The pre-print of our work On the Utility of Domain Modeling Assistance with Large Language Models, in collaboration with Meriem Ben Chaaben, Lola Burgueño, and Houari Sahraoui is available on …
Kyanna Dagenais, undergraduate researcher in our lab, has been awarded the prestigious Undergraduate Student Research Award (USRA) by the Natural Sciences and Engineering Research Council of Canada (NSERC) in support …
It is our pleasure to congratulate to our undergraduate researcher, Kyanna Dagenais on her 1st place at the ACM Student Research Competition (SRC) at this year’s MODELS. Kyanna got her …
Recently, I had the pleasure of joining McMaster’s Centre for Software Certification (McSCert). McSCert is dedicated to the certification of software-intensive systems, as well as the design of such systems …
On October 15 2024, I will have the pleasure of giving a guest lecture about the “Foundations of Engineering Digital Twins” for some bright minds at the Federal University of …
Xiaoran (Sharon) Liu‘s recent conference paper “AI Simulation by Digital Twins: Systematic Survey of the State of the Art and a Reference Framework” [preprint], which she published at the 1st …
https://locos.codeberg.page/loco2024/ The 1st International Workshop on Low Carbon Computing (LOCO 2024) will bring together researchers and practitioners with a keen interest in low carbon and sustainable computing. The workshop will …
We have five accepted papers for this year’s MODELS’ co-located and satellite events; and in addition, we lead the organization of two workshops. Accepted papers Sharon Liu, PhD candidate in …
I’m honored to serve on the Program Committee of the 37th International Conference on Advanced Information Systems Engineering (CAiSE). CAiSE is the leading venue of the information systems community, a well-established and …
The full pre-print of our work on Opinion-guided reinforcement learning with Kyanna Dagenais is now available on arXiv: https://arxiv.org/abs/2405.17287. Abstract. Human guidance is often desired in reinforcement learning to improve …