CLAM: Coalgebraic Learning for Automated Modelling

Dept of Computer Science

<H2>Inaugural Lecture</H2>
By Alexandra Silva, Professor of Algebra, Semantics, and Computation, UCL Department of Computer Science
Date/time: 18th December 2018 from 17.30-18:30 (followed by a catered reception from 18.30- 19.30)
Location: Faber Creative Spaces, Bloomsbury House, 74-77 Great Russell St, London WC1B 3DA
Abstract Automata are one of the simplest and pervasive structures in Computer Science.  Despite their simplicity, automata play an important role in many tasks notably in modelling and verification of hardware and software systems. 
Coalgebra has emerged in the last two decades as a mathematical framework to uniformly describe semantics and algorithms of different types of automata and, more generally, state-based systems. 
In this talk, I will describe how coalgebraic techniques can be used to understand and generalize automata learning algorithms. This opens the door to automated modelling of a large class of systems which can be used in verification. 
Biography Alexandra Silva is a theoretical computer scientist whose main research focuses on semantics of programming languages and modular development of algorithms for computational models. A lot of her work uses the unifying perspective offered by coalgebra, a mathematical framework established in the last decades.  
Alexandra is currently a Professor of Algebra, Semantics, and Computation at University College London. Previously, she was an assistant professor in Nijmegen and a post-doc at Cornell University, with Prof. Dexter Kozen, and a PhD student at the Dutch national research center for Mathematics and Computer Science (CWI), under the supervision of Prof. Jan Rutten and Dr. Marcello Bonsangue. 
She was the recipient of the Needham Award 2018, the Presburger Award 2017, the Leverhulme prize 2016, and an ERC starting Grant in 2015.

Faber Creative Spaces

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CLAM: Coalgebraic Learning for Automated Modelling

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