Resoundingly Human

When we hear the word "optimization," we tend to think about finding the best possible solution to a problem. But when those problems involve schools, communities, limited resources and competing priorities, defining what "best" actually means can become much more complicated.
In this episode of Resoundingly Human: The INFORMS Podcast, Karen Smilowitz, Associate Provost and professor at Northwestern University with a joint appointment in the operations group at the Kellogg School of Management, and a plenary speaker at the 2026 INFORMS Annual Meeting, shares how operations research can be used to tackle complex problems with very real human consequences in education, humanitarian, and nonprofit applications.

Computers keep getting faster. But sometimes, taking full advantage of new computing power requires more than simply speeding up the way we've always done things. It requires rethinking the way we solve problems altogether.
Welcome to Resoundingly Human: The INFORMS Podcast where we share how operations research, analytics, data science, and AI are helping us better understand – and improve – the world around us.
Today's guest has spent his career exploring how we can solve some of the most complex optimization problems more effectively.
A professor at the Jacobs Technion-Cornell Institute at Cornell Tech, Andrea Lodi will be joining us in San Francisco as a plenary speaker at the 2026 INFORMS Annual Meeting, where he'll explore how GPUs could change not just the speed of Mixed-Integer Optimization, but potentially the algorithms themselves.

Artificial intelligence has become one of the defining technologies of our time. But what if the way we're thinking about AI – starting with the very idea of "intelligence" – is too narrow?
Welcome to Resoundingly Human: The INFORMS Podcast about how operations research, analytics, data science, and AI are helping us better understand – and improve – the world around us.
Today's guest has spent decades helping shape our understanding of machine learning and its connections to statistics, computation, cognition and decision-making.
Michael Jordan is a researcher at Inria Paris and Professor Emeritus at the University of California, Berkeley and will be joining us in San Francisco as the opening plenary speaker at the 2026 INFORMS Annual Meeting, where he'll present "A Collectivist, Economic Perspective on AI."

If you've ever visited a hospital emergency department, chances are you've experienced one of its most persistent challenges: waiting.
For hospitals, reducing those wait times can seem like a capacity problem. More patients require more beds, more staff or more space, right?
But what if one of the solutions is simply making better decisions about how the resources already available are used?
Joining me today is Agni Orfanoudaki, Oxford University, to share new research on a data-driven approach to determining which patients actually need a traditional emergency department bed and who can be treated in alternate locations. Ultimately, this reduced emergency room stays by 11 minutes, all without adding staff, beds or technology, and without compromising patient safety.

Organizations have more data, more dashboards, and more sophisticated analytics tools than ever before. And yet, many still struggle to make confident decisions quickly.
Sometimes the problem isn't the data itself. It's what happens between the insight and the action: unclear ownership, competing versions of the truth, slow review cycles, and analytics that sit beside the business instead of helping shape it.
In today's episode of Resoundingly Human: The INFORMS Podcast, I'm joined by Ritish Chugh, Senior Analytics Engineer with Airbnb, to talk about what it takes to move from producing analytics to building an organization that actually knows how to use it.