New for 2026:

Hands-On Analytics Training Workshops

Tuesday, April 14th
2:30pm – 4:30pm EST

You asked. We listened.

In 2026, we’re going deeper with interactive training workshops designed to turn analytics concepts into real-world impact.

These sessions go beyond theory, giving you practical tools, expert insights, and immediately usable takeaways.

With sessions designed for a range of experience levels, this workshop series offers something for everyone.

Sample workshop topics include:

The INFORMS Analytics Framework in Action – Discover how problem business and analytics problem statements evolve across domains in real scenarios

Generative AI in Analytics – Bringing analysts, subject matter experts, and decision-makers together to build stronger analytical teams

AI & Ethics – Navigating responsibility, trust, and transparency in AI-driven work

The Analyst’s View – explore how the INFORMS Analytics Framework can drive real-world impact across sectors
Hosted by WINFORMS – INFORMS Washington DC Chapter

Using the INFORMS Analytics Framework in Hiring – Smarter hiring for analytics success

Graphical Processing Units (GPU) for Industrial Strength Optimization – the ongoing evolution of Mixed Integer Linear Programming (MILP) and new advances in optimization which make much larger models still solvable

Bonus:

All participants will receive a Certificate of Completion at the end of each workshop—perfect for sharing with your boss or supervisor as proof of skills gained and value delivered.

All workshops are included with your conference registration.

Upgrade your conference experience.

Leave with knowledge you can use on Wednesday.

Louis Luangkesorn

Using Generative AI in Analytics: bringing analysts, subject matter experts, and decision makers into a better analytical team

Abstract:

Generative AI promises to transform the practice of analytics, however, the foundation models, trained on readily available data, fails in situations that experts would recognize but novices would not. In analytics projects where context and nuance are important this leads to faulty analysis and failed projects. This workshop will demonstrate using Generative AI through the steps of the INFORMS Analytics Framework, with special attention to enabling good communication between the analyst, subject matter experts, and decision makers who will use analytical products. Specifically, Generative AI will be used to enable clear communications between stakeholders and analysts. It will use project artifacts such as Product Requirements Documents, mathematical formulations, and implemented models to enable all stakeholders to verify that analytical products meet project requirements. Finally, use Generative AI to present results for a range of different stakeholders. The workshop will be done using Gemini NotebookLM, but can be followed using any Generative AI persistent workspace tool (e.g. Gemini NotebookLM, Gems, Claude Projects, OpenAI Custom GPTs, or Copilot Agents) or terminal based tools (e.g. Gemini CLI, Claude Code, or OpenAI Codex). While the workshop will implement models as project artifacts, Generative AI will be used to translate back and forth to domain language so programming and modeling knowledge is not necessary.

Bio

Dr. Luangkesorn is a Lead Data Scientist on the Highmark Health People Analytics Team where he works on projects applying statistical, predictive, operations research, and Generative AI models in use cases involving human resources and healthcare. He has a volunteer role as a National Planner for the American Red Cross, where he develops and uses analytical tools to create rapid estimates of disaster needs as part of a major disaster response. Prior to working at Highmark Health he was an Assistant Professor of Industrial Engineering at the University of Pittsburgh. In this role he worked with industry partners including over 20+ industry based capstone projects per year for the department of Industrial Engineering and the Health Systems Engineering program at the University of Pittsburgh Graduate School of Public Health. He is the author of the Data Science chapter of the book Health Informatics: an Interprofessional Approach. He is a Senior Member of INFORMS, currently on the INFORMS Practice Strategy Committee, and President of the INFORMS Pittsburgh Chapter.