Functional Ultrasound Imaging (fUSI): A game changer in neuroscience and medicine
Abstract: Recent advances in neuroimaging technology have significantly contributed to a better understanding of human brain organization, and the development and application of more efficient clinical programs. However, the limitations and tradeoffs inherent to the existing techniques, prevent them from providing large-scale imaging of neural activity with high spatiotemporal resolution, deep penetration, and specificity in...
Statistical methods for analyzing and comparing single-cell gene expression data
Abstract: Single-cell RNA sequencing (scRNA-seq) experiments enable gene expression measurement at a single-cell resolution, and provide an opportunity to characterize the molecular signatures of diverse cell types and states in tissue development and disease progression. However, it remains a challenge to construct a comprehensive view of single cell transcriptomes in health and disease, due to...
Why 95% of papers on Time Series Anomaly Detection are Wrong (with more general lessons for Researchers).
Abstract: Time Series Anomaly Detection (TSAD) is the task of monitoring a time series, say an ECG, or the pressure in an industrial boiler, while attempting to recognize when there has been an anomalous event. The anomalies could be the beginning of heart attack, or a leak in the boiler that will cause the industrial...
Estimation and Sensitivity Analysis for Causal Decomposition: Assessing Robustness Toward Omitted Variable Bias
Abstract: A key objective of decomposition analysis is to identify risks or resources (‘mediators’) that contribute to disparities between groups of individuals defined by social characteristics such as race, ethnicity, gender, class, and sexual orientations. In decomposition analysis, a scholarly interest often centers on estimating how much the disparity (e.g., health disparities between Black women...
A Bayesian multilevel time-varying framework for joint modeling of hospitalization and survival in patients on dialysis.
Abstract: Over 782,000 individuals in the U.S. have end-stage kidney disease with about 72% of patients on dialysis, a life-sustaining treatment. Dialysis patients experience high mortality and frequent hospitalizations, at about twice per year. These poor outcomes are exacerbated at key time periods, such as the fragile period after transition to dialysis. In order to...
Deplatforming Right-Wing Extremists on Twitter Following the January 6 Insurrection
Abstract: What happened when Twitter deplatformed 70,000 right-wing extremists following the January 6 insurrection? Using a panel of over a half million active Twitter users and a sharp regression discontinuity design, we test the causal effects of this intervention on the circulation of misinformation by those deplatformed, and by users from adjacent groups such as...
Understanding Large ML Models through the Structure of Feature Covariance
Abstract: An overarching goal in machine learning is to enable accurate statistical inference in the setting where the sample size is less than the number of parameters. This overparameterized setting is particularly common in deep learning where it is typical to train large neural nets with relatively smaller sample sizes and little concern of overfitting...
Multiview learning for knowledge discovery
Abstract: Extracting hidden patterns of multiview data containing heterogeneous feature representations is attracting more and more attention in various scientific fields such as image processing and natural language processing. In this talk we will present a comprehensive unsupervised framework that leverages existing and novel multiview learning models, towards obtaining a single node embedding from a...
Characterizing soil – plant – water relationships across scales for sustainable agricultural management
Abstract: Agricultural systems are pressured by growing global population, increasing water scarcity, and changing climate. In the pursuit of increasing food security, agriculture (especially intensive systems) should also minimize negative and undesired impacts on the environment and on rural societies. Part of the solution to this challenge lies in understanding how environmental factors such as...
Immune regulatory pathways in infection, inflammation and sepsis
Abstract: My lab investigates the immune responses to infection and inflammation using mouse models of parasitic worm infection and clinical samples from sepsis patients. Our ultimate goal is to identify protective or pathogenic immune pathways that we can target for diagnostic or therapeutic purposes. In our mouse infection models we investigate macrophages as first responders...