Public lectures 2022

The Department hosted a number of public lectures during 2022 as part of the 50 Years of Computer Science at York celebrations. 

Inaugural Lecture of Radu Calinescu

Professor Radu Calinescu's Inaugural Lecture on 25 May 2022 was entitled "Resilient Autonomous Systems: Vision and Challenges".

"Recent advances in artificial intelligence and robotics promise a future in which autonomous systems will help with societally beneficial tasks that are dangerous, tedious or too costly for humans.

In this talk, I will give examples of such tasks, and explain why delivering them requires autonomous systems that can operate resiliently in the presence of high levels of uncertainty and disruption. I will then argue that the development and operation of resilient autonomous systems pose unprecedented and complex sociotechnical challenges.


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For some of these challenges, I will present possible preliminary solutions. For others, I will only be able to suggest open research questions that must be addressed before progress can be made."

Dr Will Smith

Dr Will Smith presented a Public Lecture on 12 October 2022 entitled "The revolution will not be supervised! Teaching computers to see with self-supervised learning".

"Machine learning, in particular a specific branch called "deep learning", has had a transformative effect on many areas of computer science as well as science and industry more generally.

However, the vast majority of machine learning methods require very large datasets annotated with labels that are usually provided by humans, at great cost and effort. This sort of "supervised learning" is unlike how humans learn and may not be possible for tasks where labels are difficult to obtain or data is scarce. In addition, the trained model is a black box. We do not know how it works and it does not take advantage of any prior information we may have about the problem being solved.

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In this talk, I will provide an accessible introduction to supervised deep learning before describing a recent idea called "self-supervised learning". Here, the data itself provides the supervision without the need for additional labels. This provides a more plausible explanation for how humans are able to learn new skills quickly and with very little supervision. It also provides a promising route for autonomous systems to learn useful tasks simply by observing the world.

I will mainly focus on applications and interesting problems in the area of computer vision, i.e. extracting information from images and videos. In particular, I will describe my own research on the problem of "inverse rendering". This seeks to invert the process of how an image is formed by light reflecting from surfaces towards a camera and has many applications in scene understanding and content capture."

Professor John McDermid OBE FREng

Professor John McDermid, Director of the Assuring Autonomy International Programme, presented a lecture on 14 December 2022 entitled "Safe, Ethical and Secure: Robots you can rely on".

"Computer systems and software have been used in safety-critical applications, where their behaviour could impact human health and wellbeing, for at least 50 years.

These uses have evolved from relatively simple applications, e.g. syringe pumps used to deliver medicines, via sophisticated systems supporting humans, e.g. railway signalling and aircraft flying control systems, through to autonomous systems – where computers and software control physical systems without human intervention. Such modern systems include robots in factories and those that can support the elderly in independent living.

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Often these systems include software technologies such as machine learning and computer vision. These technologies are not just used for robots – they can give clinical advice, they can drive trains and cars – the applications are almost endless. But, even with the current systems, there can be ethical concerns. Will a clinical advisory system treat all patients equally, or will it give advice better suited to one ethnic group than another? Will an autonomous road vehicle be more likely to hit and injure pedestrians than other cars? Will a breach in system security cause harm via any other system connected to it?

The talk will illustrate the evolution of such critical systems over (at least) 40 years and consider what can be done to make them safe, ethical and secure – hence producing robots and other advanced systems you can rely on."