Clinic Team
Our team of experts cover a diverse set of topics in statistics; including but not limited to those listed below.
Nicole Augustin
Methods: Spatio-temporal models, spatial models, health statistics, spatial confounding, model selection uncertainty
Applications: ecology, Accelerometer data, Fisheries stock management, Forest health monitoring, Physical activity, Tobacco control
Tim Cannings
Methods: classification and clustering, high-dimensional data, nonparametric, random projections, data perturbation, noisy and incomplete data
Applications: big data analytics, cancer therapy, genomic data, precision medicine
Victor Elvira
Methods: Bayesian inference, computational statistics, Monte Carlo methods, state-space models, statistical statistics
Applications: communications, localization, remote sensing, tracking, wireless sensor networks
Ruth King
Methods: Bayesian inference, capture-recapture, hidden (semi-)Markov models, integrated models, missing data, state-space models
Applications: epidemiology, medicine, ecology
Amanda Lenzi
Methods: spatiotemporal statistics, Bayesian inference, deep learning, statistics of extremes
Applications: geoscience, energy, environmental science
Daniel Paulin
Methods: Markov chain Monte Carlo, Hamiltonian dynamics, concentration inequalities, matrix-free optimization methods
Applications: statistical genetics, Weather forecasting, stochastic volatility models in finance
Gordon Ross
Methods: Bayesian inference, time series, nonparametrics, point process
Applications: finance, risk, cybersecurity, earthquakes, seismology
Torben Sell
Methods: Markov chain Monte Carlo, Piecewise deterministic Markov processes, Particle filtering, Function space sampling methods
Applications: Stochastic control, Bayesian neural networks
Simon Wood
Methods: fast stable computation, MGCV, penalized regression, Smoothing
Applications: energy, environment