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Emmanuel Bacry is a graduate of ENS (Ulm) and holds a doctorate in Mathematics. He is currently CNRS Research Director at Paris-Dauphine University, Scientific Director of the Health Data Hub. He led the Big Data & Data Science Initiative at Ecole Polytechnique for more than 4 years (2016-2019). On this occasion, he created the largest French summer school on AI (with more than 500 participants) on the campus of the Ecole Polytechnique.
His research has always been guided by a constant concern for applications, particularly in statistical finance, health and more recently in sustainable development.
From 2015 to 2020, he led a partnership between the Ecole Polytechnique and the CNAM consisting in developing “Big Data” methodologies on the SNIIRAM database (one of the largest medico-administrative databases in the world). Expert in AI, Emmanuel Bacry is a member of several scientific councils or committees.
Wu P., Rambaldi M., Muzy J-F., Bacry E. (2023), A single queue reactive Hawkes model for the order flow, Market Microstructure and Liquidity 
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
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
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
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
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
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., 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
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
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
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
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
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
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
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.
