[Call for Abstracts] INFORMS Regional Analytics Conference SF Bay Area 2026


Convergence 2026: AI Meets Decision Intelligence
How AI and optimization are transforming decision-making at scale

As artificial intelligence moves from experimentation to enterprise deployment, the critical question is no longer just what AI can predict, but how decisions are made and executed at scale. Convergence 2026 explores the evolving intersection of AI, spanning agentic and generative systems to forecasting and machine learning, with decision intelligence grounded in optimization and operations research.
This conference brings together industry leaders, researchers, and practitioners to examine how AI and optimization are converging to power real-world decision systems. From agentic workflows and autonomous decision loops to large-scale forecasting, optimization, and compute efficiency, we will explore what is working, what is not, and what lies ahead.
We are now accepting submissions for contributed talks. We invite submissions from researchers, practitioners, and students affiliated with academia, industry, or national laboratories. Entries may be submitted individually or by groups of up to three presenters. (The works can have any number of authors.) Preference will be given to submissions from the SF Bay Area and California.

Topics of Interest
We invite abstract submissions that highlight innovative work or practical case studies on (but, of course, not limited to) the following topics:
Agentic AI & Autonomous Systems: Development of agentic systems, decision orchestration, and evaluation of autonomous decision systems in production.
Generative AI Meets Optimization: Integrating Large Language Models (LLMs) and generative AI with mathematical optimization and traditional operations research methodologies.
Forecasting & Optimization: End-to-end architectures that successfully bridge large-scale predictive machine learning with optimization.
Scaling & Efficiency: Operations research applications in systems optimization, High-Performance Computing (HPC), and efficient training for scaling AI-driven decision systems.
Real-World Deployment Case Studies: Industry case studies highlighting what succeeds and what fails in practice, and strategies for bridging the gap between theoretical AI/OR and operational reality.
The Future of AI & Operations Research: Forward-looking research and applications that define the next generation of capabilities at the convergence of artificial intelligence and decision intelligence.


Presentation Format
Selected contributors will be invited to give a 15-minute in-person talk as part of the main program. We have ~5 slots available.

Important Dates
Submission Deadline: Aug 9, 2026
Notification of acceptance/rejection: Aug 17, 2026
Conference Date: Oct 2, 2026

How to Submit
Please submit a short abstract (max 1500 characters) summarizing your talk topic, its relevance to the theme, and any key take-aways. Include your name, affiliation, and a brief bio. Include bios of all speakers (for submissions with multiple presenters up to three).
Submit via: https://forms.gle/E35iXK9XiQxziQEL7

For questions, reach out to: zq2107@caa.columbia.edu