Tags: Colloquium Series

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


WenZhan Song

Connecting the dots for health and security monitoring Abstract This talk introduces our research on sensor web for health and security monitoring. In concern of cyber-physical security, we have created sensor web systems that utlize the spatio-temporal electrical signals in power networks, together with cyber signals, for the security and health monitoring of devices, machines and infrastructures. Electrical devices (including computers,…


Mandev Gill

Mixture models for improved inference of evolutionary dynamics Abstract Scientific studies in many areas of the biology routinely employ evolutionary analyses based on the probabilistic inference of phylogenetic trees from molecular sequence data. Evolutionary processes that act at the molecular level are highly variable, and properly accounting for heterogeneity in evolutionary processes is crucial for more accurate phylogenetic inference.…


Ruizhi Zhang


Adrienne Hoarfrost

Deep Learning Gateways to Illuminating the Functional Potential and Ecosystem Impacts of Microbial Communities Astract: We live in a world dominated by microbes. These microbial communities drive biogeochemical cycles that regulate current and future climate, impact ecosystem health and services, and have shaped the coevolution of life and Earth. Biology, and the biogeochemistry that is driven by it, is characterized by its complexity: in…


Garrett N Vande Kamp

Spatial Regression Models in the Presence of Measurement Error Abstract The estimation of dynamic regression models in the presence of measurement error is well understood, both in terms of consequences and solutions. But there is considerable ambiguity as to the estimation of spatial regression models in the presence of measurement error. My coauthor and I investigate this possibility, finding that there are both unique challenges and unique…


Yang Yang

Conditional likelihood – the key to analyzing infectious disease transmission in close contact groups Abstract  Close contacts groups such as households, schools and hospitals are ideal venues for understanding transmission characteristics of infectious diseases and for evaluating intervention effectiveness, due to the feasibility of tracking individual-level exposure history. However, observation of such transmission dynamics is often…


Rik Sen

Estimating the causal effect on a proportional change in probability -- an application to measuring vaccine effectiveness Abstract Instrumental variables analysis and other similar techniques, such as regression discontinuity design (RDD), have become important in finance and economics for obtaining credible causal estimates using observational data. This talk will first introduce a situation where the standard RDD falls short of producing a…


Hongyue Sun

Data science enabled decision-making in advanced manufacturing and personalized safety Abstract The advancements of sensing and information technology have brought significant opportunities to engineering systems, where data containing rich streaming and heterogenous information are collected in manufacturing, occupational, and other systems. However, there is a lack of systematic methodologies to address these high dimensional, streaming, and…


Aditya Mishra

On integrative statistical learning approach for cancer genomics and microbial science Abstract The modeling of interrelated responses utilizing correlated predictors within high-dimensional contexts emerges as a compelling conundrum in the realm of integrative statistical learning, resonating across diverse scientific inquiries. This dilemma is manifest in scenarios such as genomics, where insights into the modulation of gene expression in…


Ansu Chatterjee

Bayesian and machine learning frameworks for studying climate anomalies and social conflicts Abstract Climate change stands to have a profound impact on human society, and on political and other conflicts in particular. However, the existing literature on understanding the relation between climate change and societal conflicts has often been criticized for using data that suffer from sampling and other biases, often resulting from being too…
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