About us

The Laboratory for Foundations of Computer Science (LFCS) is one of six research institutes in the School of Informatics at the University of Edinburgh.

It was founded in 1987 and is a community of theoretical computer scientists with interests in concurrency, semantics, categories, algebra, types, logic, algorithms, complexity, databases and modelling. The mainspring of research in LFCS is the study of theories which underlie, or should in future underlie, the analysis and design of computing systems. Our work has a core of theoretical research and a practical component which explores application and implementation of the theory.  Several research groups exist within LFCS.

  • Algorithms and Computational Complexity
  • Databases
  • Logic, Semantics and Concurrency
  • Programming Languages
  • Quantum Computing
  • Security, Privacy and Cryptography
  • Software Engineering
  • System Biology
  • Verification, Testing and Model Checking

Example Projects

  • ABCD Concurrent Functional Programming and Session Types (Professor Philip Wadler)
  • Blockchain Technology Laboratory (Professor Aggelos Kiayias and IOHK)
  • VADA Value Added Database Systems (Leonid Libkin, Professor Wenfei Fan)
  • App Garden Security of Mobile Systems (Professor David Aspinall)
  • Quanticol Design and Analysis of Collective Adaptive Systems (Professor Jane Hillston)
  • REMS Rigorous Engineering Systems (Doctor Ian Stark)
  • QUEST Quantum Technology (Professor Elham Kashefi)
  • Askye Programming Language Technology for Data  Curation (Professor James Chaney)
  • Huawei- Edinburgh Joint Research Laboratory Grant: Graph Systems (Professor Wenfei Fan)
  • Huawei- Edinburgh Joint Research Laboratory Grant: Game-Theoretic approaches to data privacy ( Professor Kousha Etessami)

Emerging Research

  • Security and Privacy: secure voting, multi-party computation, blockchains and cryptocurrency, and data privacy
  • Programming Languages: probabilistic programming languages for machine learning, concurrent programming with session types, programming languages for data curation
  • Algorithms: foundations for data science, randomized algorithms, spectral algorithms, algorithmic game theory
  • Databases: querying big data, incomplete databases, efficient graph pattern querying
  • Quantum technology: quantum verification, quantum information and category theory