Organizing two sessions at JSM 2026 in Boston

Created on July 16, 2026

2026

I am organizing two sessions at the Joint Statistical Meetings (JSM) 2026 in Boston.

Dynamics at Scale: Statistical Frontiers in High-Dimensional and Streaming Time Series

📅 Monday, August 3, 2026, 8:30–10:20 AM
📍 Thomas M. Menino Convention & Exhibition Center, Room CC-253C
🔢 Session 1176 (Invited Paper Session)
🔗 Session details and abstracts

The session features five talks:

  • Jiayu Li (New York University) — Modewise Additive Factor Model for Matrix Time Series
  • David Matteson (Cornell University & NISS) — Network Modeling of Large-scale Time Series with Cumulative Impulse Response Functions
  • Xiaofeng Shao (Washington University in St. Louis) — Sequential Monitoring for Object-Valued Time Series
  • Likai Chen (Washington University in St. Louis) — Inference for High-Dimensional Data with Partially Missing Returns
  • Jonghyeok Lee (Georgia Tech) — Multi-Rank Subspace Change-Point Detection with Application in Monitoring Robotic Swarms

Frontiers in Generative AI, Time Series, and Probabilistic Deep Learning

📅 Thursday, August 6, 2026, 8:30–10:20 AM
📍 Thomas M. Menino Convention & Exhibition Center, Room CC-254A
🔢 Session 1715 (Topic-Contributed Paper Session)
🔗 Session details and abstracts

The session features five talks:

  • Ning Hao (University of Arizona) — When Dependence Meets Nonstationarity
  • Mengyang Gu (UC Santa Barbara) — GaussNet: A Gaussian Process Network Accelerated by the Inverse Kalman Filter
  • N. Benjamin Erichson (UC Berkeley) — Quantifying Epistemic Uncertainty in Diffusion Models for Time Series (joint work with Elynn Chen)
  • Ning Ning (Texas A&M University) — Robust Iterative Learning Hidden Quantum Markov Models
  • Timm Haucke (MIT) — Seeing Above and Below the Canopy: Modeling and Interpreting Species Occupancy with Deep Multi-modal Habitat Representations

If you are attending JSM, please join us!