The Reliable, Secure, and Sustainable Software lab (ReSeSS) focuses on developing automated solutions that support expert decision-making in areas related to quality, security, and reliability of software and AI systems, as well as technology for enabling regulatory compliance of AI.
Our work relies on program analysis, formal methods, machine learning, and empirical research. We typically start from exploratory studies, investigating existing practices and core challenges. We then develop solutions for the identified challenges and evaluate them in a practical setup.
I am extremely grateful to have our research supported by NSERC, CFI, Mitacs, IBM, Samsung, Huawei, and Meta.
Our current projects evolve around four main areas:
Please read this page if you are interested in joining the ReSeSS research lab.
Internal information for lab members is here.