Tags: Colloquium Series

The Statistics Department hosts weekly colloquia on a variety of statistcal subjects, bringing in speakers from around the world.


Departmental Colloquium - Dr. Jordan Eckers

Abstract: Prototype selection has become a large area of current research in statistical learning. We introduce a novel topological data analysis (TDA)-based framework for selecting representative prototypes from large datasets. We show that this approach preserves classification performance while substantially reducing data size. Such methods are crucial in resource-constrained environments where memory and computation are limited. Together,…


Departmental Colloquium - Dr. Sanjukta Nath

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Departmental Colloquium - Dr. Sarah Haight

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Departmental Colloquium - Dr. Xinran Li

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Dr. Emma Zhang


Departmental Colloquium - Dr. Vasileios Pavlopoulos

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Departmental Colloquium - Dr. Dennis Lin

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Departmental Colloquium - Dr. João M. Pereira

Method of Moments: From Sample Complexity to Efficient Implicit Computations Abstract: The focus of this talk is the multivariate method of moments for parameter estimation. First from a theoretical standpoint, we show that in problems where the noise is high, the sample complexity, that is, the number of observations necessary to estimate parameters, is dictated by the moments of the distribution. This follows from a Taylor expansion of the KL…


Susmita Datta

Unraveling Disease Mysteries: Statistical Models Reveal Cellular Conversations using Spatial Transcriptomics data. Abstract: Understanding cell microenvironments from spatially resolved transcriptomics data is a cutting-edge approach in biomedical research. This innovative method enables scientists to investigate the spatial organization of cells near diseased tissues and identify their inter - and intracellular communications through…


Ying Guo

A Regularized Blind Source Separation Method for Disentangling Dynamic Functional Connectome Abstract: Brain connectomics has become increasingly popular in neuroimaging studies to advance understanding of neural circuits and their association with neurodevelopment, mental illnesses, and aging. These analyses often face major challenges, including the high dimensionality of brain networks, unknown latent sources underlying the observed…
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