Torelli, T., Raggi, D., Farè, E., Crestani, A., Pizzocaro, G., Salvioni, R. (2014),
    Neo-adjuvant and adjuvant combination of a taxane plus cisplatin and 5-fluorouracil in patients undergoing lymph-node dissection for nodal metastases from squamous cell carcinoma (SCC) of the penis: Is there an indication for a recommendable use?,
    European Urology Supplements, Vol. 13, Issue 1, pp. e57.
  78. De Lalla, C., Rinaldi, A. , Montagna, D., Sangalli, L.M., Azzimonti, L., Paganoni, A.M., Maccario, R., Bernardo, M.E., Locatelli, F. Dellabona, P., Casorati, G. (2010),
    iNKT cell reconstitution in paediatric leukaemia patients following haploidentical stem cell transplantation suggests contribution to leukaemia control and reveals independent CD4+ and CD4-subset maturation programmes,
    Bone Marrow Transplantation, Vol. 45, pp. S206-S206.
  79. Ammirati, E., Cristell, N., Cannistraci, C., Paganoni, A.M., Sangalli, L., Monello, A., Uren, N., Manfredi, A., Cianflone, D., Maseri, A. (2009),
    Distinctive cytokine signature in patients with ST-Elevation Myocardial Infarction (STEMI) associated with high levels of circulating interleukin (IL)6,
    European Heart Journal, Vol. 30, Suppl. 1, pp. 934-935.
  80. Ammirati, E., Cristell, N., Cannistraci, C., Vecchio, V., Paganoni, A.M., Sangalli, L., Palini, A. Monello, A., Banfi, M., Uren, N., Manfredi, A., Cianflone, D., Maseri, A. (2009),
    Cytokine differentiation pattern in patients with st-elevation myocardial infarction (stemi) associated with high levels of circulating inteleukin (il)-6,
    Atherosclerosis Supplements, Vol. 10, No. 2, pp. e466.
  81. Bacigaluppi, S., Passerini, T, Sangalli, L.M., Secchi, P., Vantini, S., Vele, S., Veneziani, A. (2008),
    Analysis of cerebral vascular morphologies for assessing rupture risk in cerebral aneurysms,
    Journal of Biomechanics, Vol. 41, pp. S9.
  82. Colecchia, M., Nicolai, N., Secchi, P., Bandieramonte, G., Paganoni, A.M., Sangalli, L.M., Piva, L., Pizzocaro, G., Salvioni, R. (2008),
    Carbon-dioxide (CO2) laser microsurgery only for initially invasive squamous cell carcinoma (SCC) of the penis: A 25 years experience,
    European Urology Supplements 7, 3, Elsevier Science BV, p. 111.

    Other peer-reviewed conference proceedings

  83. Blerta Begu#, Simone Panzeri#, Eleonora Arnone, Laura M. Sangalli (2023),
    A Novel Spatio-Temporal Estimation Method for Occurrences Over Planar and Curved Regions,
    Proceedings of the GRASPA 2023 Conference. 
  84. Cristian Castiglione#, Eleonora Arnone, Mauro Bernardi, Alessio Farcomeni, Laura M. Sangalli (2023),
    Penalized quantile regression for spatial distributed data,
    Proceedings of the GRASPA 2023 Conference.  
  85. Michele Cavazzutti#, Eleonora Arnone, Federico Ferraccioli, Livio Finos, Cristina Galimberti#, Laura M. Sangalli (2023),
    A Novel Spatio-Sign-Flip tests for the nonparametric component in Spatial Regression with PDE regularization,
    Proceedings of the GRASPA 2023 Conference.  
  86. Aldo Clemente#, Eleonora Arnone, Jorge Mateu, Laura M. Sangalli (2023),
    Non-parametric density estimation over linear networks,
    Proceedings of the GRASPA 2023 Conference. 
  87. Alessandro Palummo#, Eleonora Arnone, Luca Formaggia, Laura M. Sangalli (2023),
    Functional principal component analysis for space-time data,
    Proceedings of the GRASPA 2023 Conference. 
  88. Simone Panzeri#, Blerta Begu#, Eleonora Arnone, Laura M. Sangalli (2023),
    An Estimation Tool for Spatio–Temporal Events over Curved Surfaces,
    Proceedings of “Statistics and Data Science Conference”. 
  89. Michele Cavazzutti#, Eleonora Arnone, Federico Ferraccioli, Livio Finos, Laura M. Sangalli (2023),
    Sign-Flip tests for spatial regression with differential regularization,
    Proceedings of “Statistics and Data Science Conference”. 
  90. Aldo Clemente#, Eleonora Arnone, Jorge Mateu, Laura M. Sangalli (2023),
    Spatial regression with differential regularization over linear networks,
    Proceedings of “Statistics and Data Science Conference”. 
  91. Ferraccioli#, F., Sangalli, L. M., Finos, L. (2019),
    Bounded Domain Density Estimation,
    Smart statistics for smart applications, 861-866. 
  92. Bernardi#, M.S., Carey, M., Ramsay, J.O., Sangalli, L.M. (2019),
    PDE-regularized regression for anisotropic spatial fields,
    Smart statistics for smart applications, 669-672. 
  93. Arnone#, E., Azzimonti#, L., Nobile, F., Sangalli, L.M. (2019),
    Regression with time-dependent PDE regularization for the analysis of spatio-temporal data,
    Smart statistics for smart applications, 649-652.
  94. Stefanucci#, M., Sangalli, L.M., Brutti, P. (2018),
    Classification of the Aneurisk65 dataset using PCA for partially observed functional data,
    Proceedings of the 49th Scientific Meeting of the Italian Statistical Society.
  95. Ferraccioli#, F., Sangalli, L.M., Finos, L. (2018),
    Nonparametric penalized likelihood for density estimation,
    Proceedings of the 49th Scientific Meeting of the Italian Statistical Society.
  96. Bernardi#, M.S., Mazza#, G., Ramsay, J.O., Sangalli, L.M. (2016),
    A penalized regression model for functional data with spatial dependence,
    Proceedings of the 48th Scientific Meeting of the Italian Statistical Society.
  97. Laura M. Sangalli* (2014),
    Statistical and Numerical Techniques for Spatial Functional Data Analysis,
    Contributions in infinite-dimensional statistics and related topics, Esculapio, pp. 239-244.
  98. Laura M. Sangalli* (2014),
    Functional data analysis in spaces of surfaces,
    Proceedings of the 47th Scientific Meeting of the Italian Statistical Society.
  99. Laura Azzimonti#, Laura M. Sangalli*, Piercesare Secchi (2014),
    Modeling prior knowledge on complex phenomena behaviors via partial differential equations, Proceedings of the 47th Scientific Meeting of the Italian Statistical Society.
  100. Marzia A. Cremona#, Pier Giuseppe Pelicci, Laura Riva, Laura M. Sangalli, Piercesare Secchi, and Simone Vantini (2014),
    Cluster analysis on shape indices for ChIP-Seq data},
    Proceedings of the 47th Scientific Meeting of the Italian Statistical Society.
  101. Laura Azzimonti#, Laura M. Sangalli, Piercesare Secchi (2013),
    Spatial regression with pde penalization: an application to blood velocity field estimation,
    Proceedings of S.Co.2013 Conference.
  102. Marzia A. Cremona#, Laura Riva, Laura M. Sangalli, Piercesare Secchi and Simone Vantini (2013), 
    Clustering chip-seq data using peak shape,
    Proceedings of S.Co.2013 Conference.
  103. Bree Ettinger#, Simona Perotto, Laura M. Sangalli (2013), 
    A functional data analysis approach to modeling spatially distributed data across several non-planar domains,
    Proceedings of S.Co.2013 Conference.
  104. Laura M. Sangalli* (2013), 
    On a novel class of models for spatial data analysis,
    Proceedings of S.Co.2013 Conference.
  105. Matthieu Wilhelm#, Laura M. Sangalli (2013), 
    Generalized models for spatial regression with differential penalization, 
    Proceedings of S.Co.2013 Conference.
  106. Bree Ettinger#, Simona Perotto, Laura M. Sangalli* (2013), 
    Studying hemodynamic forces via spatial regression models over non-planar domains, 
    Proceedings of the 2013 Conference of the Italian Statistical Society, Advances in Latent Variables – Methods, Models and Applications. 
  107. Laura M. Sangalli* and James O. Ramsay (2012),
    A novel method for spatial smoothing,
    Proceedings of the 46th Scientific Meeting of the Italian Statistical Society.
  108. Laura Azzimonti#, Laura M. Sangalli, Piercesare Secchi, Silvia Romagnoli and Maurizio Domanin (2012),
    PDE penalization for spatial fields smoothing,
    Proceedings of the 46th Scientific Meeting of the Italian Statistical Society.
  109. Bree Ettinger#, Simona Perotto, Laura M. Sangalli (2012),
    Spatial smoothing over non-planar domains,
    Proceedings of the 46th Scientific Meeting of the Italian Statistical Society.
  110. James O. Ramsay, Tim Ramsay and Laura M. Sangalli* (2011),
    Spatial spline regression models for data distributed over irregularly shaped regions,
    Proceedings of S.Co.2011 Conference.
  111. Laura Azzimonti#, Laura M. Sangalli and Piercesare Secchi (2011),
    Surface estimation via spatial spline models with PDE penalization,
    Proceedings of S.Co.2011 Conference.
  112. Laura M. Sangalli*, Piercesare Secchi, Simone Vantini, Valeria Vitelli (2010),
    Classification of Functional Data: Unsupervised Curve Clustering When Curves are Misaligned,
    2010 JSM Proceedings, pp. 4034-4047. 
  113. Tiziano Passerini, Alessandro Veneziani, Laura Sangalli, Piercesare Secchi, Simone Vantini (2010),
    Cerebral aneurysms: relations between geometry, hemodynamics and aneurysm location in the cerebral vasculature,
    Bulletin of the American Physical Society, Vol. 55, N. 16. 
  114. Laura Azzimonti#, Claudia De Lalla, Anna Maria Paganoni, Laura M. Sangalli (2010),
    Mixed effects models for growth curves.
    Proceedings of the XLV Scientific Meeting of the Italian Statistical Society. 
  115. Matilde Dalla Rosa#, Laura M. Sangalli and Simone Vantini (2010), 
    Data Reduction by means of Principal Differential Analysis: Application to the Study of the Geometrical Features of the Internal Carotid Artery. 
    Proceedings of the XLV Scientific Meeting of the Italian Statistical Society. 
  116. Laura M. Sangalli, Piercesare Secchi, Simone Vantini and Valeria Vitelli (2010),
    Functional clustering and alignment.
    Proceedings of the XLV Scientific Meeting of the Italian Statistical Society. 
  117. Davide Pigoli#, Laura M. Sangalli (2010),
    Wavelet smoothing for curves in more than one dimension.
    Proceedings of the XLV Scientific Meeting of the Italian Statistical Society.  
  118. Tiziano Passerini, Alessandro Veneziani, Laura M. Sangalli, Piercesare Secchi and Simone Vantini (2009),
    Wall shear stress in the Internal Carotid Artery and its relation to aneurysm location,
    Proceedings of CMBE2009, 1st International Conference on Mathematical and Computational Biomedical Engineering, edited by P. Nithiarasu and R. Lohner, pp. 163-166.
  119. Laura M. Sangalli, Piercesare Secchi, Simone Vantini and Valeria Vitelli (2009),
    Curve clustering for misaligned data: the k-mean alignment algorithm,
    Proceedings of S.Co.2009 Conference, Maggioli Eds, pp. 381–386.
  120. Laura M. Sangalli* (2009),
    Locally adaptive regression techniques for multidimensional curve fitting,
    Proceedings of S.Co.2009 Conference, Maggioli Eds, pp. 375-380.
  121. Laura M. Sangalli*, Piercesare Secchi, Simone Vantini and Valeria Vitelli (2009),
    K-mean clustering of misaligned functional data,
    Actes des XVIèmes Rencontres de la Société Francophone de Classification.
  122. E. Ammirati, N. Cristell, V. Vecchio, A. Palini, A.M. Paganoni, L.M. Sangalli, A. Monello, D. Piratino, C.V. Cannistraci, A. Durante, A.C. Vermi, M. Banfi, M. De Metrio, G.C. Marenzi, P. Secchi, A.A. Manfredi, D. Hu, N. Uren, D. Cianflone, A. Maseri (2008),
    Pattern differenziale cito/chemochinico nei pazienti con STEMI associato ad elevati livelli di IL-6 circolante riconosciuto mediante analisi simultanea di 18 cito/chemochine con Flex-set CBA,
    Giornale Italiano di Cardiologia, 9, Suppl. 1-12, p. 22.
  123. Laura M. Sangalli, Piercesare Secchi and Simone Vantini (2008),
    A case study in functional data analysis; investigating the geometry of the internal carotid artery for cerebral aneurysms classification,
    Proceedings of the XLIV Scientific Meeting of the Italian Statistical Society, pp. 181-188.
  124. Laura M. Sangalli* and Simone Vantini (2008),
    Free knot regression splines for 3-dimensional functional data, with applications to the analysis of Inner Carotid Artery centerlines,
    Proceedings of the XLIV Scientific Meeting of the Italian Statistical Society.
  125. Laura M. Sangalli and Simone Vantini (2008),
    Registration of Functional Data: Aligning Inner Carotid Artery Centerlines,
    Proceedings of the XLIV Scientific Meeting of the Italian Statistical Society.
  126. S. Bacigaluppi, L. Antiga, T. Passerini, M. Piccinelli, S. Vantini, L. Sangalli, A. Remuzzi, P. Secchi, M. Collice, E. Boccardi and A. Veneziani (2008),
    Geometric analysis of the Internal Carotid Artery (ICA) in relation to aneurysms,
    Proceedings of the 59th Annual Meeting of the German Society of Neurosurgery (DGNC) – 3rd Joint Meeting with the Italian Neurosurgical Society (SINch).
    GMS German Medical Science e-journal, German Medical Science GMS Publishing House, Düsseldorf.
  127. Laura M. Sangalli, Piercesare Secchi and Simone Vantini (2007),
    Functional data analysis for 3D-geometries of the Inner Carotid Artery,
    Book of Short Papers of S.Co.2007 conference, pp. 427-432.

    PhD dissertation 

  128. Laura M. Sangalli (2006),
    Random probability measures and their applications to Bayesian Statistics,
    PhD thesis, Dipartimento di Matematica, Università degli Studi di Pavia.
  129. Laura M. Sangalli (2007),
    Alcune misure di probabilità aleatorie e loro applicazioni in statistica bayesiana,
    Bollettino Unione Matematica Italiana, A, Vol. 10, No. 2, pp. 339-342.

    Editing 

  130. Proceedings of S.Co. 2009 Sixth Conference on Complex Data Modeling and Computationally Intensive Statistical Methods for Estimation and Prediction.
    Edited by A.M. Paganoni, L.M. Sangalli, P. Secchi, S. Vantini; Maggioli Editore.

    Software

  131. Arnone, E., Clemente, A., Sangalli, L.M., Lila, E., Ramsay, J., and Formaggia, L. (2023),
    fdaPDE: Physics-Informed Spatial and Functional Data Analysis, R package available from CRAN
    https://cran.r-project.org/package=fdaPDE
  132. Clemente, A., Palummo, A., Arnone, E., Formaggia, L., Sangalli, L.M. (2023),
    femR: Bridging Physics and statistics in R
    Supported by R Consortium: Discover femR!
    https://github.com/fdaPDE/femR
  133. Sangalli, L.M., Secchi, P., Stamm, A., Vantini, S., Vitelli, V., Zito, A. (2022),
    fdacluster: Joint Clustering and Alignment of Functional Data, R package available from CRAN,
    https://CRAN.R-project.org/package=fdacluster
  134. Parodi#, A., Morelli, M., Sangalli, L.M., Secchi, P., Vantini, S. (2023),
    FunChIP: Clustering and Alignment of ChIP-Seq peaks based on their shapes, R package available from Bioconductor,
    https://bioconductor.org/packages/FunChIP