I am a Harrison Early Career Assistant Professor at the Department of Statistics, University of Warwick.
My research interests are statistics and machine learning, particularly Bayesian nonparametrics, regression, density estimation, clustering, and feature allocation. Applications of interest include the study of Alzheimer’s disease based on neuroimaging, biological, and clinical data.
Before joining the department, I was a postdoctoral researcher at University of Cambridge working with Prof. Zoubin Ghahramani on Bayesian nonparametric clustering and feature allocation. In January 2013, I earned my PhD in Statistics from Bocconi University in Milan, working on Bayesian nonparametric regression with Prof. Sonia Petrone.
I am the chair of BAYSM 2018: Bayesian Young Statisticians Meeting to be held on 2-3 July, 2018 at the Department of Statistics, University of Warwick: warwick.ac.uk/statistics/staff/academic-research/wade/2018baysmconference/
I co-organised a CRiSM workshop on Contempory Issues in Hypothesis Testing on September 15-16, 2016 at Department of Statistics, University of Warwick: warwick.ac.uk/crism/workshops/hypothesistesting
Term 1 2015/2016: "Fundamentals of Modern Statistical Inference" ST911.
Term 2 2015/2016: "Bayesian Nonparametrics" Statistical Frontiers Seminar ST912.
- Wade, S. and Ghahramani, Z. (2017). Bayesian cluster analysis: Point estimation and credible balls. To appear in Bayesian analysis. arXiv
- Prestia, A., Caroli, A., Wade, S., van der Flier, W.M., Ossenkoppele, R., Van Berckel, B., Barkhof, F., Teunissen C.E., Wall, A., Carter, S.F., Scholl, M., Choo, I.H., Nordberg, A., Scheltens, P., and Frisoni, G.B. (2015). “Prediction of AD dementia by biomarkers following the NIA-AA and IWG diagnostic criteria in MCI patients from three European memory clinics”. Alzheimer’s & Dementia. link
- Caroli, A., Prestia, A., Wade, S., Chen, K., Ayutyanont, N., Landau, S.M., Madison, C.M., Haense, C., Herholz, K., Reiman, E.M., Jagust, W.J., and Frisoni, G.B. (2015). “Alzheimer’s disease biomarkers as outcome measures for clinical trials in MCI”. Alzheimer’s Disease and Associated Disorders, 29:101-109. link
- Antoniano Villalobos I., Wade S., and Walker S. G. (2014). “A Bayesian nonparametric regression model with normalized weights; A study of hippocampal atrophy in Alzheimer’s disease.” Journal of the American Statistical Association, 109:477-490. link
- Wade S., Dunson D., Petrone S., Trippa, L. (2014). “Improving prediction from Dirichlet process mixtures via enrichment.” Journal of Machine Learning Research, 15:1041-1071. link
- Wade S., Walker S. G., and Petrone S. (2014). “A predictive study of Dirichlet process mixture models for curve fitting.” Scandinavian Journal of Statistics, 41:580-605. link
- Wade S., Mongelluzzo S., and Petrone S. (2011). “A enriched conjugate prior for Bayesian nonparametric inference.” Bayesian Analysis, 6:359-386. link
- R package mcclust.ext (2015) for point estimation and credible balls to summarize Bayesian clustering models. mcclust.ext_1.0.tar.gz mcclust.ext-manual
- Charles Gadd (PhD), co-supervised with Dr Akeel Shah (Engineering)
Dr Sara Wade
Dept of Statistics
University of Warwick
Coventry, CV4 7AL
s.wade AT warwick.ac.uk
R2.26, Ramphal Building
Term 3 2015/16: