2018 Milner Award Lecture given by Professor Marta Kwiatkowska.
Computing devices support us in almost all everyday tasks, from mobile phones and online banking to wearable and implantable medical devices and autonomous driving. Since embedded software at the heart of these devices must behave correctly in presence of uncertainty, probabilistic verification techniques have been developed to guarantee their safety, reliability and resource efficiency.
Using illustrative examples, this lecture will give an overview of the role that probabilistic modelling and verification can play in a variety of applications, including robotics, security, medical devices and DNA computing. It will also describe recent developments towards model synthesis, which aims to devise a system model that satisfies a given requirement, and is therefore correct by construction. Finally, challenges in verification of deep learning systems will be outlined, and how these may be overcome.
The prize lecture will be webcast live and the video recording of the event will be available shortly after the event.
Attending this event
- Free to attend
- No registration required
- Doors open from 18:00, and seats are allocated on a first-come, first-served basis
- This event may be popular, and entry cannot be guaranteed
- Live subtitles will be available
- British Sign Language interpretation will be available on request. Please let the Scientific Programmes Team know if you plan to attend at least two weeks prior to the event.
- Travel and accessibility information
The Royal Society Milner Award, kindly supported by Microsoft Research, is given annually for outstanding achievement in computer science by a European researcher.
The award replaces the Royal Society and Académie des sciences Microsoft Award and is named in honour of Professor Robin Milner FRS (1934-2010), a pioneer in computer science.
Professor Marta Kwiatkowska was awarded the 2018 Milner Award in recognition of her contribution to the theoretical and practical development of stochastic and quantitative model checking.
For all enquiries, please contact the Scientific Programmes team.