IEEE Journal on Selected Areas in Information Theory
Q1 Journal
Journal
Country
United States
Northern America
Subject Area and Category
Computer Science
└
Applied Mathematics
Q1
└
Artificial Intelligence
Q1
└
Computer Networks and Communications
Q1
SJR 2025
1.352
Q1
SJR Score
H-Index
34
Citations / Doc (2yr)
2.66
Total Docs. (latest)
36
Total Citations (3yr)
603
Publication type
Journals
ISSN
26418770
Coverage
2020-2026
Journal Rank
#2,941
Subject Categories
Applied Mathematics
Q1
Artificial Intelligence
Q1
Computer Networks and Communications
Q1
Media Technology
Q1
Subject Areas
Aims & Scope
The IEEE Journal on Special Areas in Information Theory (JSAIT) is a multi-disciplinary journal of special issues focusing on the intersections of information theory with fields such as machine learning, statistics, genomics, neuroscience, theoretical computer science, and physics.
Any field that utilizes the fundamentals of information theory, including concepts such as entropy, compression, coding, mutual information, divergence, capacity, and rate distortion theory is a candidate for a JSAIT special issue.
There will also be special issues for topics firmly within information theory, particularly emerging areas.
Abstracting & Indexing
Scopus
Google Scholar
Detailed Metrics
| Total Docs. (latest) | 36 |
| Total Docs. (3 years) | 178 |
| Total Refs. | 1,681 |
| Total Citations (3 years) | 603 |
| Citable Docs. (3 years) | 168 |
| Citations / Doc. (2 years) | 2.66 |
| Ref. / Doc. | 46.69 |
| % Female | 20.8% |
Metrics Visualization
Latest year data vs 3-year cumulative figures
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