A Conversation with Mike West
Hedibert F. Lopes, Filippo Ascolani

TL;DR
This paper provides an overview of Mike West's extensive contributions to Bayesian analysis, covering theoretical foundations, methodological advances, and diverse applications across multiple scientific disciplines.
Contribution
It highlights Mike West's interdisciplinary research, leadership, and mentorship in Bayesian statistics, emphasizing his innovative work in dynamic models, inference, and decision analysis.
Findings
Developed advanced dynamic models for time series analysis.
Contributed to foundational theories in Bayesian inference.
Applied Bayesian methods across diverse scientific fields.
Abstract
Mike West is currently the Arts & Sciences Distinguished Professor Emeritus of Statistics and Decision Sciences at Duke University. Mike's research in Bayesian analysis spans multiple interlinked areas: theory and methods of dynamic models in time series analysis, foundations of inference and decision analysis, multivariate and latent structure analysis, stochastic computation and optimisation, among others. Inter-disciplinary R&D has ranged across applications in commercial forecasting, dynamic networks, finance, econometrics, signal processing, climatology, systems biology, genomics and neuroscience, among other areas. Among Mike's currently active research areas are forecasting, causal prediction and decision analysis in business, economic policy and finance, as well as in personal decision making. Mike led the development of academic statistics at Duke University from 1990-2002, and…
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Taxonomy
TopicsAdvanced Statistical Modeling Techniques · Data Analysis with R · Gaussian Processes and Bayesian Inference
