SDS Seminar Series – Shuangjie Zhang, University of Texas at Austin
Sep
11
2026
Sep
11
2026
Description
The Fall 2026 SDS Seminar Series kicks off on September 11th from 2:00 p.m. to 3:00 p.m. with postdoctoral fellow Shuangjie Zhang (postdoctoral fellow, Department of Statistics & Data Science, UT Austin0. This event is in-person in the Avaya Room (POB 2.302).
Title: Structure Learning for Directed Trees with Zero-Inflated Compositional Nodes
Abstract: Zero-inflated compositional data, which are vectors of proportions constrained to the probability simplex, arise frequently in modern applications, such as microbiome relative abundances across body sites. While regression methods for zero-inflated compositional data are well developed, no existing graphical model framework addresses the problem of learning conditional dependence structures among multiple compositional vectors. This paper introduces a novel framework for directed tree structure learning over compositional nodes. We employ the Kullback–Leibler divergence as the scoring function and model the conditional expectation of each child composition as a mixture of a baseline composition and a parent-driven component parameterized by a column-stochastic transition matrix. This formulation respects the simplex geometry, handles zero-inflated compositions gracefully, and, combined with a non-degeneracy condition on the transition matrix, ensures identifiability of edge directions from observational data. We prove consistency of structure recovery and derive finite-sample guarantees that characterize the required sample size in terms of the signal gap, node dimension, and penalty level. The efficacy of our approach is demonstrated through simulations and applications to multi-site microbiome data and single-cell data, yielding interpretable directed structures that partially align with known biological mechanisms.
Other Events in This Series
Sep
5
2025
SDS Seminar Series – Sarah Coleman, University of Texas at Austin
A Linear Mixed Effects Model for Evaluating Synthetic Gene Circuits
2:00 pm – 3:00 pm • In Person
Speaker(s): Sarah Coleman
Sep
12
2025
SDS Seminar Series – Lydia Lucchesi, University of Texas at Austin
Visual Documentation for Data Preprocessing in R and Python
2:00 pm – 3:00 pm • In Person
Speaker(s): Lydia Lucchesi
Sep
19
2025
SDS Seminar Series – Tuan Pham, University of Texas at Austin
Time-uniform Bounds for Iterated Algorithms
2:00 pm – 3:00 pm • In Person
Speaker(s): Tuan Pham
Sep
26
2025
SDS Seminar Series - Ryan Giordano, University of California, Berkeley
Local Weighting--Based Diagnostics for Bayesian Multilevel Regression with Poststratification
2:00 pm – 3:00 pm • In Person
Speaker(s): Ryan Giordano
Oct
3
2025
SDS Seminar Series – Rafael Campello de Alcantara, University of Texas at Austin
Searching for Parallel Trends: A Decision Tree Algorithm for Discovering Conditional Diff-in-Diff Estimators
2:00 pm – 3:00 pm • In Person
Speaker(s): Rafael Campello de Alcantara
Oct
10
2025
SDS Seminar Series – Michele Guindani, University of California, Los Angeles
Embracing Heterogeneity: Bayesian Clustering Methods for Neuroscience Data
2:00 pm – 3:00 pm • In Person
Speaker(s): Michele Guindani
Oct
17
2025
SDS Seminar Series – Wenyi Wang, MD Anderson Cancer Center
Deciphering Tumor Heterogeneity for Benefits from Immunotherapy in Cancer
2:00 pm – 3:00 pm • In Person
Speaker(s): Wenyi Wang
Oct
24
2025
SDS Seminar Series - Jonathan Huggins, Boston University
Robust Model Selection for Discovery of Latent Mechanistic Processes
2:00 pm – 3:00 pm • In Person
Speaker(s): Jonathan Huggins
Oct
31
2025
SDS Seminar Series – Max Goplerud, University of Texas at Austin
Generalized Bilinear Mixed Models and Variational Inference
2:00 pm – 3:00 pm • In Person
Speaker(s): Max Goplerud
Nov
7
2025
SDS Seminar Series – Jeffrey Miller, Harvard University
Bayesian Model Criticism Using Uniform Parametrization Checks
2:00 pm – 3:00 pm • In Person
Speaker(s): Jeffrey Miller
