About Denis Rustand Denis Rustand Postdoctoral Research Fellow (former), Statistics Survival analysis Bayesian computational statistics Denis Rustand is a Post-Doctoral fellow In Statistics at the King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Håvard Rue in his research group. Education and Early Career MSc (Statistics), University of Southern Brittany, 2017 PhD (Biostatistics), University of Bordeaux, 2020 Research interests Bayesian computational statistics, survival analysis, applications of statistics to medical research, INLA. Awards Doctor Norbert Marx Award, 2021 Summer school grant, Univerity of Toronto, 2018 Académie Française, Jean Walter Zellidja grant, 2018 EHESP Articles Related News May 2026 INLA Team Publishes New Book on Joint Survival and Longitudinal Modelling 1 min read · Tue, May 5 2026 News INLA Longitudinal Models Survival analysis We are thrilled to announce the publication of our latest book, a comprehensive guide to fitting complex Bayesian survival, longitudinal, and joint models using the Integrated Nested Laplace Approximations (INLA) methodology. This highly anticipated release represents a major milestone for our team, offering a powerful, computationally efficient alternative to traditional MCMC methods for researchers around the globe. October 2023 Real-time modeling a step closer to reality 2 min read · Thu, Oct 26 2023 News An efficiency upgrade for an already fast approximation method enables accurate near-real-time modeling of complex systems and large datasets. February 2023 Two-part joint models using INLA published in the Biometrical Journal 1 min read · Mon, Feb 27 2023 News Two-part joint models for a longitudinal semicontinuous biomarker and a terminal event have been recently introduced based on frequentist estimation. The biomarker distribution is decomposed into a probability of positive value and the expected value among positive values. Shared random effects can represent the association structure between the biomarker and the terminal event. The computational burden increases compared to standard joint models with a single regression model for the biomarker. In this context, the frequentist estimation implemented in the R package frailtypack can be January 2023 INLAjoint at SFB-JJC in Rennes 1 min read · Tue, Jan 31 2023 News Dr. Denis Rustand presented a talk on using INLA and INLAjoint for research in biometrics at the SFB-JJC: Young Researchers Day in Biometrics of the French Society of Biometrics, on 19 January 2023 in Rennes. June 2022 INLA course at Bordeaux population health center 1 min read · Wed, Jun 15 2022 News Some members of the INLA team presented an INLA short course to the Biostatistics group at the Bordeaux population health center of INSERM and the University of Bordeaux. The content was tailored for biostatistics and public health applications, to avail INLA as a tool for fast Bayesian inference of applicable statistical models.
INLA Team Publishes New Book on Joint Survival and Longitudinal Modelling 1 min read · Tue, May 5 2026 News INLA Longitudinal Models Survival analysis We are thrilled to announce the publication of our latest book, a comprehensive guide to fitting complex Bayesian survival, longitudinal, and joint models using the Integrated Nested Laplace Approximations (INLA) methodology. This highly anticipated release represents a major milestone for our team, offering a powerful, computationally efficient alternative to traditional MCMC methods for researchers around the globe.
Real-time modeling a step closer to reality 2 min read · Thu, Oct 26 2023 News An efficiency upgrade for an already fast approximation method enables accurate near-real-time modeling of complex systems and large datasets.
Two-part joint models using INLA published in the Biometrical Journal 1 min read · Mon, Feb 27 2023 News Two-part joint models for a longitudinal semicontinuous biomarker and a terminal event have been recently introduced based on frequentist estimation. The biomarker distribution is decomposed into a probability of positive value and the expected value among positive values. Shared random effects can represent the association structure between the biomarker and the terminal event. The computational burden increases compared to standard joint models with a single regression model for the biomarker. In this context, the frequentist estimation implemented in the R package frailtypack can be
INLAjoint at SFB-JJC in Rennes 1 min read · Tue, Jan 31 2023 News Dr. Denis Rustand presented a talk on using INLA and INLAjoint for research in biometrics at the SFB-JJC: Young Researchers Day in Biometrics of the French Society of Biometrics, on 19 January 2023 in Rennes.
INLA course at Bordeaux population health center 1 min read · Wed, Jun 15 2022 News Some members of the INLA team presented an INLA short course to the Biostatistics group at the Bordeaux population health center of INSERM and the University of Bordeaux. The content was tailored for biostatistics and public health applications, to avail INLA as a tool for fast Bayesian inference of applicable statistical models.
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