Research Showcase, Queen Mary University of London 2016

Some shots of BAYES-KNOWLEDGE staff from today's Research Showcase event.

Hillsborough Inquest - my input

With today's verdict (fans unlawfully killed) coming after more than two years I can now speak about my own involvement in the Inquest.

Because of the years that have passed few people are aware that there was a 'near-miss'  disaster at Hillsborough eight years before the actual disaster. The circumstances were essentially identical -  an FA Cup Semi Final with far too many supporters let in to the Leppings Lane stand leading to a massive crush. Because of the quick thinking of a steward who was able to open a gate onto the pitch nobody died on that occasion (although there were many injuries).  I know this because I was present at that earlier near disaster and I was, in fact, Secretary of the Sheffield Spurs Supporters Club. At the time I wrote to the FA and South Yorkshire police as I felt mistakes had been made, and indeed the incident was sufficiently serious that Hillsborough (which had been used every year as one of the two semi-final venues) was avoided until 1988 (the year before the disaster). Immediately after the disaster in 1989 I wrote to the FA and Lord Taylor (who led the original enquiry) to inform them of the events of 1981. Although I was interviewed at that time by the Police investigators, my evidence was never used.

In 2014 - out of the blue - I was asked to attend the new Hillsborough Inquest as it had been decided that the 1981 incident was an important piece of the story.  Here are a couple of links to media reports about my appearance:

• BBC News Report
• ITV News Report
• Liverpool FC report

Norman Fenton, 26 April 2016

Evangelia Kyrimi wins first prize for best poster at annual UK Meeting on Causal Inference

Evangelia Kyrimi - PhD student supervised by Dr William Marsh has won first prize for the best poster at the annual UK Meeting on Causal Inference that took place last week in London. Her poster was titled "A progressive explanation of causal inference in 'hybrid' Bayesian Networks for supporting clinical decision making" (click on link to download the full poster) .

It explains that, although many ‘causal’ models (notably in medicine) have been developed as decision tools, few of them have been used in practice and this is often due to lack of perceived trustworthiness of the model. Giving users an explanation of the model’s reasoning is crucial for effective decision support. Evangelia's research provides a coherent explanation of inference that can be applied to any causal Bayesian Network model.

The prize included some excellent books...