Invited Sessions in Probability

  • IP1 - Geometric Probability (Joseph Yukich, Lehigh)

  • IP3 - Stochastic Partial Differential Euqations  (Benjamin Gess, Bielefeld, Leipzig)

  • IP4 - Numerics and Stochastics (Evelyn Buckwar, JKU Linz)

  • IP5 - Percolation  (Vincent Tassion, ETH Zurich)

  • IP6 - Liouville Quantum Gravity and Planar Maps (Nina Holden, ETH Zurich)

  • IP7 - Random Matrices (Florence Merlevede, Universite Gustav Eiffel, Paris)

  • IP8 - Growth Processes  (Alexandre Stauffer, Roma Tre and Bath)

  • IP9 - KPZ Universality  (Daniel Remenik, Universidad de Chile)

  • IP10 - Topology of Random Objects (Takashi Owada, Purdue)

  • IP11 - Infinitely Divisible Laws and Processes (Jan Rosinski, Knoxville)

  • IP12 - Optimal Transport in Machine Learning and Artificial Intelligence
    (Marco Cuturi, CREST-ENSAE Paris)

  • IP13 - Exact Monte Carlo for Stationary Analysis (Gareth Roberts, Warwick)

  • IP14 - Financial Mathematics (Caroline Hillairet, ENSAE Paris)

  • IP15 - Insurance Mathematics (Mogens Steffensen, Copenhagen)

  • IP16 - Rough path theory, signatures and applications (Thomas Cass, Imperial College London)

  • IP17 - Stochastic models in fluid dynamics (Oana Lang, Imperial College London)

  • IP18 - Stochastics interacting systems (Daniel Valesin, University of Groningen)  

  • IP19 - Stochastic processes, extremes and risk (Clement Dombry, University of Besancon)

  • IP20 - Levy processes: recent advances in theory and applications (Aleks Mijatovic, University of Warwick) 

  • IP21 - Regularization by noise (Oleg Butkovsky, Weierstrass Institute Berlin)

  • IP22 - Reflecting diffusions, stochastic networks and applications (Cristina Costantini, University of Chieti-Pescara)

  • IP23 - Centennial of the Lindeberg central limit theorem (Adam Jakubowski, University of Torun)

  • IP24 - Quantum field theory and stochastic analysis (Hao Shen, University of Wisconsin-Madison)

  • IP25 - High-dimensional extremes and their applications (Richard A. Davis, Columbia University New York)

  • IP26 - Random walks in static and dynamic random environments (Jonathon Peterson, Purdue University)

  • IP27 - Stable random walks, capacity and fractional diffusions session in honour of Mark M. Meerschaert (John P. Nolan, American University)

  • IP28 - Vector- and Function-valued Random Fields: models, Structure and Regularity (Stilian Stoev, University of Michigan)

  • IP29 - Geodesics in first-passage percolation (Daniel Ahlberg, Stockholm University)

Invited Sessions in Statistics

  • IS1 - A Statistical View on Neural Networks (Michael Kohler, Darmstadt)

  • IS2 - Optimal Transport Methods for Statistical Data Analysis (Jonathan Niles-Weed, NYU)

  • IS3 - Interaction Discovery in Genetics (Hongzhe Li, Upenn)

  • IS4 - Second Generation Change-Point Methods: Complex Models and Fast Computation
    (Alexander Aue, UC Davis)

  • IS5 - Local Differential Privacy (Angelika Rohde, Freiburg)

  • IS6 - Bayesian Computation (Arnaud Doucet, Oxford)

  • IS7 - Causal Inference (Jonas Peters, Copenhagen)

  • IS8 - Selective Inference (Jacob Bien, USC)

  • IS9 - Network Analysis (Tracy Ke, Harvard)

  • IS10 - Spatial and Spatial-Temporal Modelling (Hsin-Cheng Huang, Academia Sinica, Taipei)

  • IS11 - Statistical Methods in Reinforcement Learning (Chengchun Shi, LSE)

  • IS12 - High-Dimensional Statistical Learning (Peter Buhlmann, ETH)

  • IS13 - Adaptive learning (Alexandra Carpentier, Magdeburg)

  • IS14 - Robust Statistics in High Dimensions (Po-Ling Loh, Cambridge)

  • IS15 - Statistical Machine Learning (Lester Mackey, Microsoft Research & Stanford)

  • IS16 - New Developments in High-Dimensional Learning and Nonparametric Inference (Jinchi Lv, University of Southern California)

  • IS17 - Recent Progress in Randomization Inference (Qingyuan Zhao, Statistical Laboratory, University of Cambridge)

  • IS18 - Quantum Computing and Statistics (Yazhen Wang, University of Wisconsin-Madison)

  • IS19 - Analysis of Multilayer Networks (Marianna Pensky, University of Central Florida)

  • IS20 - Inference Methods for Adaptively Collected Data (Kelly Zhang, Harvard University)

  • IS21 - Modern Approaches to Missing Data (Richard Samworth, University of Cambridge)

  • IS22 - Tensors in Statistics I (Anru Zhang, Duke University)

  • IS23 - Tensors in Statistics II (Han Xiao, Rutgers University)

  • IS24 - Structured High-Dimensional Inference (Alexandre Tsybakov, CREST, ENSAE, IP Paris)

  • IS25 - Conformal Predication, Semiparametric Statistics, and Casual Inference (Yachong Yang, University of Pennsylvania) 

  • IS26 - Recent Developments in High-Dimensional Time Series (Haeran Cho, University of Bristol and Matteo Barigozzi, University of Bologna)

  • IS27 - Analyzing Stochastic Gradient Methods: Noise, Nonconvexity and Dependency (Vivak Patel, University of Wisconsin-Madison)

  • IS28 - Scalable Particle Filter Algorithms and its Applications (Ning Ning, University of Michigan)

  • IS29 - New Developments on Foundations of Statistical Inference in Data Science (Minge Xie, Rutgers, The State University of New Jersey)

  • IS30 - Prediction and Sampling with Deep Neural Networks (Jian Huang, University of Iowa) 

  • IS31 - Game-theoretic statistics and safe anytime-valid inference (Aaditya Ramdas, Carnegie Mellon University)