PhD and postdoc positions at LAIV

The Lab for AI and Verification is looking to fill one PhD post and one postdoctoral post. We are looking for candidates with solid knowledge of Theorem Proving and/or Functional/Logic programming, and enthusiasm to apply this knowledge in the domain of Artificial Intelligence.
The PhD post is for 4 years, starting in October 2022. It covers full stipend and PhD fees and is sponsored by the UKRI (ukri.org) and Schlumberger Cambridge (slb.com). The company will provide additional training and support during the PhD studies. This post needs to be filled in as  soon as possible.
We are also looking to employ a postdoctoral researcher for a  6-12 months project to formalise Criminal law in the Functional Language Catala. Formalising criminal law for autonomous cars is of particular interest. This project will be in collaboration with Jonathan Protzenko, Microsoft Research and the School of Law, Edinburgh University. This project has a flexible starting date. 

Please direct all queries to Ekaterina Komendantskaya (ek19@hw.ac.uk

SPLV’22 this week

LAIV team (Katya, Kathrin, Filip, Marco, Natalia, Akilan) are running SPLV’22 this week. For web streaming and recordings visit SPLV main page: https://www.macs.hw.ac.uk/splv/splv-2022/

LAIV PhD students at FOMLAS’22 and FLOC’22

Many congratulations to LAIV PhD students and researchers, who will present their work at FOMLAS’22, as part of the FLOC’22 conference:

Matthew Daggitt, Wen Kokke, Robert Atkey, Luca Arnaboldi and Ekaterina Komendantskaya: Vehicle: A High-Level Language for Embedding Logical Specifications in Neural Networks

Natalia Ślusarz, Ekaterina Komendantskaya, Matthew Daggitt and Robert Stewart: Differentiable Logics for Neural Network Verification

Marco Casadio, Ekaterina Komendantskaya, Verena Rieser, Matthew Daggitt, Daniel Kienitz, Luca Arnaboldi and Wen Kokke: Why Robust Natural Language Understanding is a Challenge

Remi Desmartin, Grant Passmore and Ekaterina Komendantskaya: Neural Networks in Imandra: Matrix Representation as a Verification Choice

CAV’22 contribution

Many congratulations to Marco Casadio et al for having a paper accepted at the international conference on Computer-Aided Verification CAV’22 (Part of FLOC’22). Marco Casadio, Ekaterina Komendantskaya, Matthew L. Daggitt, Wen Kokke, Guy Katz, Guy Amir and Idan Refaeli: “Neural Network Robustness as a Verification Property: A Principled Case Study”

AAAI’22 Success

HAPPY news, the paper by LAIV PhD student Daniel Kienitz et co The Effect of Manifold Entanglement and Intrinsic Dimensionality on Learning has been accepted to the AAAI’22. It is a great success, and totally deserved! Many congratulations, Daniel!