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:

• PINN-based models for the forward numerical solution of ODEs and PDEs
• solution of ill-posed inverse problems by PINN-based parameter identification
• use of PINN as encoders and decoders for reduced order models
• PINN-based surrogate models of statistical variables in stochastic simulations
• encoding by PINN of matricial operators and their use in numerical linear algebra applications
• Deep Neural Networks and Machine Learning for PDEs
• Advances in Deep Neural Networks

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

• Luca Bergamaschi (luca.bergamaschi@unipd.it) University of Padova
  
• Andrea Franceschini (andrea.franceschini@unipd.it) University of Padova
  
• Caterina Millevoi (caterina.millevoi@phd.unipd.it) University of Padova
  

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

The program is available here. PDF version for download here.
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 - SLIDES
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 - SLIDES
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 - KTH, Stockholm
    Physics-Informed Neural Networks for Power Systems Applications - SLIDES
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 - SLIDES
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 - SLIDES
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 - SLIDES
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 - SLIDES
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 - SLIDES
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 - SLIDES
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 - SLIDES
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 - SLIDES
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 - SLIDES
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 - SLIDES
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 - SLIDES
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.

Photos

Some photos taken during the event are available here.