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Antonio's research intersects astrostatistics and the Canadian Hydrogen Intensity Mapping Experiment, where he focuses on studying Fast Radio Bursts. |
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Archer's work centers on data integration and managing distribution shifts, mainly through the lens of semiparametric models like the Density Ratio Model and nonparametric methods such as Empirical Likelihood. |
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Austin's research focus is on the analysis and computational efficiency of Markov chain Monte Carlo algorithms. Creating reliable, computational efficient Markov chain Monte Carlo algorithms for practitioners is the main motivation for his research. |
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Benjamin-Samuel is involved in mortality estimation using Bayesian methods, with a keen interest in applied statistics and data visualization. |
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Biprateep's current research focuses on developing interpretable deep learning-based methods to predict distances to galaxies from astronomical images and for principled uncertainty quantification for machine learning algorithms. |
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Samuel focuses on hydrometric data modeling, air pollution's health impacts, and broad interests in nonparametric statistics, extreme value theory, and statistical learning. |
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Sofia's research applies statistical methods to spatio-temporal data, with specific applications in epidemiology and environmental science. |
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Yaoming's interests include tensor data analysis, network data analysis, counterfactual inference, and point processes. |