Schedule

8:30 — 9:10

Registration and coffee

–

9:10 — 9:30

Welcome and opening

–

9:30 — 10:15

Shubhada Agrawal

Concentration of Stochastic Approximation Under Markovian Noise

10:15 — 11:00

Patrick Rebeschini

Optimal Sequential Inference and Decision Making: From Uniform A/B Testing to Gradient-Based Bandits

11:00 — 11:30

Break

–

11:30 — 12:15

Alessandro Arlotto

Ballot design and electoral outcomes: The role of candidate order and party affiliation

12:15 — 14:00

Lunch

–

14:00 — 14:45

Sandeep Juneja

Generating Samples from Exponentially Tilted Distributions via Diffusions

14:45 — 15:30

Yilun Chen

The Side Effects of Adaptive Learning Algorithms

15:30 — 16:00

Break

–

16:00 — 16:45

Liron Ravner

Stochastic Approximation Algorithms for Regulating Queues with Strategic Customers

16:45 — 17:30

Yunbei Xu

Finite-Time Information-Theoretic Bounds in Queueing Control

9:30 — 10:15

Michel Mandjes

Inference problems in stochastic networks

10:15 — 11:00

Nian Si

Evaluation of Queueing Scheduling and LLM Inference via Stability Conditions and A/B Tests

10:30 — 11:00

Break

–

11:30 — 12:15

John J. Hasenbein

Belief-driven Strategic Queueing Models

12:15 — 14:00

Lunch

–

14:00 — 14:45

Lucy Huo

Exploring the Operational Potential of Queue-Ratio Policies in Multiclass Queueing Networks

14:45 — 15:30

Weiliang Liu

Data-Driven Matching for Impatient and Heterogeneous Demand and Supply

15:30 — 16:00

Break

–

16:00 — 16:45

Galit Yom-Tov

Optimizing Visitor Load at National Parks: Balancing Accessibility and Overcrowding through Online Reservation Systems

16:45 — 17:30

Xuefeng Gao

Reward-Directed Diffusion Models via Continuous-Time Reinforcement Learning

9:00 — 9:45

Cynthia Rush

The Out-of-sample Rrediction Error of the Square-root Lasso and Related Estimators

9:45 — 10:30

Andrew Daw

Stopping Self-Excitement

10:30 — 11:00

Break

–

11:00 — 11:45

Guiyu Hong

Learning When to Surge: Online Queue-based Pricing for Delay-sensitive Customers