Boston Journal of Computers & Information Technology

Artificial Intelligence & Machine Learning

The journal publishes benchmarked research papers. Focusing on advancing on AI and ML, this is a double-blind, peer-reviewed scientific journal.

Publish Your Research

The call for paper is open. Start your publication process in a peer-reviewed, internationally acclaimed research journal.

Submit Manuscript
Guide To Publish Research
Boston Research Journals


2231-DSDS (Print)
22313-FSWS (Online)

Acceptance to publication

28 days




Creative Commons 2.0 Generic

Computers & Information Technology


The journal of computer science is a well-known journal that primarily focuses on computer science and technology. The journal contains the original and progressive research papers in this discipline in order to provide knowledge. We aim to become a reference research publication. We publish and review original and authentic research papers as well auxiliary materials such as case studies, technical reports, etc. by scholars and researchers all across the world. We welcome submission of papers concerning any branch of computer science and their application in business, industry and other organizations.

Acceptance Rate 31%
Quantopian Grade 84.4%
  • Well-established international journal of scientific research involved in all aspects of computer science and technology.
  • Publish new and refined research and selected scientific journals articles/research papers from all over the world.
  • Promote insight and understanding of the latest trends in computer science and technology.

BRJCIT: Artificial Intelligence & Machine Learning


The objective of our journal is to produce peer-reviewed, authenticated research papers on various theoretical as well as applied disciplines of artificial intelligence prepared by scholars and researchers all across the world. Our journal does not just concern the field of artificial intelligence but also includes all the scopes that are mildly or completely related to these fields providing our authors a single platform for all their works.

  • Neural networks
  • Artificial intelligence
  • Robotics
  • Machine structure and working
  • Mechanical engineering
  • Aerospace & Aerodynamics
  • Elements of AI
  • Machine learning for musicians and artists
  • Transport systems: Global Issues and Future Innovations
  • Introduction to Artificial intelligence
  • Machine Learning Foundations: A case study Approach
  • A complete Reinforcement Learning system(Capstone)
  • Introduction to Machine Learning Course
  • Neural Networks and Deep Learning
  • Join the world’s largest programming course-Python for Everybody
  • Machine Learning with big data
  • Machine Learning for Trading
  • AWS Machine Learning
  • Machine Learning for data science and Analytics
  • MedTech: AI and Medical Robots
  • Reinforcement Learning
  • Artificial intelligence for Business
  • Bayesian Methods for Machine Learning
  • Introduction to Deep Learning
  • Deep Learning in computer vision
  • AI workflow: Machine Learning, Visual Recognition, and NLP
  • Evaluations of AI Applications in Healthcare
  • Artificial Intelligence: Distinguishing Between Fact and Fiction
  • Artificial Intelligence (AI) Education for Teachers
  • Data Science
  • Education & Teaching
  • Art and Design
  • Statics and Probability
  • Nonlinear Dynamics: Mathematical and Computational Approaches
    TensorFlow for Artificial Intelligence by deep learning

Other Boston Research Journals