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Faculty of Mathematics

 

 

Associate Professor (Grade 9)

Research Interests: Bayesian methods and Bayesian nonparametrics, analysis of Markov models, and applications to biology and biophysics

 

Publications

Calibrated prediction of scarce adverse drug reaction labels with conditional neural processes
M Garcia-Ortegon, S Seal, S Singh, A Bender, S Bacallado
(2024)
DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design
M García-Ortegón, GNC Simm, AJ Tripp, JM Hernández-Lobato, A Bender, S Bacallado
– J Chem Inf Model
(2022)
62,
3486
BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic
Q Zhao, N Ju, S Bacallado, RD Shah
– The Annals of Applied Statistics
(2021)
15,
363
BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic
Q Zhao, N Ju, S Bacallado, RD Shah
(2020)
Bayesian mixed effects model for zero-inflated compositions in microbiome data analysis
B Ren, S Bacallado de Lara, S Favaro, T Vatanen, C Huttenhower, L Trippa
– Annals of Applied Statistics
(2020)
Bayesian Uncertainty Directed Trial Designs
S Ventz, M Cellamare, S Bacallado, L Trippa
– Journal of the American Statistical Association
(2019)
114,
962
Sufficientness Postulates for Gibbs-Type Priors and Hierarchical Generalizations
SA Bacallado de Lara, M Battiston, S Favaro, L Trippa
– Statistical Science
(2017)
32,
487
Bayesian Nonparametric Ordination for the Analysis of Microbial Communities
B Ren, S Bacallado, S Favaro, S Holmes, L Trippa
– Journal of the American Statistical Association
(2017)
112,
1430
Bayesian nonparametric inference for shared species richness in multiple populations
S Bacallado, S Favaro, L Trippa
– Journal of Statistical Planning and Inference
(2015)
166,
14
Bayesian Regularization of the Length of Memory in Reversible Sequences
S Bacallado, V Pande, S Favaro, L Trippa
– Journal of the Royal Statistical Society Series B: Statistical Methodology
(2015)
78,
933
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Research Group

Statistical Laboratory

Room

D1.10

Telephone

01223 337960