Statistics is the science of inferring knowledge from data and describing uncertainty in those inferences. It plays a central role in scientific research, social policy, and governance. The Department of Statistics has a world-class record of success in education, research and service and has an out-sized impact on campus because of its engagement in educating students in all disciplines and interdisciplinary research. Learn more about our applied and interdisciplinary research impact as well as our long list of research collaborations and interactions here.
Faculty Research Areas
Jay Breidt
Statistics + Probability Research
- Time series and spatio-temporal modeling
- Theory and methods of survey statistics
- Nonparametric regression
- Uncertainty quantification
Applied + Interdisciplinary Research
- Environmental resource inventories
- Greenhouse gas inventory and the carbon cycle
- Ecological process models
- Biochemistry
- Geological sciences
Dan Cooley
Statistics + Probability Research
- Extreme value analysis
- Tail dependence
- Risk of rare events
- Heavy tails
- Modeling
Applied + Interdisciplinary Research
- Atmospheric science
- Climate modeling
- Energy-related environmental research
Kirsten Eilertson
Statistics + Probability Research
- Applied statistics
- Generalized linear mixed models
- Latent variable and state space models
Applied + Interdisciplinary Research
- Behavioral neuroscience
- Biomechanics
- Functional genomics
- Quantitative epidemiology
- Generally public heath and medicine
Bailey Fosdick
Statistics + Probability Research
- Statistical analysis of networks
- Bayesian methodology
- Methods for survey analysis
- Multivariate analysis
Applied + Interdisciplinary Research
- Social sciences
- Population on ecology
- Science of team science
- STEM education
Ann Hess
Statistics + Probability Research
- Applied linear models
- Bioinformatics and statistical collaboration
Applied + Interdisciplinary Research
- Applied statistics and biostatistics across a broad range
Jennifer Hoeting
Statistics + Probability Research
- Bayesian statistics
- Spatial statistics
- Computational statistics
- Model selection and uncertainty
Applied + Interdisciplinary Research
- Statistical ecology
- Human and wildlife diseases
- Spatial ecology
- Climate science
Mevin Hooten
Statistics + Probability Research
- Bayesian methodology and computing
- Spatial and spatio-temporal statistics
- Point process modeling
- Hierarchical modeling using mathematical and statistical dynamical processes
Applied + Interdisciplinary Research
- Ecological and environmental animal movement modeling
- Disease ecology
- Invasive species
- Spatial ecology
- Species distribution models
Andee Kaplan
Statistics + Probability Research
- Computationally scalable statistics methods
- Record linkage (Entity resolution or de-duplication)
- Markov chain monte carlo (MCMC)
- Network analysis
- Spatial re-sampling and generalized statistical machine learning methods
- Interactive statistical graphics
- Reproducible research
Applied + Interdisciplinary Research
- Social sciences
- Data with network structures
- Multiple source data
Josh Keller
Statistics + Probability Research
- Environmental biostatistics
- Spatiotemporal modeling
- Measurement error
- Spatial confounding
- Hierarchical models
Applied + Interdisciplinary Research
- Public health
- Air pollution epidemiology
- Environmental engineering
- Infectious disease
Piotr Kokoszka
Statistics + Probability Research
- Models for dependent data
- Asymptotic theory
- Functional data analysis
- Time series
- Spatio-temporal statistics
- Change point analysis
- Extreme value theory and heavy tails
Applied + Interdisciplinary Research
- Finance
- Climate science
- Physical networks
- Space physics
Matt Koslovsky
Statistics + Probability Research
- Bayesian methodology
- Nonparametric Bayes
- Variable selection
- Statistical computing
- Markov models
Applied + Interdisciplinary Research
- mHealth
- Public health
- Cancer Prevention
- Microbiome
- Nutrition
Mary Meyer
Statistics + Probability Research
- Nonparametric function estimation with constraints involving shapes and orderings with likelihood-based inference methods
- Generalized additive models
- Robust regression
Applied + Interdisciplinary Research
- Discrete choice models in economics
- Shape selection in forestry models
Ben Shaby
Statistics + Probability Research
- Spatial statistics
- Bayesian modeling
- Bayesian computation
- Extreme values
Applied + Interdisciplinary Research
- Climate and weather
- Geophysics
- Neurodegenerative diseases like Alzheimer’s and ALS
- High-throughput biological data
Julia Sharp
Statistics + Probability Research
- Statistical consulting
- Statistical applications
- Experimental design and analysis
- Mixed effects models
Applied + Interdisciplinary Research
- Public health
- Nutrition
- Food science
- Agricultural studies
- Life sciences
- Proteomics
Haonan Wang
Statistics + Probability Research
- Object oriented data analysis
- Functional data analysis
- Functional dynamic modeling
- Spatial and spatiotemporal modeling
- Statistical learning for big data
- Time series
- Statistical modeling for complex networks
Applied + Interdisciplinary Research
- Neuroscience
- Communication networks
- Sensor data
Zach Weller
Statistics + Probability Research
- Bayesian statistics
- Spatial statistics
- Non-parametric statistics
Applied + Interdisciplinary Research
- Applications in biology, ecology, energy, environmental issues and wildlife management
Ander Wilson
Statistics + Probability Research
- Bayesian statistics
- Confounder selection and model uncertainty
- Functional regression
- Environmental statistics
Applied + Interdisciplinary Research
- Public health
- Environmental epidemiology
- Air pollution epidemiology
- Children’s health
Tianjian Zhou
Statistics + Probability Research
- Bayesian methodology and computing
- Bayesian hierarchical modeling
- Bayesian nonparametrics
- Bayesian hypothesis testing
- Methodology for missing data
Applied + Interdisciplinary Research
- Clinical trials
- Genomics
- Infectious diseases
Wen Zhou
Statistics + Probability Research
- High dimensional inference
- Statistical machine learning
- Graphical modeling
- Statistical genomics and genetics
- Bioinformatics
- Inverse problems
- Multivariate time series
Applied + Interdisciplinary Research
- Genetics and genomics
- Proteomics and structure biology
- Omics analysis
- Integrative analysis
- System biology
- Econometrics and finance
DEPARTMENT NEWS
Assistant professor develops novel methods for analyzing microbiome data
Human microbiome research seeks to better understand the role of our microbial communities and how they interact with their host, respond to their environment and influence disease.
Statistics professor honored for expertise in object-oriented data analysis
Haonan Wang’s creativity and research excellence recently earned him election as a Fellow of the American Statistical Association, the world’s largest community of statisticians.
By storing ‘sketches’ of data, computer scientists seek to transform urban systems
A research team is developing a system for streamlining and managing vast datasets that could advance research in urban sustainability.
NYC utility improves safety of natural gas pipelines, thanks to CSU science
Research that uses Google Street View cars to map natural gas methane leaks is helping the nation’s largest metropolitan area prioritize tens of millions of dollars in infrastructure upgrades.
