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IEEE Journal on Selected Areas in Information Theory | 2024 Impact Factor: 2.2 | Cite Score: 7.5 | Q1

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IEEE Journal on Selected Areas in Information Theory | 2024 Impact Factor: 2.2 | Cite Score: 7.5 | Q1

  • About this Journal:
  • IEEE Journal on Selected Areas in Information Theory (JSAIT) is a multidisciplinary journal of special issues that publishes high-quality technical papers on all aspects of information theory and its applications. IEEE Journal on Selected Areas in Information Theory (JSAIT) publishes high quality technical papers on all aspects of Information Theory. It is a multi-disciplinary journal of special issues (SIs) focusing on the intersections of information theory with fields such as machine learning, statistics, genomics, neuroscience, theoretical computer science, and physics. Many fields lean heavily on the fundamentals of information theory, including concepts such as information entropy, compression, coding and decoding, mutual information, divergence, capacity, and rate distortion theory. There will also be special issues for hot topics firmly within information theory, such as new types of codes, short-packet communication, advances in multi-terminal information theory, quantum information theory, information theoretic security, and other emerging topics.
  • The journal emphasizes intersections of information theory with fields such as machine learning, statistics, genomics, neuroscience, theoretical computer science, and physics.
  • It welcomes contributions that use fundamental concepts of information theory — including entropy, compression, coding, mutual information, divergence, capacity, and rate-distortion theory — applied in both traditional and emerging domains.

  • Editor-in-Chief:  Elza Erkip

  • Scope of the Journal:
  • Fundamental and applied aspects of information theory in communications and networks.
  • Advances in coding theory, source and channel coding, quantisation, and rate-distortion analysis.
  • Interdisciplinary applications of information theory in machine learning, inference, and data science.
  • Information-theoretic methods in neuroscience, genomics, and biological systems.
  • Quantum information theory, cryptography, and information-theoretic security.
  • Emerging topics such as short-packet communication, multi-terminal networks, and physics-based information systems.
  • Latest Research Topics for PhD in Computer Science
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  • Latest Research Topics for PhD in Machine Learning
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  • Print ISSN:  26418770

    Electronic ISSN:  

  • Abstracting and Indexing:  Scopus

  • Imapct Factor 2024:  2.2

  • Subject Area and Category:  Artificial Intelligence, Computer Networks and Communications

  • Publication Frequency:  

  • H Index:  28

  • Best Quartile:

    Q1:  Artificial Intelligence

    Q2:  

    Q3:  

    Q4:  

  • Cite Score:  7.5

  • SNIP:  1.447

  • Journal Rank(SJR):  1.297