Università degli Studi di Padova Department of Civil, Environmental And Architectural Engineering INDAM GNCS

GNCS - Gruppo Nazionale per il Calcolo Scientifico

PINN-PAD: Physics Informed Neural Networks in PADova

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The scope of the workshop includes, but is not limited to, the following topics: The meeting will consist of presentations from a number of leading researchers in neural network for Optimization and PDEs, aiming to encourage an exchange of ideas to further advance the state-of-the-art in these fields.

Scientific - Organizing Committee

Official email

For any information/questions, please use the official email address: pinn-pad@dicea.unipd.it.

Dates and location

The workshop will take place 22--23 February 2024.
Location is: Aula Nievo/Aula E of Palazzo Bo, via VIII Febbraio, 2, 35122 Padova

Call for Contributions

Contributions for a talk (20 mins + 5 mins question) (by sending an e-mail to the organizers pinn-pad@dicea.unipd.it).
Deadline for sending title and abstract of a contribution was January 20, 2024.

Registration

Registration for the event is free of charge but mandatory, and must be done by sending an e-mail to: pinn-pad@dicea.unipd.it. You will receive a confirmation email.
Deadline for registration was February 01, 2024.

Program and flyer

Preliminary program available here. PDF version for download here.
The program is updated as frequently as possible, also considering the number of contributions that are submitted.
The flyer of the event is available here.

Invited speakers and participants

List of invited speakers ([I]), speakers ([S]) and participants ([A]):
  1. [A] Ambrosi Filippo - University of Padova
  2. [A] Andrean Daniele - Department of Information Engineering, University of Padova
  3. [I] Antonietti Paola - MOX, Politecnico di Milano
    Machine Learning-enhanced Polytopal Finite Element Methods
  4. [A] Aslan İsmail - Department of Mathematics, University of Padova
  5. [A] Bachini Elena - Department of Mathematics, University of Padova
  6. [A] Bandiziol Cinzia - University of Padova
  7. [A] Barberi Gianmarco - CAPE-Lab, Department of Industrial Engineering, University of Padova
  8. [A] Barbierato Marco - University of Padova
  9. [A] Basei Riccardo - Department of Industrial Engineering, University of Padova
  10. [A] Beccaro Luca - CAPE-Lab, Department of Industrial Engineering, University of Padova
  11. [S] Bioli Ivan - Computational Science and Engineering - École Polytechnique Fédérale de Lausanne (EPFL)
    Multi-Fidelity Neural Network Surrogate Modeling for Large-Scale Bayesian Inverse Problems
  12. [S] Boiger Romana - Paul Scherrer Institute: Laboratory for Waste Management
    Solving the Bateman Equation using Physics Informed Neural Networks
  13. [A] Boscolo Baicolo Lorenzo - University of Padova
  14. [A] Bozzo Enrico - Dipartimento di Scienze Matematiche, Informatiche e Fisiche, Università di Udine
  15. [I] Bragone Federica - ETH, Stockholm
    Physics-Informed Neural Networks for Power Systems Applications
  16. [A] Breda Dimitri - CDLab - Computational Dynamics Laboratory, Department of Mathematics, Computer Science and Physics - University of Udine
  17. [A] Brunasso Alessandro - Department of Information Engineering, University of Padova
  18. [A] Burhan Muhammad - Northwestern Polytechnic University
  19. [A] Cardin Franco - Department of Mathematics, University of Padova
  20. [A] Carraro Marco - Department of Industrial Engineering, University of Padova
  21. [A] Casanova Miguel - University of Padova
  22. [A] Centofanti Edoardo - Department of Mathematics, University of Pavia
  23. [S] Chinellato Erik - Department of Mathematics, University of Padova
    Physics-Aware Deep Nonnegative Matrix Factorization
  24. [A] Cogo Michele - Centro di Ateneo di Studi e Attività Spaziali "Giuseppe Colombo" - CISAS, University of Padova
  25. [A] Conte Filippo - Department of Industrial Engineering, University of Padova
  26. [A] Coscia Dario - SISSA, Trieste
  27. [A] Crispino Andrea - Politecnico di Milano
  28. [A] Cristiu Daniel - CAPE-Lab, Department of Industrial Engineering, University of Padova
  29. [I] Cuomo Salvatore - Università di Napoli
    Computational Paradigms in Scientific Machine Learning
  30. [S] D'Inverno Giuseppe Alessio - SISSA, Trieste
    Physics Informed Graph Neural Networks for AC Optimal Power Flow
  31. [A] Davanzo Mauro - Department of Industrial Engineering, University of Padova
  32. [A] De Marchi Stefano - Department of Mathematics, University of Padova
  33. [A] Dell'Orto Marco - University of Padova
  34. [I] Della Santa Francesco - Department of Mathematical Sciences, Politecnico di Torino
    Graph-informed neural network and discontinuity learning
  35. [S] Difonzo Fabio V. - Istituto per le Applicazioni del Calcolo “Mauro Picone” Consiglio Nazionale delle Ricerche
    Physics Informed Neural Networks for an Inverse Problem in Peridynamic Models
  36. [A] Facco Pierantonio - CAPE-Lab, Department of Industrial Engineering, University of Padova
  37. [A] Faggionato Edoardo - Department of Information Engineering, University of Padova
  38. [A] Faggionato Samuele - University of Padova
  39. [A] Fanan Mattia - Department of Information Engineering, University of Padova
  40. [A] Fanton Lorenzo - Università Ca' Foscari Venezia
  41. [A] Ferronato Massimiliano - Department of Civil, Environmental and Architectural Engineering, University of Padova
  42. [A] Florido Jose - University of Leeds
  43. [S] Forootani Ali - Max Planck Institute for Dynamic of Complex Technical Systems
    Application of Physics-Informed Neural Networks in Nonlinear Systems Identification and Parameter Estimation
  44. [A] Francomano Elisa - University of Palermo
  45. [A] Gallina Antonio - Department of Information Engineering, University of Padova
  46. [A] Galvanetto Ugo - Department of Industrial Engineering, University of Padova
  47. [A] Geremia Margherita - CAPE-Lab, Department of Industrial Engineering, University of Padova
  48. [A] Ghahramanibozandan Mohammadmahdi - University of Padova
  49. [A] Giampiccolo Stefano - DISI, Department, University of Trento
  50. [A] Girardi Lorenzo - CAPE-Lab, Department of Industrial Engineering, University of Padova
  51. [A] Grigoletto Tommaso - University of Padova
  52. [A] Güçlü Yaman - Max Planck Institute for Plasma Physics
  53. [A] Guidolin Mattia - C-Square Lab, Dept of Management and Engineering, University of Padova
  54. [S] Gupta Karan - Center of Studies and Activities for Space "G. Colombo" CISAS - University of Padova
    Enhancing Biomechanical Impact Simulations through Physics-Informed Neural Networks
  55. [A] Hajaltoom Lubna Eltayeb Kamaleldeen - Department of Industrial Engineering, University of Padova
  56. [S] Henriquez Fernando José Barraza - École Polytechnique Fédérale de Lausanne
    Wavenumber-Robust Deep ReLU Neural Network Emulation in Acoustic Wave Scattering
  57. [S] Hoefler Matthias - Department of Mathematics and Scientific Computing, University of Graz
    Parameter estimation in cardiac biomechanical models based on physics-informed neural networks
  58. [A] Hu Liwei - Department of Mathematics, University of Bologna
  59. [A] Janna Carlo - Department of Civil, Environmental and Architectural Engineering, University of Padova
  60. [S] Jnini Anas - Industrial Innovation, University of Trento
    Gauss-Newton Natural Gradient for Physics-Informed Computational Fluid Dynamics
  61. [A] Kabuya Désiré - University of L'Aquila
  62. [A] Karimnejad Esfahani Mohammad - Department of Mathematics, University of Padova
  63. [A] Kong Xiang'en - Center of Studies and Activities for Space "G. Colombo" CISAS - University of Padova
  64. [A] Larese De Tetto Antonia - Department of Mathematics, University of Padova
  65. [A] Lopez Luciano - Department of Mathematics, Università degli Studi di Bari Aldo Moro
  66. [S] Lovison Alberto - Department of Mathematics, University of Padova
    Brain memory working. Optimal control behavior for improved Hopfield-like models
  67. [A] Lucchini Francesco - Department of Industrial Engineering, University of Padova
  68. [S] Marchetti Francesco - Department of Mathematics, University of Padova
    Predicting coronal mass ejections' travel times by using physics-informed loss functions
  69. [A] Marchiori Hadija - University of Padova
  70. [A] Marconato Nicolò - Department of Industrial Engineering, University of Padova
  71. [A] Marcuzzi Fabio - Department of Mathematics, University of Padova
  72. [A] Maritan Alessio - Department of Information Engineering, University of Padova
  73. [A] Martínez Calomardo Ángeles - Department of Mathematics, Informatics and Geosciences - University of Trieste
  74. [A] Mohib Hussain - Department of Mathematics, Govt. College University, Faisalabad, Pakistan
  75. [A] Moro Federico - Department of Industrial Engineering, University of Padova
  76. [A] Narduzzi Claudio - Department of Information Engineering, University of Padova
  77. [S] Onwunta Akwum - Department of Industrial and systems Engineering, Lehigh University
    A deep neural network approach for parameterized PDEs and Bayesian inverse problems
  78. [A] Parodi Davide - Department of Mathematics, University of Genova
  79. [A] Pase Francesco - Lead AI Research Engineer - NEWTWEN
  80. [A] Pedersen Morten Gram - Department of Information Engineering, University of Padova
  81. [A] Pellegrini Luca - University of Pavia
  82. [A] Pellizzari Elisa - Department of Information Engineering, University of Padova
  83. [A] Perin Giovanni - Department of Information Engineering, University of Padova
  84. [A] Petrella Alessandro - University of Bologna
  85. [A] Poggiana Giulio - Department of Industrial Engineering, University of Padova, ElectraLab
  86. [A] Prendin Francesco - Department of Information Engineering, University of Padova
  87. [A] Putti Mario - Department of Agronomy, Food Natural resources, Animals and Environment, University of Padova
  88. [A] Rama Martina - University of Trento
  89. [A] Rinaldi Laura - Department of Mathematics, University of Padova
  90. [I] Rozza Gianluigi - SISSA, Trieste
    Accelerating Numerical Simulations by Model Reduction with Scientific and Physics-Informed Machine Learning
  91. [A] Saccardo Alberto - CAPE-Lab, Department of Industrial Engineering, University of Padova
  92. [S] Saleh Yahya - Department of Mathematics - Universität Hamburg
    Spectral learning for solving molecular Schrödinger equations
  93. [A] Santin Gabriele - Department of Environmental Sciences, Informatics and Statistics - Ca' Foscari University of Venice
  94. [A] Scarpa Mattia - Lead AI Research Engineer - NEWTWEN
  95. [A] Schiano Di Cola Vincenzo - Università degli Studi di Napoli Federico II
  96. [A] Schiavon Samuele - University of Padova
  97. [I] Schwarz Anna - University of Stuttgart
    Recent advances and failures in the machine-learning enhanced solution of PDEs
  98. [A] Scialpi Matteo - Department of Physics and Earth Science, University of Ferrara
  99. [A] Tamiazzo Edoardo - CAPE-Lab, Department of Industrial Engineering, University of Padova
  100. [S] Tanveer Muhammad - Department Mathematics - University of Udine
    A Neural Network Approach to Learn Delay Differential Equations via Pseudospectral Collocation
  101. [A] Tonicello Niccolò - SISSA, Trieste
  102. [A] Torchio Riccardo - Department of Industrial Engineering, University of Padova
  103. [A] Vargiolu Tiziano - Department of Mathematics, University of Padova
  104. [A] Wajid Ahmed - Northwestern Polytechincal University, Xi'an, China
  105. [A] Yousefi Mahsa - Morgagni Learning Center, University of Firenze
  106. [A] Zaccariotto Mirco - Dep. of Industrial Engineering & CISAS "G. Colombo", University of Padova
  107. [A] Zavattari Carlo - Industrial Innovation, University of Trento
  108. [A] Zorzetto Matteo - Department of Industrial Engineering, University of Padova

Book of abstract

The collection of the abstracts from the invited speakers is available here.
The collection of the abstracts from the contributed speakers is available here.
Page accessed times (starting from September 30, 2023)