Thursday, 30 July 2026, 15:00 at Centre for Mathematical Sciences, MR14 – A core challenge in scientific machine learning is how to learn from limited, noisy, or strategically chosen data. This talk presents the mathematics of sparse sensing—the problem of choosing maximally informative measurements for high-dimensional estimation and control. Sensor placement defines a highly nonconvex optimization landscape and, in general, is NP-hard. …