CEREMADE
Bacry Emmanuel
Directeur de recherche CNRS
Biographie
Emmanuel Bacry est diplômé de l’ENS (Ulm) et docteur en Mathématiques. Il est actuellement Directeur de Recherche au CNRS à l’Université Paris-Dauphine, Directeur scientifique du Health Data Hub. Il a dirigé l’Initiative Big Data & Data Science à l'Ecole Polytechnique pendant plus de 4 ans (2016-2019). A cette occasion il a créé la plus grande école d’été française sur l’IA (avec plus de 500 participants) sur le campus de l’Ecole Polytechnique.
Sa recherche a toujours été guidée par un souci constant des applications, notamment en finance statistique, en santé et plus récemment en développement durable.
Il a dirigé de 2015 à 2020 un partenariat entre l’Ecole Polytechnique et la CNAM consistant à développer des méthodologies « Big Data » sur la base SNIIRAM (une des plus importantes bases de données médico-administrative au monde). Expert en IA, Emmanuel Bacry est membre de plusieurs conseils ou comités scientifiques.
Publications
Articles
Wu P., Muzy J-F., Bacry E. (2022), From rough to multifractal volatility: The log S-fBM model, Physica A: Statistical Mechanics and its Applications, vol. 604 
Bacry E., Gaiffas S., Leroy F., Morel M., Nguyen D., Sebiat Y., Sun D. (2020), SCALPEL3 : a scalable open-source library for healthcare claims databases, International Journal of Medical Informatics, vol. 141
Kabeshova A., Yu Y., Lukacs B., Bacry E., Gaïffas S. (2020), ZiMM : a deep learning model for long term adverse events with non-clinical claims data, Journal of biomedical informatics, vol. 110
Morel M., Bacry E., Gaiffas S., Guilloux A., Leroy F. (2019), ConvSCCS: convolutional self-controlled case-seris model for lagged adverser event detection, Biostatistics
Luquiens A., Dugravot A., Panjot H., Benyamina A., Gaiffas S., Bacry E. (2019), Self-exclusion in online poker gamblers: effect on time and money as compared to matched controls, International Journal of Environmental Research and Public Health, vol. 16, n°22
Rambaldi M., Bacry E., Muzy J-F. (2019), Disentangling and quantifying market participant volatility contributions, Quantitative Finance, vol. 19, n°10, p. 1613-1625
Bacry E., Bompaire M., Deegan P., Gaiffas S., Poulsen S. (2018), tick: a Python library for statistical learning, with a particular emphasis on time-dependent modeling, Journal of Machine Learning Research, vol. 18, n°214, p. 1-5
Rambaldi M., Bacry E., Lillo F. (2017), The role of volume in order book dynamics: a multivariate Hawkes process analysis, Quantitative Finance, vol. 17, n°7, p. 999-1020
Achab M., Gaiffas S., Bacry E., Mastromatteo I., Muzy J-F. (2017), Uncovering Causality from Multivariate Hawkes Integrated Cumulants, Journal of Machine Learning Research, vol. 18, n°1, p. 6998-7025
Achab M., Bacry E., Muzy J., Rambaldi M. (2017), Analysis of order book flows using a non-parametric estimation of the branching ratio matrix, Quantitative Finance, vol. 18, n°2, p. 199-212
Bacry E., Muzy J-F. (2016), First- and Second-Order Statistics Characterization of Hawkes Processes and Non-Parametric Estimation, IEEE Transactions on Information Theory, vol. 62, n°4, p. 2184-2202
Bacry E., Gaïffas S., Mastromatteo I., Muzy J-F. (2016), Mean-field inference of Hawkes point processes, Journal of Physics A: General Physics, vol. 49, n°17
Bacry E., Jaisson T., Muzy J. (2016), Estimation of slowly decreasing Hawkes kernels: application to high-frequency order book dynamics, Quantitative Finance, vol. 16, n°8, p. 1179-1201
Mastromatteo I., Bacry E., Muzy J-F. (2015), Linear processes in high dimensions: Phase space and critical properties, Physical Review. E, Statistical, Nonlinear, Biological and Soft Matter Physics, vol. 91, n°4
Bruna J., Mallat S., Bacry E., Muzy J-F. (2015), Intermittent process analysis with scattering moments, Annals of Statistics, vol. 43, n°1, p. 323-351
Bacry E., Delattre S., Muzy J-F., Hoffmann M. (2013), Some limit theorems for Hawkes processes and application to financial statistics, Stochastic Processes and their Applications, vol. 123, n°7, p. 2475–2499
Muzy J-F., Bacry E., Delattre S., Hoffmann M. (2013), Modelling microstructure noise with mutually exciting point processes, Quantitative Finance, vol. 13, n°1, p. 65-77
Communications sans actes
de Barros Soares D., Andrieux F., Hell B., Lenhardt J., Badosa J., Gavoille S., Bacry E. (2021), Predicting the Solar Potential of Rooftops using Image Segmentation and Structured Data, NIPS 2021, virtuel
Prépublications / Cahiers de recherche
Merad I., Yu Y., Bacry E., Gaïffas S. (2021), About contrastive unsupervised representation learning for classification and its convergence, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 17 p.
Morel M., Bouyer B., Guilloux A., LAANANI M., Leroy F., Nguyen D., Sebiat Y., Bacry E., Gaïffas S. (2021), Screening anxiolytics, hypnotics, antidepressants and neuroleptics for bone fracture risk among elderly: a nation-wide dynamic multivariate self-control study using the SNDS claims database, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 75 p.