The Savage Award, named in honor of Leonard J. “Jimmie” Savage, is bestowed each year to two outstanding doctoral dissertations in Bayesian econometrics and statistics, one each in:

• Theory and Methods:   for a dissertation that makes important original contributions to the foundations, theoretical developments, and/or general methodology of Bayesian analysis.
• Applied Methodology:   for a dissertation that makes outstanding contributions with novel Bayesian analysis of a substantive problem that has potential to impact statistical practice in a field of application.

Each award is accompanied by a monetary prize.

The award was instituted by the NBER-NSF Seminar in Bayesian Inference in Econometrics and Statistics in 1977 with an endowed fund supported by royalties from a series of books authored and edited under the auspices of  the Seminar on Bayesian Inference in Econometrics. ISBA and the ASA Section on Bayesian Statistical Science (SBSS) joined as co-sponsors in 1993.   Additional contributions to the endowment include royalties from the Handbook of Bayesian Econometrics edited by John Geweke, Gary Koop and Herman van Dijk. and donations by past recipients of the Savage Prize and members of ISBA.

Leonard J. (“Jimmie”) Savage

Born November 20, 1917, Jimmie Savage was graduated from the University of Michigan and later worked at the Institute for Advanced Study in Princeton, New Jersey, the University of Chicago, and the Statistical Research Group at Columbia University. Though his thesis advisor was Sumner Myers, he also credited Milton Friedman and W. Allen Wallis as his statistical mentors.

Eligibility and Application Procedure

Winners of the Savage Award

2022
Theory & Methods
Edwin Fong, The predictive view of Bayesian inference. University of Oxford; Chris Holmes, advisor.
Saifuddin Syed (Honorable Mention), Non-reversible parallel tempering on optimized paths. University of British Columbia; Alexandre Bouchard-Côté , advisor.
Matteo Giordano (Honorable Mention), Asymptotic theory for Bayesian nonparametric inference in statistical models arising from partial differential equations. University of Cambridge; Richard Nickl, advisor.
Yixin Wang (Honorable Mention), Multiple causal inference with Bayesian factor models. Columbia University; David M. Blei, advisor.

Applied Methodology
Emily Wang, Bayesian state-space models with variable selection for neural count data. Rice University; Marina Vannucci, advisor.
Paul Parker (Honorable Mention), Bayesian unit-level modeling of non-Gaussian survey data under informative sampling with application to small area estimation. University of Missouri; Scott H. Holan, advisor.
Zhao Tang Luo (Honorable Mention), Bayesian spanning tree models for complex spatial data. Texas A&M University; Huiyan Sang and Bani Mallick, advisors.
Maria Masotti (Finalist), Bayesian functional spatial partitioning methods for prostate cancer lesion detection . University of Minnesota; Joseph S. Koopmeiners and Lin Zhang, advisors.

2021
Theory & Methods
Aritra Guha, Inference and Interpretability in Latent Variable Modeling. University of Michigan; Long Nguyen, advisor.
Marta Catalano (Finalist), On complex dependence structures in Bayesian nonparametrics: a distance based-approach. University of Warwick; Antonio Lijoi and Igor Prünster, advisors.
Aditi Shenvi (Finalist), Non-stratified chain event graphs: dynamic variants, inference and applications. University of Warwick; Jim Q. Smith, advisor.
John O’Leary (Finalist), Coupling and Parallelization in Statistical Inference. Harvard University; Pierre E. Jacob, advisor.

Applied Methodology
Cecilia Balocchi, Bayesian nonparametric analysis of spatial variation with discontinuities. University of Edinburgh; Edward I. George and Shane T. Jensen, advisors.
Neil Marchant (Honorable Mention), Statistical approaches for entity resolution under uncertainty. University of Melbourne; Ben Rubinstein and Rebecca C. Steorts, advisors.
Augusto Fasano (Finalist), Advances in Bayesian inference for binary and categorical data. Bocconi University; Daniele Durante and Igor Prünster, advisors.
Valerio Perrone (Finalist), Bayesian models for scalable machine learning. University of Oxford/University of Warwick; Dario Spanò, Paul Jenkins, and Yee Whye Teh, advisors.

2020
Theory & Methods
Tommaso Rigon, Finite-dimensional nonparametric priors: Theory and applications. Bocconi University; Antonio Lijoi and Igor Prünster, advisors.
Leah South (Honorable Mention), Contributions to computational Bayesian statistics. Queensland University of Technology; Christopher Drovandi, advisor.
George Papamakarios (Finalist), Neural density estimation and likelihood-free inference. University of Edinburgh; Iain Murray, advisor.
Seonghyun Jeong (Finalist), Frequentist properties of Bayesian procedures for high-dimensional sparse regression. North Carolina State University; Subhashis Ghosal, advisor.

Applied Methodology
Adji Bousso Dieng, Deep Probabilistic Graphical Modeling. Columbia University; David Blei, advisor.
Kelly Moran (Honorable Mention), Advances in Bayesian Factor Modeling and Scalable Gaussian Process Regression. Duke University; Amy Herring, advisor.
Sharmistha Guha (Honorable Mention), Bayesian Methods in Network Regression with Applications in Brain. University of California, Santa Cruz; Abel Rodriguez, advisor.
Daniel Spencer (Finalist), Inference and uncertainty quantification for high-dimensional tensor regression with tensor decompositions and Bayesian methods. University of California, Santa Cruz; Rajarshi Guhaniyogi and Raquel Prado, advisors.

2019
Theory & Methods
Christian Andersson Naesseth, Machine learning using approximate inference. Variational and sequential Monte Carlo methods. Linköping University; Fredrik Lindsten and Thomas Schön, advisors.
Espen Bernton (Honorable Mention), Optimal Transport in Statistical Inference and Computation. Harvard University; Pierre Jacob, advisor.
Francois-Xavier Briol (Honorable Mention), Statistical Computation with Kernels. University of Warwick; Mark Girolami, advisor.

Applied Methodology
Alejandra Avalos-Pacheco, Factor regression for dimensionality reduction and data integration techniques with applications to cancer data. University of Warwick; Richard Savage and David Rossell, advisors.
Lindsay Berry (Honorable Mention), Bayesian Dynamic Modeling and Forecasting of Count Time Series. Duke University; Mike West, advisor.

2018
Theory & Methods
Rajesh Ranganath, Black Box Variational Inference: Scalable, Generic Bayesian Computation and its Applications.  Princeton University; David Blei, advisor.
Andrew Holbrook (Honorable Mention), Geometric Bayes.  University of California, Irvine; Babak Shahbaba, advisor.

Applied Methodology
Henry Scharf, Statistical Models for Dependent Trajectories With Applications to Animal Movement.  Colorado State University; Mevin Hooten, advisor.
Tianjian Zhou (Honorable Mention), Bayesian Nonparametric Models for Biomedical Data Analysis.  The University of Texas at Austin; Peter Müller, advisor.

2017
Theory & Methods
Jackson Gorham, Measuring Sample Quality with Stein’s Method.  Stanford University; Lester Mackey, advisor.
Akihiko Nishimura (Honorable Mention), General and Efficient Bayesian Computation Through Hamiltonian Monte Carlo Extensions.  Duke University; David Dunson, advisor.

Applied Methodology
Lorin Crawford, Bayesian Kernel Models for Statistical Genetics and Cancer Genomics.  Duke University; Sayan Mukherjee, advisor.
Abhirup Datta (Honorable Mention), Statistical Methods for Large Complex Datasets.  University of Minnesota; Sudipto Banerjee, advisor.
Giacomo Zanella (Honorable Mention), Bayesian Complementary Clustering, MCMC and Anglo-Saxon Placenames.  University of Warwick; Wilfrid S. Kendall, advisor.

2016
Theory & Methods
Federico Camerlenghi, Hierarchical and Nested Random Probability Measures with Statistical Applications.   University of Pavia; Antonio Lijoi and Igor Prünster, advisors.
Prithwish Bhaumik (Honorable Mention), Bayesian Estimation and Uncertainty Quantification in Differential Equation Models. North Carolina State University; Subhashis Ghoshal, advisor.

Applied Methodology
Scott Linderman, Bayesian Methods for Discovering Structure in Neural Spike Trains. Harvard University; Ryan Adams and Leslie Valiant, advisors.
Yang Ni (Honorable Mention), Bayesian Graphical Models for Complex Biological Networks, Rice University; Francesco Stingo and Veera Baladandayuthapani, advisors.

2015
Theory & Methods
Tamara Broderick, Clusters and Features from Combinatorial Stochastic Processes.   University of California, Berkeley; Michael Jordon, advisor.
Botond Szabó (Honorable Mention), Adaptation and Confidence in Nonparametric Bayes.  Eindhoven University of Technology; Harry van Zanten and Aad van der Vaart, advisors.

Applied Methodology
Maria De Yoreo, A Bayesian Framework for Fully Nonparametric Ordinal Regression.  University of California, Santa Cruz; Athanasios Kottas, advisor.
Linen Zhang (Honorable Mention), Bayesian Nonparametric Models for Functional Magnetic Resonance Imaging (fMRI) Data.  Rice University; Marina Vannucci, advisor.

2014
Theory & Methods
Vinayak Rao, Markov Chain Monte Carlo for Continuous-Time, Discrete State Systems.  University of Oxford; Yee Whye Teh, supervisor.
Veronika Rockova (Honorable Mention), Bayesian Variable Selection in High-Dimensional Applications.  Erasmus Universiteit Rotterdam;  E. M. E. H. Lessafre and B. Lowenberg, advisors.
Sayantan Banerjee (Honorable Mention), Bayesian Inference for High Dimensional Models; Convergence Properties and Computations Issues.  North Carolina State University;  Subhashis Ghoshal, advisor.

Applied Methodology
Christine Peterson, Bayesian Graphical Models for Biological Network Inference. Rice University; Marina Vanucci, advisor.
Masanao Yajima (Honorable Mention), Bayesian Modeling of Interactions of Structured Heterogeneous Data.  University of California – Los Angeles; Jan de Leeuw and Donatello Telesca, advisors.

2013
Theory & Methods
Weining Shen, Adaptive Bayesian Function Estimation.  North Carolina State University; Subhasis Ghosal, advisor.
Depdeep Pati (Honorable Mention), Bayesian Nonparametric Modeling and Theory for Complex Data.  Duke University; David Dunsun, advisor.

Applied Methodology
Ole Maneesoonthorn, Stochastic Volatility, Jumps and Variance Risk Premia: A Bayesian state space approach. Monash University;
Osvaldo Anacleto (Honorable Mention), Bayesian Dynamic Graphical Models for High-Dimensional Flow Forescasting in Road Traffic Networks.  Open University; Catriona Queen and Paul Garthwaite, advisors.

2012
Theory & Methods
Anirban Bhattacharya, Bayesian Shrinkage in High Dimensions .  Duke University; David Dunson, advisor.
Bernardo Nipoti (Honorable Mention), Dependent Completely Random Measures and Statistical Applications.  University of Pavia; Antonio Lijoi, advisor.

Applied Methodology
Avishek Chakraborty, Modeling Point Patterns, Measurement Error and Abundance for Exploring Species Distributions.  Duke University; Alan Gelfand, advisor.
Rebecca C. Steorts (Honorable Mention), Small Areas, Benchmarking, and Political Battles: Today’s Novel Demands in Small-Area Estimation.  University of Florida; Malay Ghosh, advisor.

2011
Theory & Methods
Juan Carlos Martinez-Ovando, Contributions to Bayesian Nonparametric Modelling of Time-Series Data.  University of Kent; Stephen G. Walker, advisor.
Gun Ho Jang (Honorable Mention), Invariant Procedures in Model Checking for Prior-Data Conflict and Bayesian Analysis.  University of Toronto; Michael Evans, advisor.

Applied Methodology
Kaisey Mandel, Improving Cosmological Distances to Illuminate Dark Energy: Hierarchical Bayesian Models for Type Ia Supernovae in the Optical and Near-Infrared. Harvard University; Robert Kirshner, advisor.
Fabian Scheipl (Honorable Mention), Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models.  Ludwig-Maximilians-Universitat Munchen; Ludwig Fahrmeir, advisor.

2010
Theory & Methods
Julien Cornebise, Adaptive Sequential Monte Carlo Methods. Université Pierre et Marie Curie – Paris 6, France; Eric Moulines, advisor.
Daniel Williamson (Honorable Mention), Policy Making Using Computer Simulators for Complex Physical Systems; Bayesian Decision Support for the Development of Adaptive Strategies. Durham Univ, UK; Michael Goldstein, advisor.

Applied Methodology
Ricardo Lemos, Hierarchical Bayesian Methods for the Marine Sciences: Analyses of Climate Variability and Fish Abundance. University of Lisbon, Portugal; Henrique Cabral and Ramiro Neves, advisors.
Robin Ryder (Honorable Mention), Phylogenetic Models of Language Diversification. University of Oxford, UK. Geoff Nicholls, advisor.

2009
Theory & Methods
James G. Scott, Bayesian Adjustment for Multiplicity. Duke Univ, USA; James Berger, advisor.
Ryan Prescott Adams (Honorable Mention), Kernel Methods for Nonparametric Bayesian Inference of Probability Densities and Point Processes. University of Cambridge, UK; David MacKay, advisor.

Applied Methodology
Emily B. Fox, Bayesian Nonparametric Learning of Complex Dynamical Phenomena. Massachusetts Institute of Technology, USA; Alan S. Willsky & John W. Fisher III, advisors.
Matthew A. Taddy (Honorable Mention), Bayesian Nonparametric Analysis of Conditional Distributions and Inference for Poisson Point Processes. University of California at Santa Cruz, USA; Athanasios Kottas, advisor.

2008
Theory & Methods
Lorenzo Trippa, Some Extensions of the Polya Urn scheme with Bayesian Applications. L. Bocconi University (Milano, IT); Pietro Muliere, advisor.

Applied Methodology
Alejandro Jara, Bayesian Semiparametric Methods for the Analysis of Complex Data. Katholieke Universiteit Leuven (BE); Emmanuel Lesaffre, Irene Gijbels and Geert Verbeke, advisors.
Donatello Telesca (Honorable Mention), Bayesian Hierarchical Curve Registration. U Washington (Seattle, US); Lurdes Y.T. Inoue, advisor.
Astrid Jullion (Finalist), Adaptive Bayesian P-splines models for Fitting Time-Activity Curves and Estimating Associated Clinical Measures in Positron Emission Tomography and Pharmacokinetic Studies. Université Catholique de Louvain, Belgium; Philippe Lambert, advisor.

2007
Theory & Methods
Kostas Kalogeropoulos, Bayesian Inference for Multidimensional Diffusion Processes. Athens University Economics and Business; Petros Dellaportas, advisor.
Iain Murray (Honorable Mention), Advances in Markov chain Monte Carlo Methods. University College London; Zoubin Ghahramani, advisor.

Applied Methodology
Vladimir Minin, Exploring Evolutionary Heterogeneity with Change-Point Models, Gaussian Markov Random Fields, and Markov Chain Induced Counting Processes. UCLA; Marc Suchard, advisor.
Edoardo M. Airoldi (Honorable Mention), Bayesian Mixed-Membership Models of Complex and Evolving Networks. CMU; Stephen E. Fienberg and Kathleen Carley, advisors.

2006
Theory & Methods
Surya Tokdar, Exploring Dirichlet Mixture and Logistic Gaussian Process Priors in Density Estimation, Regression and Sufficient Dimension Reduction. Purdue Univ; J.K. Ghosh, advisor.
Pierpaolo de Blasi (Honorable Mention), Semiparametric Models in Bayesian Event History Analysis. Bocconi U; Nils Lid Hjort & Pietro Muliere, advisors.

Applied Methodology
Robert Gramacy, Bayesian Treed Gaussian Process Models. UCSC; Herbie Lee, advisor.
Carlos Carvalho (Honorable Mention), Structure and Sparsity in High-Dimensional Multivariate Analysis. Duke University; Mike West, advisor.

2005
Theory & Methods
Xinyi Xu, Estimation of High Dimensional Predictive Densities. University of Pennsylvania; Ed George, advisor.
Taeryon Choi (Honorable Mention), Posterior Consistency in Nonparametric Regression Problems under Gaussian Process Priors. CMU; Mark Schervish, advisor.

Applied Methodology
Dimitris Nicoloutsopoulos, Parametric and Bayesian Non-parametric Estimation of Copulas. UCL; Phil Dawid, advisor.
Billy Amzal (Honorable Mention), Optimisation Bayésienne de Décisions et de Plans d’Expériences par Algorithmes Particulaires. University Paris Dauphine; Eric Parent & Christian Robert, advisors.

2004
Theory & Methods
Mario Trottini (Honorable Mention), Decision Models for Data Disclosure Limitation. Carnegie Mellon University; Stephen Fienberg, advisor.
Ramses Mena (Honorable Mention), Stationary Models using Latent Structures. University Bath; Stephen Walker, advisor.

Application Methodology
Shane Jensen, Statistical Techniques for Examining Gene Regulation. Harvard University; Jun Liu, advisor.
Jesus Palomo (Honorable Mention), Bayesian Methods in Bidding Processes. Rey Juan Carlos University; David Ríos Insua & Fabrizio Ruggeri, advisors.

2003
Theory & Methods
Chris Paciorek, Non-Stationary Gaussian Processes for Regression and Spatial Modeling. Carnegie Mellon University; Mark Schervish, advisor.

Application Methodology
Louis T. Mariano, Information Accumulation, Model Selection, and Rater Behavior in Constructed Response Student Assessments. Carnegie Mellon University; Brian Junker, advisor.

2002
Theory & Methods
Nicolas Chopin, Applications des Méthodes de Monte Carlo Séquentielles à la Statistique Bayésienne. University Paris Dauphine; Christian Robert, advisor.

Application Methodology
Marc Suchard, Model Building and Selection in Bayesian Phylogenetic Reconstruction. UCLA; Robert Weiss, advisor.

2001
Theory & Methods
Luis E. Nieto-Barajas, Bayesian Nonparametric Survival Analysis via Markov Processes. University Bath; Stephen Walker, advisor.

Application Methodology
J. R. Lockwood, Estimating Joint Distributions of Contaminants in U.S. Community Water System Sources. CMU; Mark Schervish, advisor.

2000
Theory & Methods
Peter Hoff (Co-winner), Constrained Nonparametric Estimation via Mixtures. University Wisconsin; Michael Newton, advisor.
Tzee-Ming Huang (Co-winner), Convergence Rates for Posterior Distributions. Carnegie Mellon University; Larry Wasserman, advisor.

Application Methodology
Jeremy Oakley, Bayesian Uncertainty Analysis for Complex Computer Code. University of Sheffield; Tony O’Hagan, advisor.
Tim Hanson (Honorable Mention), Applied Bayesian Semiparametric Methods with Special Application to the Accelerated Failure Time Model and to Hierarchical Models for Screening UC Davis; Wes Johnson, advisor.

1999
Theory & Methods
Garrick L. Wallstrom, Consistency and Strong Inconsistency of Inferences. University of Minnesota; Joe Eaton, advisor.

Application Methodology
Clare E. Marshall, Statistical Methods for Institutional Comparisons. Cambridge Univ; David Spiegelhalter, advisor.
Andrew S. Mugglin (Honorable Mention), Fully Model-Based Approaches for Spatially Misaligned Data. University of Minnesota; Brad Carlin, advisor.

1998
Antonietta Mira, Ordering, Splicing and Splitting Monte Carlo Markov Chains. University of Minnesota; Luke Tierney, advisor.

Jaelong Lee (Honorable Mention) Semiparametric Bayesian analysis: selection models and meteorolgical applications. Purdue Univ; Jim Berger, advisor.

1997
David Denison, Simulation Based Bayesian Non-parametric Regression Methods. Imperial College; Bani Mallick & Adrian Smith, advisors.

Juha Heikkinen (Honorable Mention), Bayesian Smoothing and Step Functions in Nonparametric Estimation of Curves and Surfaces. University of Helsinki; Antti Penttinen & Elija Arjas, advisors.

1996
Nariankadu D. Shyamalkumar, Contributions to Bayesian Nonparametrics and Bayesian Robustness. Purdue Univ; Jim Berger, advisor.

Eric Bradlow (Honorable Mention), A Hierarchical Latent Response Model for Ordinal Data with “No Answer” Responses. Harvard University; Alan Zaslavsky, advisor.

Max Chickering (Honorable Mention), Learning Bayesian Networks from Data. UCLA; David Heckerman, Richard Korf & Judea Pearl, advisors.

Andrea Piesse (Honorable Mention), Coherent Predictive Probabilities. University of Canterbury; John Deely & Frank Lad, advisors.

1995
Christopher K. Carter (Co-winner), On Markov Chain Monte Carlo for Linear State Space. University or New South Wales; Robert Kohn, advisor.

Alyson Wilson (Co-winner) Statistical Models for Shapes and Deformations. Duke University; Valen Johnson, advisor.

Simon J. Godsill (Honorable Mention), The Restoration of Degraded Audio Signals.

Ming-Hui Chen (Honorable Mention), Monte Carlo Markov Chain Sampling for Bayesian Computation with Applications. Purdue Univ; Jim Berger & Bruce Schmeiseer, advisors.

1994
Merlise A. Clyde, Bayesian Optimal Designs for Approximate Normality. University of Minnesota; Kathryn Chaloner, advisor.

Marìa Del Carmen Fernandez-Llana (Honorable Mention), Estudios Sobre Robustez Bayesiana Global. University of Autonoma de Madrid; Julian de la Horra, advisor.

Paul Gustafson (Honorable Mention), Local Sensitivity of Posterior Expectations. CMU; Larry Wasserman, advisor.

Debajyoti Sinha (Honorable Mention), Semiparametric Bayesian Analysis of Single and Multiple Time Event Data. University of Rochester; W Jack Hall, advisor.

1993
Charles Jeremy York, Bayesian Methods for the Analysis of Misclassified or Incomplete Multivariate Data.

1990
Giovanni Parmigiani, Optimal Scheduling of Inspections with an Application to Medical Screening Tests.

1989
Valen E. Johnson, On Statistical Image Reconstruction.

1988
Michael David Escobar, Estimating the Means of Several Normal Populations by Nonparametric Estimation of the Distribution of the Means.

1987
Peter E. Rossi, Specification and Analysis of Econometric Production Models.

1986
Mohan Delampady (Co-winner), Testing a Precise Hypothesis Interpreting P-Values from a Robust Bayesian Viewpoint.

S. Sivaganesan (Co-winner), Robust Bayesian Analysis with Contamminated Classes.

Herman K. van Dijk (Co-winner), Posterior Analysis of Econometric Models Using Monte Carlo Integration.

1985
Peter Jamison Lenk, Bayesian Nonparametric Predictive Distributions.

1984
Luc Bauwens (Co-winner), Bayesian Full Information Analysis of Simultaneous Equation Models.

Peter C. Cranston (Co-winner), The Role of Time and Information in Bargaining.
1983

Paul H. Garthwaite, Assessment of Prior Distributions for Normal Linear Models.

1982
Soo Hong Chew, Two representation Theorems and Their Applications to Decision Theory.

1981
Robert Kass (Co-winner), The Riemannian Structure of Model Spaces: A Geometrical Approach to Inference.

John P. O’Connor (Co-winner), A Certainty Equivlaent Based Metrization of Utility Function Space.

1980
Paul Milgram, The Structure of Information in Competitive Bidding.

1979
Kevin James McConway, The Combination of Experts’ Opinions in Probability Assessment: Some Theoretical Considerations.

1978
Lorraine DeRobertis, The Use of Partial Prior Knowledge in Bayesian Inference.

José Bernardo (Honorable Mention), The Use of Information in the Design and Analysis of Scientific Experimentation.

1977
Charles A. Holt, Bidding for Contracts.

Robert Shore (Honorable Mention), A Bayesian Approach to the Spectral Analysis of Stationary Time Series.