果冻传媒麻豆社

The problem of estimating latent or hidden states of a dynamical system from noisy observed data often arises in many branches of science, including navigation, weather prediction and mathematical finance.  ‘Filtering’ refers to any method for obtaining such state estimates, recursively in time, by combining model predictions with noisy observations. Filtering theory is one of the hidden cornerstones of modern life; most weather prediction, on-board aircraft guidance and GPS based navigation are based on a variety of filtering algorithms. Prof Date has been working in filtering and its diverse applications for the past two decades. The inaugural lecture will outline some of his significant contributions related to filtering and prediction in dynamical systems, delving into fascinating applications in accurate forecasting of financial variables such as interest rates and commodity prices. Prof Date will also reflect on his journey, from a provincial college in India, through his scholarship-funded doctoral studies in engineering at the University of Cambridge to his current position at Brunel.

"Hybrid Event: Free of charge and open for all"