CV
Biography
Gianluca Fabiani is a PhD student in Modeling and Engineering Risk and Complexity (MERC) at Scuola Superiore Meridionale (SSM), Naples, Italy. Additionally, He have been recently a Visiting Student at the Department of Chemical and Biomolecular Engineering, Johns Hopkins University. Gianluca Fabiani holds a Bachelor’s Degree in Mathematics and a Master’s Degree in Applied Mathematics from the Department of Mathematics and Applications of the University of Naples Federico II. During his Master’s Degree, the direction of his studies has focused on the numerical analysis, machine learning, statistics and mathematical modeling of complex dynamical systems. He graduated with honours, conducting his MSc Thesis entitled “Learning Partial Differential Equations from Data with Machine Learning algorithms” under the supervision of Prof. Constantinos Siettos. His research interests have found a natural continuation within the PhD program in Modeling and Engineering Risk and Complexity (MERC) at the Shool of Advances Studies of Naples (SSM).
Current Position
Ph.D. Student in Modelling and Engineering Risk and Complexity (MERC), at Scuola SUperiore Meridionale (SSM) (expected November 2024)
- Supervisor: Professor Constantinos Siettos,
- Co-Advisor: Professor Ioannis G. Kevrekidis
- Thesis Project: Machine Learning-based Modelling and Numerical Analysis of the emergent dynamics of complex systems
- This Ph.D. program in MERC covers Mathematics, Physics, Engineering and Science, providing the possibility of attending courses and seminars from world-renown experts on a variety of topics including:
- Complex systems, infrastructures and networks.
- Data analysis and machine learning.
- Reliability theory for uncertainty modelling.
- Systems and control theory.
- Risk Analysis and Risk management.
Education
- M.S. in Applied Mathematics (LM-40), Università degli Studi di Napoli Federico II, October 2020
- Department of Mathematics and Applications Renato Caccioppoli
- Final Mark: 110/110 cum laude.
- Thesis: ``Learning Partial Differential Equations from Data with Machine Learning algorithms”
- Supervised by Professor Constantinos Siettos
- B.S. in Mathematics (LM-35), Università degli Studi di Napoli Federico II, June 2018
- Department of Mathematics and Applications Renato Caccioppoli
- Final Mark: 104/110.
- Thesis:``Quantum harmonic oscillator”
- Supervised by Prof. Luigi Rosa
- High School Scientific Diploma - PNI, Liceo scientifico Niccolò Copernico, July 2013
Visiting Experiences
- International Visiting Student at Dept. of Chemical and Biomolecular Engineering, Johns Hopkins University (JHU), Supervisor: Prof. Ioannis G. Kevrekidis
- 4 months from 03/2022 to 06/2022
- 6 months from 02/2023 to 07/2023
- 1 months in 01/2024
Research Activities
- Team member of scientific project: multiscale COMputational Based Analysis and modeling of the Transmission network for the assessment and control of the COVID-19 Pandemic in Italy
- funded by the Bando FISR 2020 COVID, MUR
- https://www.covid19uninafisr.com/; https://combatcovid19uninafisr.com/
Publications Impact
From ResearchGate (RG) and Google Scholar (GS), updated up to September 23, 2024
- Citations 204 (max between RG 204 and GS 195)
- h-index 6
- i10-index 5
- g-index 13 (Harzing’s publish or perish, about GS stats)
- Research Interest Score 229.7 (RG)
- higher than 77% of ResearchGate members.
- higher than 97% of ResearchGate members who first published in 2020
- higher than 78% of researchers with work related to Applied Mathematics
- higher than 84% of researchers with work related to Artificial Intelligence
- higher than 86% of researchers with work related to Artificial Neural Networks
- higher than 73% of researchers with work related to Computing in Mathematics, Natural Science, Engineering and Medicine
- higher than 70% of researchers with work related to Computational Physics
- higher than 83% of researchers with work related to Computing in Social science, Arts and Humanities
- higher than 73% of researchers with work related to Mathematical Physics
- Total reads 3680 (RG)
- Recommendations 69 (RG)
From Scopus (2019–2023)
- 102 Citations by 63 documents
- 9 Documents
- 4 h-index
- 17 Co-authors
- 40% International collaboration
- Documents in top citation percentiles 80% (4 documents)
- Documents in top 25% journals by CiteScore percentile 100% (5 documents)
- Field-Weighted Citation Impact 2.56 FWCI
List of peer-reviewed publications
Fabiani, G., Kevrekidis, I. G., Siettos, C., & Yannacopoulos, A. N. RandONets: Shallow-Networks with Random Projections for learning linear and nonlinear operators. J Comp Phys (2024)
Auricchio, F., Belardo, M. R., Calabrò, F., Fabiani, G. & Pascaner, A. F. (2024). On the accuracy of interpolation based on single-layer artificial neural networks. Soft Computing
Alvarez, H. V., Fabiani, G., Kevrekidis, I. G., Kazantzis, N., & Siettos, C. (2024). Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks. Chaos Solitons & Fractals 186.
Patsatzis, D. G., Fabiani, G., Russo, L., & Siettos, C. (2024). Slow invariant manifolds of singularly perturbed systems via physics-informed machine learning. SIAM Journal on Scientific Computing 46(4)
Fabiani, G., Evangelou, N., Cui, T. et al. Task-oriented machine learning surrogates for tipping points of agent-based models. Nat Commun 15, 4117 (2024). https://doi.org/10.1038/s41467-024-48024-7
Gnanadesikan, A., Fabiani, G., Liu, J., Gelderloos, R., Brett, G. J., Kevrekidis, Y., ... & Sleeman, J. (2023). Tipping points in overturning circulation mediated by ocean mixing and the configuration and magnitude of the hydrological cycle: A simple model. Journal of Physical Oceanography.
Hector Vargas Alvarez, Gianluca Fabiani, Nikolaos Kazantzis, Constantinos Siettos, Ioannis G. Kevrekidis, Discrete-time nonlinear feedback linearization via physics-informed machine learning, Journal of Computational Physics, Volume 492, 2023, 112408, ISSN 0021-9991, https://doi.org/10.1016/j.jcp.2023.112408.
Fabiani, G., Galaris, E., Russo, L., & Siettos, C. (2023). Parsimonious physics-informed random projection neural networks for initial value problems of ODEs and index-1 DAEs. Chaos: An Interdisciplinary Journal of Nonlinear Science, 33(4).
Galaris, E., Fabiani, G., Gallos, I., Kevrekidis, I., & Siettos, C. (2022). Numerical bifurcation analysis of pdes from lattice Boltzmann model simulations: a parsimonious machine learning approach. Journal of Scientific Computing, 92(2), 34.
Fabiani, G., Calabrò, F., Russo, L., & Siettos, C. (2021). Numerical solution and bifurcation analysis of nonlinear partial differential equations with extreme learning machines. Journal of Scientific Computing, 89, 1-35.
Calabrò, F., Fabiani, G., & Siettos, C. (2021). Extreme learning machine collocation for the numerical solution of elliptic PDEs with sharp gradients. Computer Methods in Applied Mechanics and Engineering, 387, 114188.
List of Preprints
Fabiani, G., Bollt, E., Siettos, C., & Yannacopoulos, A. N. (2024). Stability Analysis of Physics-Informed Neural Networks for Stiff Linear Differential Equations. arXiv preprint arXiv:2408.15393.
Fabiani, G. (2024). Random Projection Neural Networks of Best Approximation: Convergence theory and practical applications. arXiv preprint arXiv:2402.11397.
Galaris, E., Fabiani, G., Calabrò, F., di Serafino, D., & Siettos, C. (2021). Numerical Solution of Stiff ODEs with Physics-Informed RPNNs. arXiv preprint arXiv:2108.01584.
Talks in International Conferences
July 29, 2024
Talk at DDE24, Bremen, Germany
February 28, 2024
Talk at SIAM UQ24, Trieste, Italy
November 10, 2023
Talk at CCS/Italy 2023, Naples, Italy
September 08, 2023
Talk at Dynamics Days Europe 2023, Naples, Italy
June 23, 2023
Talk at Crunch Seminars, Brown, Division of Applied Mathematics
June 14, 2023
Talk at NUMTA DS23, Pizzo Calabro (VV), Italy
May 17, 2023
Talk at SIAM DS23, Portland, Oregon, USA
March 27, 2023
Talk at AAAI Spring Symposium Series, Palo Alto, California
September 26, 2022
Talk at 2022 Conference in Nonlinear Science and Complexity, Thessaloniki, Greece
Conference Organization
Local Organizing Committee:
Invited Speaker
- June 23, 2023: Parsimonious Physics-informed Random Projection Neural Networks (RPNN) for solving Forward and Inverse Problems https://bpb-us-w2.wpmucdn.com/sites.brown.edu/dist/1/376/files/2023/09/Flyer_6.23.23_Gianluca-Fabiani-Scuola-Superiore-Meridionale-SSM-Naples-Italy.pdf
Minisymposia Organization
- Dynamics Days Europe 2023 Physics-Informed Machine Learning for the solution of forward and inverse problems
Teaching (Assistant and Didactic Internship)
Peer-reviewing activity
Gianluca Fabiani has served as a reviewer for several scientific journals, covering topics related to scientific computing, dynamical systems, and multidisciplinary research. His peer review contributions include the following (total 17 reviews):
- 8 articles for Soft Computing (Elsevier)
- 4 articles for Nonlinear Dynamics (Springer)
- 2 articles for Plos One
- 1 article for International Journal of Applied and Computational Mathematics (Springer)
- 1 article for Multibody System Dynamics (Springer)
- 1 article for Transaction on machine learning research (sub-journal of Journal of Machine Learning Research)
Skills
- Mathematics and Mathematical Reasoning
- Complex Problem Solving
- Critical Thinking
- Active Learning
- Deductive and Inductive Reasoning
- Information Ordering
- Programming
- MATLAB
- Python
- TensorFlow
- Keras
- numpy
- others
- C
- Fortran
- Latex
- Microsoft Office 365
Awards
- Featured Article in Nature Communication award - Awarded May 2024 for the paper “Task-oriented machine learning surrogates for tipping points of agent-based models” in the collection “AI and Machine Learning”
- Featured Article in Nature Communication award - Awarded May 2024 for the paper “Task-oriented machine learning surrogates for tipping points of agent-based models” in the collection “Applied physics and mathematics”
- Chaos Editor’s Pick badge award - Awarded April 2023 for the paper “Parsimonious physics-informed random projection neural networks for initial value problems of ODEs and index-1 DAEs”
- SIAM Student Travel Award - Awarded May 2023 for SIAM DS23 conference
- Kovalevskaya Grant for ICM 2022 - Awarded July 2022
- Best presentation at the conference Nonlinear Science and Complexity 2022 (NSC22). Title:”Identifying the emergent dynamics of Agent Based Models: Coarse scale integro-PDEs from fine scale simulations”. In the Mynisimposium: “Multiscale Modelling and Numerical analysis of Complex and Large scale Dynamical Systems”
- Above 90th percentile of Master’s degree thesis of 2019-2020, merit ranking in Scientific School MM.FF.NN., University of Naples, Federico II
- First place, for the CAS category, Bridge Student Sports Games, XIX Camp del Bridge a Scuola, Pisciotta (Palinuro)- July 2013
Others
European Driving license B
