I am an Assistant Professor (Maître de Conférences) at the Department of Mathematics of Université Paris-Saclay. Before that, I was a postdoctoral researcher at EPFL in BAN chair. I did my PhD at Inria Paris under the supervision of Laurent Massoulié and Marc Lelarge. Here is a short CV.
I am currently working on:
- Statistical inference in graphs and matrices
- Informational and computational thresholds for algorithms on random instances
- Optimal transport for statistical learning
- Bayesian networks, causality and fairness
Email adress: luca [dot] ganassali [at] universite-paris-saclay [dot] fr
Physical adress: Bâtiment 307, rue Michel Magat, Faculté des Sciences d’Orsay, Université Paris-Saclay, 91400 Orsay
- May 2024: Our recent paper On sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery with Fateme Jamshidi and Negar Kiyavash has been accepted at ICML24! You can check our paper here.
- April 2024: I gave an introductionary talk at IHES about Unsupervised Alignment of Graphs and Embeddings: Fundamental Limits and Computational Methods. The video is online!
F. Jamshidi, L. Ganassali, N. Kiyavash. On sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery, 2023, ICML 2024.
[arXiv]
S. Akbari, L. Ganassali, N. Kiyavash. Learning causal graphs via monotone triangular transport maps, 2023, NeurIPS 2023 Workshop on Optimal Transport and Machine Learning
[arXiv]
L. Ganassali, L. Massoulié, G. Semerjian. Statistical limits of correlation detection in trees, 2022, Annals of Applied Probability.
[arXiv]
L. Ganassali. The graph alignment problem: fundamental limits and efficient algorithms, PhD dissertation, 2022.
[pdf] [arXiv]
L. Ganassali, M. Lelarge, L. Massoulié. Correlation detection in trees for partial graph alignment, 2021, Annals of Applied Probability (short version: ITCS 2022).
[arXiv] [ITCS (extended abstract)]
L. Ganassali, M. Lelarge, L. Massoulié. Impossibility of Partial Recovery in the Graph Alignment Problem, 2021, COLT 2021.
[arXiv] [PMLR] [COLT presentation]
L. Ganassali. Sharp threshold for alignment of graph databases with Gaussian weights, 2020, Mathematical and Scientific Machine Learning (MSML21).
[arXiv] [PMLR] [MSML presentation]
M. Akian, L. Ganassali, S. Gaubert, L. Massoulié. Probabilistic and mean-field model of COVID-19 epidemics with user mobility and contact tracing, 2020, preprint.
[arXiv]
L. Ganassali, L. Massoulié. From tree matching to sparse graph alignment, 2020, COLT 2020.
[arXiv] [PMLR] [COLT presentation]
L. Ganassali, M. Lelarge, L. Massoulié. Spectral alignment of correlated Gaussian random matrices, 2019, Advances in Applied Probability.
[arXiv] [journal]