IPAM (pictured here in a photo I took today), as one of the six NSF-funded math institutes, has been a great success since its founding in 2000. Its specialty is creating three-month programs where participants (both junior and senior) from two or more fields of mathematics, science, or industry interact through workshops, participant-driven seminars, and informal interactions, centered around a theme that had been identified as particularly fertile for bringing together two or more otherwise disparate communities.

One well-known example that I was involved many years ago was the 2004 program https://www.ipam.ucla.edu/programs/long-programs/multiscale-geometry-and-analysis-in-high-dimensions/ on Multiscale geometry and analysis in high dimensions, where the organizers had identified the potential for bringing together pure mathematicians whose work involved geometry at multiple scales with scientists interested in such applied topics as signal processing or the accurate modeling of materials. I participated extensively in this program, and in particular interacted quite a bit with one of the organizers (Emmanuel Candes) as well as Justin Romberg, leading to several foundational papers in the field now known as "compressed sensing", which permits (in certain circumstances) the rapid acquisition of high-resolution images or other information from a relatively small number of measurements. (Perhaps the most well known applications of the compressed sensing algorithms that came out of the work of Emmanuel, myself, Justin, David Donoho, and others was the ability to speed up the time required for a medical-grade MRI scan by up to an order of magnitude.) (2/4)

Some accounts claim that Emmanuel and I actually started collaborating at the preschool that both of our children attended at the time, but the truth is that our main collaboration actually started at IPAM; the fact that we met on a near-daily basis at the preschool was very useful to continue the collaboration, but it was not exactly an ideal environment to initiate it.

I have been involved in several other very interesting IPAM programs since then; for instance, in 2023 I was the lead organizer in an IPAM-hosted workshop on Machine Assisted Proof https://www.ipam.ucla.edu/programs/workshops/machine-assisted-proofs/, which turned out to be a very well-timed event (occurring a few months after the launch of ChatGPT, for instance), bringing together pure mathematicians, computer scientists, and several people from industry and opening important channels of communication between researchers in such topics as proof formalization, machine learning, large language models, computer algebra solvers, and satisfiability solvers. (I previously posted on my experiences at that workshop at https://mathstodon.xyz/@tao/109858184238417737 .) My experiences at that workshop, as well as the connections made, permitted me to get up to speed on the latest developments in all of these areas, which now encompass a large portion of my current research interests. (3/4)