This is the meeting of the SIAM Activity Group on Applied & Computational Discrete Algorithms

The following meetings will be held jointly:

SIAM Conference on Applied and Computational Discrete Algorithms (ACDA21)
SIAM Annual Meeting (AN21)
SIAM Conference on Control and Its Applications (CT21)
SIAM Conference on Discrete Mathematics (DM21)
SIAM Conference on Optimization (OP21)

The SIAM Conference on Applied and Computational Discrete Algorithms is a new conference that brings together researchers who design and study combinatorial and graph algorithms motivated by applications. ACDA is organized by SIAM under the auspices of the SIAM Activity Group on Applied and Computational Discrete Algorithms. ACDA subsumes the long-running series of SIAM Workshops on Combinatorial Scientific Computing, and expands its scope to applications of discrete models and algorithms across all areas in the physical and life sciences and engineering, the social and information sciences, and anywhere discrete mathematical techniques are used to formulate and solve problems in the world. ACDA invites papers on the formulation of combinatorial problems from applications; theoretical analyses; design of algorithms; computational evaluation of the algorithms; and deployment of the resulting software to enable applications.

The conference will include a refereed proceedings and additional submitted talks that are not part of the proceedings. It will also include invited talks, an industrial problem session, a poster session, and one or two minitutorials to introduce general topical areas in applied combinatorics. Awards will be given for best paper, best poster, and best student presentation.

Included Themes

Topics of interest for ACDA include, but are not limited to, discrete or combinatorial problems and algorithms arising in:

    Algorithm engineering
    Algorithmic differentiation (AD)
    Combinatorial optimization and mathematical programming, including scheduling and resource allocation problems
    Combinatorial scientific computing (CSC) including models, algorithms, applications, numerical methods, and problems arising in data analysis
    Computational biology and bioinformatics
    Data management and data science
    Design and analysis of application-inspired exact, randomized, streaming, and approximation algorithms
    Graph and hypergraph algorithms, including problems arising in network science and complex networks
    Interaction between algorithms and modern computing platforms, including challenges arising from memory hierarchies, accelerators, and novel memory technologies
    Machine learning and statistical methods for solving combinatorial problems
    Numerical linear algebra, including sparse matrix computations and randomized approaches
    Parallel and distributed computing, including algorithms, architectures, distributed systems, and all parallelism ranging from instruction-level and multi-core all the way to clouds and exascale
    Other applications arising from security, computational finance, computational chemistry/physics, quantum computing, etc.