Bacry Emmanuel - CV

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., Rambaldi M., Muzy J-F., Bacry E. (2023), A single queue reactive Hawkes model for the order flow, Market Microstructure and Liquidity

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

Delaune A., Valmary-Degano S., Loménie N., Zryouil K., Benyahia N., Trassard O., Eraville V., Bergeron C., Devouassoux-Shisheboran M., Glaser C., Bataillon G., Bacry E., Combes S., Prevot S., Bertheau P. (2022), Le premier data challenge organisé par la Société Française de Pathologie : une compétition internationale en 2020, un outil de recherche en intelligence artificielle pour l’avenir ?, Annales de Pathologie, vol. 42, n°2, p. 119-128

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

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

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

Luquiens A., Vendryes D., Aubin H-J., Benyamina A., Gaiffas S., Bacry E. (2018), Description and assessment of trustability of motives for self-exclusion reported by online poker gamblers in a cohort using account-based gambling data, BMJ Open, vol. 8, n°12, p. e022541

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

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

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

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

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

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

Communications avec actes

Ruan R., Bacry E., Muzy J-F. (2023), Liquidity takers behavior representation through a contrastive learning approach, in , New York, NY, ACM - Association for Computing Machinery

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

SUSMANN H., Chambaz A., Josse J., Wargon M., Aegerter P., Bacry E. (2024), Probabilistic Prediction of Arrivals and Hospitalizations in Emergency Departments in Île-de-France, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 27 p.

Ruan R., Bacry E., Muzy J-F. (2023), The self-exciting nature of the bid-ask spread dynamics, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 31 p.

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.

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