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From 6pm and concluding by 7pm: Presentation on Zoom
Virtual pre-drinks and nibbles are provided, but they don't taste as good as the real thing!
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Speaker: Basim S.O. Alsaedi, formerly University of New England.
Topic: Bayesian Modelling of Non-Linear Sensor Arrays.
Abstract: Non-linear multivariate calibration methods are increasingly used to extract information from different types of sensors. As the complexity of the data increases, new methods are required to estimate parameters and to provide realistic estimates of uncertainty. This talk is focused on the study of establishing a meaningful limit of detection for sensors and sensor arrays with non-linear response. We propose a new limit of detection (LOD) definition for ion selective electrodes for sensors and sensor arrays. The Bayesian infostructure is used to calculate the uncertainty associated with the estimates. Furthermore, a comprehensive study of modularisation in sensors and sensor arrays is conducted, motivated by practical limitations of the “cut” function in Bayesian graphical models as implemented by BUGS. Alternative algorithms, based on Approximate Bayesian computation (ABC), for sensors and sensor arrays are also proposed and evaluated.
Biography: Dr Alsaedi recently graduated with a PhD in statistics from the School of Science and Technology at the University of New England. His PhD thesis was devoted to the study of non-linear multivariate Bayesian calibration i.e. Bayesian modelling for newly developed chemical sensors and sensor arrays. He is currently a lecturer in the department of statistics at the University of Tabuk, Saudi Arabia.
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