Statistics and Probability

Adaptive designs in clinical trials.
Statistical models of call centers.
Empirical distribution of correlated observations and model selection.
Development of multiple testing procedures for selective inference.
Development of methods for replicability analysis, i.e., for discovering findings that are replicated in two or more high-dimensional studies.
Development of methods for testing hypotheses on graphs.
Applications in genomic studies.
Methodology and implementation of data mining techniques.
Statistical genetics.
Topics in bio-statistics (especially related to clinical trials).
Stochastic geometry of classical and quantum models of statistical mechanics.
Phase transitions, phase segregation, interacting particle systems, metastability.
Percolation, polymers and random walks in a random environment.
Markov processes and regenerative systems.
Properties of local times of Markov processes, permanental processes associated with local times.
Fluid and diffusion limits of queueing systems using measure-valued processes.
Multi-armed bandits in discrete and continuous time.
Logarithmically correlated fields: extremal structure, induced static and dynamic Gibbs distribution, connections with Liouville quantum gravity, Gaussian multiplicative chaos and branching random walks.
Classical statistical mechanics models: Percolation, Ising, Potts, etc.
Non-linear interacting particle systems on lattices and trees, e.g., zero-temperature Glauber dynamics.
Stochastic processes, queuing theory, service enterprise engineering applications
Stochastic partial differential equations.
Limiting behavior of branching particle systems.
machine learning
causal inference
machine learning for healthcare
deep learning
Probabilistic modeling and statistical inference on extreme values.
External index of stationary sequences.
Multivariate extremes.