Eric Moulines

Eric Moulines is a Professor at EPITA, MBUZAI University and member of the French Science Academy. He has made major contributions to several fields, among which the inference of partially observed Markovian models, MCMC methods and more generally probabilistic methods for Machine Learning.

Aymeric Dieuleveut

Aymeric is a Professor at the Ecole polytechnique. He has a PhD in Mathematics from the Ecole Normale Supérieure, Paris, under the supervision of Francis Bach. From 2017 to 2019, he was a postdoctoral fellow of Pr. M. Jaggi at EPFL. His main research interests are optimization and statistics, in particular for federatd learning.

El Mahdi El Mhamdi

Alain Durmus

Alain is professor at Polytechnique and a member of the CMAP. His research interests are in the field of computational statistics and machine learning. He is particularly interested in the development of Monte Carlo and stochastic methods for Bayesian inference and generative models, as well as stochastic approximation schemes for the solution of optimization or fixed-point problems.

Vianney Perchet

Etienne Boursier

Etienne is a researcher in the CELESTE team of INRIA Paris-Saclay. Before that, he was a postdoc at EPFL with Nicolas Flammarion and completed a PhD at ENS Paris-Saclay under the supervision of Vianney Perchet. He is working on different aspects of the theory of machine learning, including decentralised (online) learning, meta-learning and the theoretical understanding of neural networks.

Antoine Scheid

Aymeric Capitaine

Aymeric is PhD student under the supervision of Michael I. Jordan, Alain Durmus, Etienne Boursier and Mahdi El Mhamdi. Before that, we was a student at Ecole Normale Supérieure PSL in Economics and Statistics. His interests cover information asymmetry in collaborative and federated learning models as well as statistical mechanism design.

Samson Gourevitch

Navid Bagheri Shouraki

navid is a PhD student at EPITA supervised by Eric Moulines and Alain Durmus. His research focuses on generative models, including diffusion-based methods for image restoration and efficient sampling techniques

Anton Conrad

Michael I. Jordan

Lydia Zakynthinou

Lydia is a Postdoctoral Researcher at the department of Electrical Engineering and Computer Sciences at UC Berkeley, hosted by Michael Jordan, and a FODSI-Simons postdoctoral research fellow. She completed her PhD at the Khoury College of Computer Sciences at Northeastern University. Her scientific interests cover differential privacy and PAC guarantees for collaborative models.

Paula Gradu

Nivasini Ananthakrishnan

Nivasini is a year PhD student at UC Berkeley advised by Nika Haghtalab and Michael I. Jordan. Her research centers around learning and decision-making in environments with complexities such strategic behavior and information asymmetry.

Xinyan Hu

Mariel Werner

Mariel is a PhD student ac UC Berkeley under the supervision of Pr. M. I. Jordan. She obtained a B.S. in applied Mathematics from Harvard, and is mostly interested in robustness and personalization in federated learning.

Francisca Vasconcelos

Gareth Roberts

G. Roberts is currently a Professor at Warwick University, and leader of the CoSInES project. He is a leading figure in the theory of MCMC methods, and has made ground-breaking theoretical and methodological contributions to the field of stochastic simulation with his research team.

Murray Pollock

Murray is a Senior Lecturer at Newcastle University. He holds a Ph.D. in Statistics, graduating in 2014 in the Department of Statistics at the University of Warwick, under the supervision of Pr. Adam M. Johansen and Pr. Gareth O. Roberts FRS. He is a close collaborator of Pr. Roberts, with research interests in computational statistics, Monte Carlo methodology and perfect simulation.

Louis Aslett

Louis is Associate Professor in the Department of Mathematical Sciences at Durham University. He received his PhD in 2013 from Trinity College Dublin, Ireland. His work is on the statistics side, developing methodology for end-to-end fitting and prediction of machine learning models fully encrypted, accommodating the constraints of existing fully homomorphic encryption (FHE) schemes.

Adam Johansen

Adam is a Professor of Statistics at Warwick. He received his PhD in 2007 from The University of Cambridge and from 2006-2008 he was a research fellow at The University of Bristol. In 2008 he joined the University of Warwick as Assistant Professor, where his research interests have mainly centered around computational statistics.

Shenggang Hu

Shenggang joined the department of Statistics at Warwick in 2024. His research interest are exact sampling, differential privacy and Bayesan inference.

Hongsheng Dai

Hongsheng is a professor of Statistics in Newcastle University. He received his PhD in Statistics at University of Oxford in 2008. He is an expert in Bayesian computational statistics and has also made contributions in statistical methodology development in biostatistics, including the areas of survival analysis and longitudinal analysis.

Hugo Queniat

Hugo is a PhD student in the Statistics working under the joint supervision of Prof. Gareth Roberts and Dr Nick Tawn. His research interests lie in the area of Monte Carlo methods and probabilistic machine learning. Currently, he is working on tempering techniques to sample from multimodal target distributions.

Filippo Pagani

He is a Postdoctoral Research Fellow on the OCEAN grant under the supervision of Professors Gareth Roberts and Adam Johansen. His research interests include Markov Chain Monte Carlo, Variational Inference, Tempering, Irreversibility, Piecewise Deterministic Markov Processes, Mixture Models, Variable Selection and Interaction Discovery, Bayesian Statistics, Machine Learning, and Inverse Problems.

Federico Perlino

He is a second-year PhD student in Statistics at the Warwick Centre for Doctoral Training. His background spans social sciences, machine learning, and statistics. His main interests lie at the intersection of computational statistics and probabilistic machine learning, with applications in behavioral and social sciences as well as in cancer epidemiology.

Christian P Robert

Christian is a Professor at both Université Paris-Dauphine PSL and Warwick University. He holds a prAIrie chair and is an ELLIS Fellow. He is considered a leader in Bayesian decision theory and computational statistics, with pioneering contributions to Approximate Bayesian Computation (ABC).

Stéphanie Allassonière

Stéphanie is a Professor of Mathematics at the University of Paris and Ecole polytechnique. She is the director of master programs and master classes in AI in healthcare and holds a prAIrie chair. Her research focuses on proposing decision support systems for diagnosis and therapy through statistical modelling of clinical data.

Julien Stoehr

Robin Ryder

Robin is an assistant professor at Paris Dauphine-PSL and a close collaborator of Pr. Robert, with expertise in Bayesian statistics, computational statistics, and models of language. He obtained his PhD in Oxford in 2010 on the latter, for which he received the Corcoran Medal. He is a prAIrie Fellow. He is currently on-leave as a lecturer at Imperial College London.

Paolo Onorati

Edoardo Bandoni

Edoardo is a first year PhD student working under the guidance of Christian Robert at Paris Dauphine-PSL. His research focuses on Bayesian inference conditional on non-sufficient statistics.