StatSci Research Alumni Symposium

A Posteriori Celebration of Statistical Science on Duke Centennial

As part of Duke Centennial events, the Department of Statistical Science is hosting a doctoral and postdoctoral research alumni symposium from Oct 31 through Nov 2 to celebrate the department’s rich history and contributions to the field of statistics, the university, and the society.

The event will feature talks and panels from doctoral and postdoctoral alumni, research posters by current PhD students and postdocs, remarks by faculty, and a banquet dinner on Friday, November 1. Saturday, November 2 will feature events celebrating Mike West on becoming a professor emeritus, to be continued to the department’s Halloween party the same evening.

Register now

Confirmed Speakers

Omar Aguilar (Schwab)
Lindsay Berry (Berry Consultants)
Fan Bu (University of Michigan)
Carlos Carvalho (University of Texas, Austin)
Yang Chen (BlackRock)
Lorin Crawford (Microsoft Research)
Federico Ferrari (Merck)
Marco Ferreira (Virginia Tech)
Lutz Gruber (QuantCo)
Mengyang Gu (University of California, Santa Barbara)
Monika Hu (Vassar College)
Gabriel Huerta (Sandia National Laboratory)
Didong Li (University of North Carolina, Chapel Hill)
Lizhen Lin (University of Maryland)
Hedibert Lopes (Insper Institute of Education and Research)
Joe Lucas (Ab Initio)
Ken McAlinn (Temple University)
Kelly Moran (Los Alamos National Laboratory)
XuanLong Nguyen (University of Michigan)
Jarad Niemi (Iowa State University)
Natesh Pillai (LinkedIn/Harvard University)
Abel Rodriguez (University of Washington)
Yajuan Si (University of Michigan) 
Graham Tierney (Netflix)

Poster Presenters

1. Davide Agnoletto: Nonparametric Predictive Inference for Discrete Data via Metropolis-Adjusted Dirichlet Sequences
2. Yunran Chen: Block Covariance Matrix Estimation
3. Alex Dombowsky: Graphical Modeling of Categorical Data via Hierarchical Dirichlet Priors
4. Kat Husar: Rerandomization and Regression Adjustment in Studies with Missing Values in Pre-Treatment Covariates
5. Jennifer Kampe: Nested Exemplar Latent Space Models for Dimension Reduction in Dynamic Networks
6. Bokgyeong Kang: Joint Spatiotemporal Modeling of Zooplankton and Whale Populations in a Dynamic Marine Environment
7. Zeki Kazan: Prioritizing Privacy – A Bayesian Approach to Setting the Privacy Budget in Differential Privacy
8. Hwanwoo Kim: Bayesian Optimization with Noise-Free Observations: Improved Regret Bounds via Random Exploration
9. Cathy Lee: Sharp Bounding Causal Estimands for Ordinal Outcome Experiments
10. Changwoo Lee: Logistic-Beta Processes for Dependent Random Probabilities with Beta Marginals
11. Aihua Li: A Bayesian Decision-Theoretic Approach to Sparse Estimation
12. Nicholas Marco: Modeling Neural Switching via Drift-Diffusion Models
13. Lorenzo Mauri: Latent Factor Pre-Training with Signal Reinforcement: Resolving Computational and Identifiability Challenges in Bayesian Multi-Study Factor Models
14. Glenn Palmer: Low-Rank Longitudinal Factor Regression
15. Rick Presman: Non-Euclidean Bayesian Constraint Relaxation via Divergence-to-Set Priors
16. Suchismita Roy: SIR Models under Missing Data – Marginal Likelihoods and Dynamical Survival Analysis 
17. Christine Shen: Bayesian Model Evaluation with p-values
18. Federica Stolf: Infinite Joint Species Distribution Models
19. Bongjung Sung: Testing Separability of Covariance Matrices in High-Dimensional Settings
20. Luke Vrotsos: Dynamic Graphical Models: Theory, Structure, and Counterfactual Forecasting
21. Houjie Wang: Likelihood-based Inference on Partially Observed Epidemics and Network Dynamics
22. Ganchao Wei: Stream-level Flow Matching from A Bayesian Decision Theoretic Perspective

23. Yuliang Xu: Bayesian Structured Mediation Analysis with Unobserved Confounders

    
    This event is invitation-only due to limited seating capacity. Those interested in attending can contact Karen Whitesell (karen.whitesell@duke.edu) for more information.