The Monash Laboratory for the Foundations of Computing (MLFC) was established in 2021 with the purpose of providing a place at Monash University to foster, promote, and better enable mathematically-grounded research in different fields of computing. Its members, all experts in different sub-disciplines of Computer Science, Mathematics, and Artificial Intelligence, share a strong interest in mathematical and theoretical aspects of computing.

At present, the laboratory has members in three different Faculties across the University -- Information Technology, Science, and Arts -- specifically working at the Department of Data Science and Artificial Intelligence (DSAI), the Department of Software Systems and Cybersecurity (SSC), the School of Mathematics (Faculty of Science), and the Department of Philosophy (Faculty of Arts). The research we currently do expands across various research areas, including:

  • Computation theory and discrete mathematics;
  • Automated reasoning and discrete optimisation;
  • Learning theory and probabilistic reasoning;
  • Theoretical foundations of computer security.

The laboratory provides support to: facilitate collaborations with researchers around the world; attract students interested in theoretical problems; engage with industry and funding agencies for the development of research projects; carry out theory-based teaching-related activities at Monash; host/organise scientific and outreach events; and, produce significant advances on important research problems in areas of Mathematics and the Foundations of Computer Science and AI.

Current research areas

We have expertise and do research in a variety of areas, including:

  • in computation theory and discrete mathematics: logic, graph theory, complexity theory, game theory, verification, network theory, semantics, proof theory;
  • in automated reasoning and discrete optimisation: computational logic, information theory, combinatorial optimisation, AI foundations, planning, search;
  • in learning theory and probabilistic reasoning: Bayesian reasoning, machine/deep learning foundations, pattern discovery, uncertainty modelling, NLP;
  • in theoretical foundations of computer security: cryptography, algebraic number theory, order theory, blockchain, foundations of cybersecurity and privacy.

If you are interested in studying or working with us, please, get in touch.