=== Tracks ===

* Symbolic Computation

+ computer algebra
+ symbolic techniques applied to numerics
+ hybrid symbolic and numeric algorithms
+ numerics and symbolics for geometry
+ programming with constraints, narrowing

* Numerical Computing

+ iterative approximation of fixed points
+ solving systems of nonlinear equations
+ numerical and symbolic algorithms for differential equations
+ numerical and symbolic algorithms for optimization
+ parallel algorithms for numerical computing
+ scientific visualization and image processing

* Logic and Programming

+ automatic reasoning
+ formal system verification
+ formal verification and synthesis
+ software quality assessment
+ static analysis
+ timing analysis

* Artificial Intelligence

+ knowledge discovery, representation, and management
+ automated reasoning, uncertain reasoning, and constraint strategies
+ recommender and expert systems
+ intelligent systems, agents, and networks
+ agent-based complex systems
+ AI-based systems for scientific computing
+ machine learning, including deep learning models and technologies
+ explainable and trustworthy AI
+ information retrieval, data mining, text mining and web mining
+ computational intelligence - including fuzzy, neural and evolutionary computing
+ AI applications: natural language processing, computer vision, signal processing, stock
market, computational neuroscience, robotics, autonomous vehicles, medical diagnosis,
cybersecurity, digital design, online education

* Distributed Computing

+ modelling of parallel and distributed systems
+ parallel and distributed algorithms
+ architectures for parallel and distributed systems.
+ applications for parallel and distributed systems,
+ acceleration of AI or Big Data applications using distributed and parallel computing
+ networked intelligence and Internet of Things

* 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