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All events will take place at the Carolina Club (150 Stadium Dr, Chapel Hill, NC 27514)

Sunday September 17

5:30pm to 7:30pmMixer and registration

Monday September 18

8:00am to 9:00amBreakfast and registration
9:00am to 9:45amOpening remarks
Vladas Pipiras (STOR Chair)
Doug Kelly (STOR Professor Emeritus)
Jim White (CAS Dean)
Marie Davidian (ASA)
Radhika Kulkarni (INFORMS)
9:45am to 10:45amSusan Murphy (Harvard University)
“Dyadic Reinforcement Learning”
Chair: Runze Li (Pennsylvania State University)
10:45am to 11:00amCoffee break
11:00am to 12:00pmRenato Monteiro (Georgia Tech)
“Complexity of proximal augmented Lagrangian methods
and ADMM for solving constrained smooth nonconvex
composite optimization problems”
Chair: Chihoon Lee (Stevens Institute of Technology)
12:00pm to 2:00pmLunch and posters
2:00pm to 2:15pmAfternoon remarks
Michael Kosorok (IMS)
2:15pm to 3:15pmVictor Perez Abreu (CIMAT)
“Random matrix theory and relationships with some
interests from the 75 years of the STOR community”
Chair: Haonan Wang (Colorado State University)
3:15pm to 3:30pmCoffee break
3:30pm to 5:00pmPanel “STOR in Industry: Current Perspectives”
5:00pm to 6:30pmBreak
6:30pm to 9:00pmBanquet
Robert Lund (UCSC)
“Things my Chapel Hill doctorate did not teach me
about an academic life”

Tuesday September 19

8:00am to 9:00amBreakfast
9:00am to 10:00amShane Henderson (Cornell University)
“Stochastic Modeling: Some STORies”
Chair: Barbara Hoopes (Virginia Tech)
10:00am to 10:15amCoffee break
10:15am to 11:45amSpotlight talks
11:45am to 1:30pmLunch and posters
1:30pm to 3:00pmPanel “STOR in Industry: Postcards from the Future”
3:00pm to 3:15pmClosing remarks
Kai Zhang (Organizing committee chair)
3:15pm to 5:00pmCareer expo and ice cream social


Dyadic Reinforcement Learning
Sequential decision making in digital health aims to enhance health outcomes by delivering interventions to individuals as they go about their daily life. The involvement of care partners and social support networks often proves crucial in helping individuals manage burdensome medical conditions. This presents opportunities in digital health to design interventions that target the dyadic relationship—the relationship between a target person and their care partner—with the aim of enhancing social support. In this paper, we develop dyadic RL, an online reinforcement learning algorithm designed to personalize intervention delivery based on contextual factors and past responses of a target person and their care partner. Here, multiple sets of interventions impact the dyad across multiple time intervals. We formally introduce the problem setup, develop dyadic RL and establish a regret bound. We demonstrate dyadic RL’s empirical performance through simulation studies on both toy scenarios and on a realistic test bed constructed from data collected in a mobile health study.

Complexity of proximal augmented Lagrangian methods and ADMM for solving constrained smooth nonconvex composite optimization problems
This talk discusses proximal augmented Lagrangian (PAL) methods and variants of the alternating minimization method of multipliers (ADMM) for solving constrained smooth non-convex composite optimization problems. Its purpose is to survey latest development and present our latest results related to the above topic. Special attention will be given to adaptive methods which do not require any specific knowledge about the problem instances (e.g., Lipschitz constants or lower curvature parameters for the objective and constraints functions) and hence are easy to run. We will also present numerical results demonstrating the significantly superior performance of adaptive methods compared to its non-adaptive versions. (joint work with William Kong and Arnesh Sujanani).

Random matrix theory and relationships with some interests from the 75 years of the STOR community
We will take a tour of some pioneering breakthroughs in the theory of random matrices and point out connections to some areas of interest of the STOR community at some point in its 75 years, such as statistical communication theory, extreme values, stochastic simulation, and complex data, among others.

Stochastic Modeling: Some STORies
I’ll present two war stories and, if time, describe some current work from my own experience, emphasizing themes and principles embodied by the stochastic modeling faculty in STOR at UNC. The first war story involves a court case on ambulance deployment. The second war story involves our (mostly) successful efforts to keep Cornell open for in-person instruction throughout the COVID 19 epidemic. The current work involves the design of volunteer schemes to decrease response times to the most urgent calls for medical assistance.
This is joint work with too many co-authors to list here.

Industry Panelists

Current Perspectives

  • Guilaume Bonnet (Google)
  • Bryan Davis (Centari)
  • Mike Hoekstra (CDC)
  • Stefanos Kechagias (SAS)
  • Radhika Kulkarni (SAS)
  • Duyeol Lee (Wells Fargo)

Postcards from the Future

  • Yunxiao Liu (Reddit)
  • Nick Locantore (NIMIRGA)
  • Glenn Sabin (ZS Associates)
  • Michele Trovero (SAS)
  • Diane Wold (CDISC)

Spotlight talks

  • Gabor Pataki (UNC Chapel Hill)
    How do exponential size solutions arise in Semidefinite Programming?
  • Mohammad R. Jahan-Parvar (Federal Reserve)
    Bayesian trend-cycle decomposition and forecasting
  • Daniel Kessler (University of Michigan)
    Matrix-Variate Canonical Correlation Analysis
  • Bala Krishnamoorthy (Washington State University)
    Median Shapes and Linear Programming
  • Ankur Patel (John Hopkins University)
    Comparison of neural networks and traditional regression methods for estimating kidney function in children with chronic kidney disease
  • Xingye Qiao (Binghamton University)
    On Set-valued Classification
  • Yuying Xie (Michigan State University)
    Foundation Models in Single-cell Data Analyses: Challenges and Opportunities
  • Lingsong Zhang (Purdue University)
    Some thoughts on precision medicine and causality

Companies at the career expo

  • Amazon
  • Demand Side Analytics
  • Discovery ABA
  • Drakeford, Scott & Assoc.
  • Enact
  • Institute for Advanced Analytics (NC State)
  • Nicholas School of the Environment (Duke)
  • Pro Financial Fitness
  • SAS
  • Siemens
  • UCB
  • United States Marine Corps
  • YMCA
  • ZS Associates