Theory of Computing

  • data structures and algorithms
  • combinatorial optimization
  • formal languages and combinatorics on words
  • graph-theoretic and combinatorial methods in computer science
  • algorithmic paradigms, including distributed, online, approximation, probabilistic, game-theoretic algorithms
  • computational complexity theory, including structural complexity, boolean complexity, communication complexity, average-case complexity, derandomization and property testing
  • logical approaches to complexity, including finite model theory
  • algorithmic and computational learning theory
  • aspects of computability theory, including computability in analysis and algorithmic information theory
  • proof complexity
  • computational social choice and game theory
  • new computational paradigms: CNN computing, quantum, holographic and other non-standard approaches to computability
  • randomized methods, random graphs, threshold phenomena and typical-case complexity
  • automata theory and other formal models, particularly in relation to formal verification methods such as model checking and runtime verification
  • applications of theory, including wireless and sensor networks, computational biology and computational economics
  • experimental algorithmics

Track Chairs:

  • Florin Manea, Christian-Albrechts-University, Kiel, Germany
  • Mircea Marin, West University of Timisoara, Romania
  • Gabriel Istrate, Institute e-Austria Timisoara, Romania