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 (firstname.lastname@example.org)
In collaboration with IMANDRA (www.imandra.ai), we are developing a neural network verification library in the language Imandra. This week, this work was accepted for publication: R. Desmartin, G. Passmore E. Komendantskaya and M. Daggitt: CheckINN: Wide Range Neural Network Verification in Imandra. 24th International Symposium on Principles and Practice of Declarative Programming PPDP’22.
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/
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
The School registration is now open, please attend and register at https://www.macs.hw.ac.uk/splv/splv22/
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”
We are organising a conference Conference Mathematics of Program Construction, MPC22. Please consider contributing a paper there! The deadline is the 17th April 2022. More information is available on the conference website.
We are looking to hire a new PhD student (fees and stipend covered), to work on verification or semantics of intelligent systems. Please contact email@example.com if you are interested.
Matthew Daggitt is giving an invited talk at WITS 2022, the first Workshop on the Implementation of Type Systems.
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!