Today I have the pleasure of welcoming back to Resoundingly Human long-time INFORMS member Jim Cochran, professor with the University of Alabama’s Culverhouse College of Business. In addition, I’m joined by Ryan McNeill, deputy editor for the Reuters global data journalism team.

Jim and Ryan are members of an investigative team that was recognized with the 2024 Scripps Howard Award for Excellence in Multimedia Journalism for their work on The Bat Lands, a groundbreaking science series exploring the origins and potential outbreak sites of bat-borne viruses.

Welcome to the latest episode of Resoundingly Human, the podcast brought to you by INFORMS, the leading association for professionals and students who apply science, math, technology and analytics to make smarter decisions for a better world. I’m your host, Ashley K. and thank you for joining me to explore how INFORMS members are saving lives, saving money and solving problems.

I’m pleased to introduce Tom Stephenson, director of services and strategic partnerships at Simul8 Corporation, who joins me today to take a look at how simulation is being leveraged to help to improve healthcare outcomes in a wide variety of applications.

We’re continuing our countdown to the 2024 INFORMS Annual Meeting, in Seattle, Washington, October 20-23, when more than 6,000 INFORMS members, students, prospective employers and employees, and academic and industry experts will share the ways O.R. and analytics are fueling Smarter Decisions for a Better World.

In this episode, I’m joined by Cynthia Rudin, with Duke University, Charles Isbell, with the University of Wisconsin, and Michel Littman, with the National Science Foundation, for a preview of their plenary session, “Making the Most of this AI Moment: A Fireside Chat.”

Charles serves as the provost and vice chancellor for academic affairs with the UW-Madison, and Michael is the division director for information and intelligent systems at NSF.

Cynthia, the session moderator, is a longtime INFORMS member and the Gilbert, Louis, and Edward Lehrman Distinguished Professor of Computer Science at Duke University, as well as heads the Interpretable Machine Learning Lab.