Workshops

Frontiers in Generative AI: Foundation and Algorithms

Short name: GenAI

Public date: Friday, June 12, 2026

Organizers: Yuxin Chen (UPenn), Laixi Shi (JHU), Yingying Li (UIUC)

A one-day workshop on recent advances in generative AI, spanning foundational and algorithmic questions as well as applications, with invited talks and networking-oriented discussion.

Workshop on Measurements, Modeling, and Metrics for Carbon-Aware Computing

Short name: CarbonMetrics

Public date: See workshop site

Organizers: Noman Bashir (AWS), Adam Lechowicz (UMass Amherst), Walid Hanafy (UMass Amherst), David Irwin (UMass Amherst), Prashant Shenoy (UMass Amherst)

CarbonMetrics focuses on rigorous measurement frameworks, modeling techniques, and metrics that help the systems community quantify and reduce the carbon footprint of computing.

Quantum Metrics and Performance Evaluation Workshop

Short name: QMETRICS

Public date: June 12, 2026

Organizers: Harsha Honnappa (Purdue University), Thiru Vasantam (Durham University), Guanyang Wang (Rutgers University), Neil Walton (Durham University)

QMETRICS is focused on performance evaluation methodologies for quantum computing, quantum communication, and quantum networking systems, including benchmarking, fidelity, latency, and resource estimation.

MAthematical performance Modeling and Analysis

Short name: MAMA

Public date: Friday, June 12, 2026

Contact: Mark S. Squillante (IBM Research)

MAMA continues the long-running SIGMETRICS workshop series on mathematical, methodological, and theoretical aspects of performance analysis, modeling, and optimization.

Causal Inference Workshop

Public date: Friday, June 12, 2026

Organizers: Devavrat Shah (MIT), Dennis Shen (USC)

This workshop brings together researchers working on causal inference across statistics, operations research, and engineering, with a mix of talks, poster presentations, and networking opportunities.

Frontiers in Stochastic Control and Reinforcement Learning

Short name: SC&RL

Public date: Friday, June 12, 2026

Organizers: Gauri Joshi (Carnegie Mellon University), Mehrdad Moharrami (University of Iowa), Srinivas Shakkottai (University of Texas A&M)

This workshop highlights recent progress in stochastic control and reinforcement learning, with emphasis on theory, scalable methods, robustness, and systems-facing applications.

Learning-augmented Algorithms: Theory and Applications

Short name: LATA

Public date: See workshop site

Organizers: Nicolas Christianson (Stanford University and Johns Hopkins University), Adam Lechowicz (UMass Amherst), Xuchuang Wang (UMass Amherst), Bo Sun (University of Ottawa)

LATA covers recent advances in learning-augmented algorithms, including algorithm design with predictions, provable robustness, and applications to computing systems, networks, and optimization.