Academic Keynote Speaker

René Vidal, Johns Hopkins Mathematical Institute for Data Science

Title and Abstract:

Semantic Information Pursuit

In 1948, Shannon published a famous paper, which laid the foundations of information theory and led to a revolution in communication technologies. Critical to Shannon’s ideas was the notion that a signal can be represented in terms of “bits,” and that the information content of the signal can be measured by the minimum expected number of bits. However, while such a notion of information is well suited for tasks such as signal compression and reconstruction, it is not directly applicable to audio-visual scene interpretation tasks, because bits do not depend on the “semantic content” of the signal, such as words in a document, or objects in an image. In this talk, I will present a new measure of semantic information content called “semantic entropy”, which is defined as the minimum expected number of semantic queries about the data whose answers are sufficient for solving a given task (e.g., classification). I will also present an information-theoretic framework called ``information pursuit'' for deciding which queries to ask and in which order, which requires a probabilistic generative model relating data and questions to the task. Experiments on handwritten digit classification show, for example, that the translated MNIST dataset is harder to classify than the MNIST dataset. Joint work with Aditya Chattopadhyay, Benjamin Haeffele and Donald Geman.


Defence Keynote Speaker

Hugh Griffiths – Defence Science Expert Committee (DSEC) / University College London

Title and Abstract:

To follow


Invited Speakers

Mark Briers, The Alan Turing Institute

Title and Abstract:

Optimising and understanding the impact of the NHS COVID-19 app using data science

The NHS COVID-19 app has been downloaded over 21 million times. It was the first app in the world to use the new Google / Apple  API, allowing novel Bayesian statistical methods to be used to infer distance. Our latest research demonstrates that the app has been able to reduce the number of cases by approximately 600,000, in 2020. The app data are providing valuable insights into the evolution of the pandemic across England and Wales. In this presentation, I will provide an overview of the NHS COVID-19 app, the impact results, and our potential future directions.