Aims & Scope

Machines and Algorithms is a double-blind peer-reviewed and open access triannual academic research journal serving the broad computing, engineering and biomedical communities. The journal aims to cover topics in various sub-disciplines of computational data science, engineering science and biomedical informatics. It also welcomes research on emerging trends of computing technologies that address pertinent challenges. The special emphasis is placed on novel algorithms, advancements in machine intelligence and data-driven approaches, along with their applications across various scientific and industrial domains.

Journal’s scope includes the following Subject areas but is by no means limited to 

  • Articles in the areas of computational approaches, artificial intelligence, data science ,big data, software engineering, cybersecurity, internet of things, and data analysis.
  • Reports substantive results on a wide range of learning methods applied to a variety of learning problems.
  • Articles provide solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena.
  • Articles that respond to a need in medicine, or rare data analysis with novel methods.
  • Articles that Involve healthcare professional's motivation for the work and evolutionary results are usually necessary.
  • Articles show how to apply learning methods to solve important application problems.

The journal covers all theoretical and applied computer science and information technology aspects. Topics of coverage include but are not limited to the following:

  • Algorithms and Data Structures
  • Artificial Intelligence
  • Cloud Computing
  • Computer Architecture and Engineering
  • Computer Graphics and Visualization
  • Computer Networks
  • Computer Security and Cryptography
  • Computer Vision
  • Concurrent, Parallel and Distributed Systems
  • Database Systems
  • Deduction, Reasoning and Problem Solving
  • Human Computer Interaction
  • Image Processing
  • Information Retrieval
  • Information and Coding Theory
  • Knowledge Representation and Reasoning
  • Machine Learning
  • Natural Language Processing
  • Operating Systems
  • Programming Languages and Compilers
  • Simulation and Modeling
  • Scientific Computing
  • Software Engineering
  • Theory of Computation