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Department of Statistics

Departmental Representation at JSM 2024

July 23, 2024

The Joint Statistical Meetings (JSM) 2024 was a great success in Portland, Oregon. Bringing together over 5,000 attendees from 52 countries, JSM is one of the largest statistical events in the world, hosting more than 600 sessions that showcase groundbreaking work in the field from professionals in academia, government, and industry.

For our department, participation in JSM 2024 underscores our commitment to contributing to the global conversation on statistics. We had roughly 46 members of our department contribute and participate in this year’s conference. Dr. Emily Hector served on the JSM Program Committee as one of two representatives for the Institute of Mathematical Statistics. Further, our faculty, students, and collaborators were well-represented across a wide range of sessions, from causal inference to environmental statistics, deep learning, and health disparities. Their contributions reflect the breadth and depth of our expertise.

In addition to our active participation in the sessions, the department also hosted our annual Alumni and Friends Reception on the evening of August 6, 2024, which was a highlight of the conference. This event brought together over 80 attendees, including alumni, faculty, students, and colleagues from across the globe. It was an evening filled with lively conversation, offering opportunities to reconnect with old friends and make new connections, all while enjoying great food and drinks. The warm and informal atmosphere allowed for meaningful networking, fostering both personal and professional relationships within our vibrant community.

See below for a detailed listing of our department’s involvement in this year’s conference and click here to enjoy photos highlighting departmental activity and engagement during this year’s conference.

Sunday August 4, 2024

Chenyin Gao-Chair

Emmett Kendall – Chair, Brian Reich – Organizer

Jonathan Williams (speaker) Model-free generalized fiducial inference for empirical risk minimizers

  1. Wenbin Lu co-author of A Landmark Competing Risk Model for Dynamic Prediction
  2. Jake Koerner (first/presenting author), Ana-Maria Staicu and William Rand (co-authors) of Are Users Susceptible to Interaction with an Automated Account Different From Those That Do Not?

Reetam Majumder – Chair

Emily Hector (speaker) New Methods For Analyzing Wearable Device Data

Sarah Fairfax (first/presenting author) Shu Yang (co-author) – Distributional Imputation for Control-Based Sensitivity Analyses of Recurrent Events Data

Xiaodan Zhou (presenting/first author) Brian Reich and Shu Yang (co-authors) Long-term Effect of Redlining Policy on Air Pollution Exposure

Srijan Sengupta (speaker) Anomalous clique detection and localization in inhomogeneous networks

Emily Hector (speaker) 09 Distributed model building and recursive integration for big spatial data modeling

Monday August 5, 2024

Annie Booth – presenting co-author of paper titled: Emulating Functional Output of Dark Matter Power Spectra Using Deep Gaussian Processes

Shu Yang – Chair

Peter Norwood (first/presenting author) Marie Davidian and Anastasios Tsiatis (co-authors) Bayesian Adaptive Randomization for the I-SPY 2 SMART

Xiaoxia Champon (co-author) Advances in Statistical Causal Inference and Applications

Justin Post (speaker) Using Generative AI to Supplement Learning in Statistical Programming Courses

Brian Reich – Chair/Organizer, Reetam Majumder – Organizer

Reetam Majumder (speaker) Vecchia-approximated Density Regression for Intractable Likelihoods Using Graph Neural Networks

Kim Sellers (co-author) Bayesian Generalized Linear Model for Difference of Over or Under Dispersed Counts

Tuesday August 6, 2024

  1. Sukanya Bhattacharyya (first/presenting author), Ana-Maria Staicu and Brian Reich (co-authors) Exploring spatiotemporal trends in air pollutants with Quantile Regression
  2. Dongjae Son (first/presenting author),  Erin Schliep and Brian Reich (co-authors) Spatial causal inference in the presence of sampling bias

Justin Post and Sunghwan Byun (co-authors) Authentic Data Explorations: Investigating the Normal Distribution through Comparative Rent Data

Jason Osborne (first/presenting author) Regression models for estimation of park effects in Major League Baseball

Charles Smith (presenting author) 20 Smartphone usage during walking decreases the positive persistency in gait cycle variability

Chenyin Gao (first/presenting author), Shu Yang (co-author) Causal Inference on Sequential Treatments via Tensor Completion

Brandon Feng (presenting author), Eric Yanchenko and Brian Reich (co-authors) 14 The R2D2 selection prior for survival regression 

Nate Wiecha (presenting author),  Brian Reich (co-author) 46 Two-stage spatial regression models for spatial confounding

  1. Emily Hector (co-author) 49 Bayesian factor analysis for multi-trait fine-mapping of pleiotropic genetic variants
  2. Wenbin Lu and Jung-Ying Tzeng (co-authors) 53 Estimating association of CNVs using penalized regression with Lasso and weighted fusion penalties

Jonathan Stallrich (speaker) An Optimal Design Framework for Lasso Sign Recovery

Brian Reich (speaker) Spatial Causal Inference with Preferential Sampling

Erin Schliep Organizer, speaker – Spatio-temporal model to quantify seasonal changes in streamflow across the northeast United States

Yi Liu (first author) Multi-Source Conformal Inference Under Distribution Shift

Erin Schliep (co-author) Analyzing whale calling through Hawkes process modeling

Annie Booth (speaker) Deep Gaussian Process Surrogates – Big and Small

Wednesday August 7, 2024

Srijan Sengupta (co-author) Efficient Two-Sample Hypothesis Testing for Large Networks : a Nonparametric Approach

Alvin Sheng (first/presenting author) Ana-Maria Staicu and Brian Reich (co-authors) A Two-Stage Approach for Segmenting Spatial Point Patterns Applied to Tumor Immunology

Herle McGowan Panelist

Ruonan Li Panelist

Donald Martin (first author) Efficient inference for start-up demonstration tests

Annie Booth (co-author) 62 Deep Gaussian Processes for Uncertainty Quantification in Large-Data Classification Settings

Emily Griffith panelist

  1. Neil Dey (first/presenting author) Ryan Martin and Jonathan Williams (co-authors) 61 Anytime-Valid Generalized Universal Inference on Risk Minimizers
  2. Annie Booth (co-author) 62 Deep Gaussian Processes for Uncertainty Quantification in Large-Data Classification Settings

Srijan Sengupta Chair

Subhashis Ghoshal Chair

  1. Matthew Shisler (first/presenting author) Erin Schliep and Brian Reich (co-authors) Bayesian Hierarchical Modeling for Spatiotemporal Analysis of Plant Phenology
  2. Wenlong Gong (first/presenting author) Brian Reich (co-author) Non-stationary spatial model with transfer learning in air pollution data

Sunghwan Byun (speaker and co-author) Justin Post (co-author) GTAs’ Problems of Practice for Teaching Introductory Statistic Courses

Wenbin Lu (speaker) Off-policy Evaluation with Irregular, Outcome-dependent Observation Process

Thursday August 8, 2024

Donald Martin (presenting/first author) Efficient computation of pattern statistics for many different input probabilities

Jonathan Williams Chair

Kimberly Sellers (presenting co-author) The Influence of Prior Distributions in Modeling Conway-Maxwell-Poisson Data

Shu Yang (speaker) Mitigating Bias in Treatment Effect Estimation: Strategies for Utilizing External Controls in Randomized Trials

Xiaoxia Champon (presenting/first author) Leonard Stefanski, Ana-Maria Staicu, and William Rand (co-authors) Clustering X Users based on Changes in Sentiment in Response to Conflict