Statistics and Its Interface, issn 1938-7989, published by INT PRESS BOSTON, INC, is a vital academic journal dedicated to bridging the critical intersection of statistics, applied mathematics, and interdisciplinary research. With its inaugural publication in 2011, this journal has continually aimed to provide a platform for innovative statistical methods and their application across various fields, offering valuable insights for researchers and practitioners alike. While the journal currently operates without an open access model, it maintains an essential position within the scholarly community, evidenced by its 2023 rankings in the third quartile for Applied Mathematics and the fourth quartile for Statistics and Probability. Furthermore, it holds a respectable position in Scopus rankings, reflecting its commitment to quality over quantity. By publishing cutting-edge research, Statistics and Its Interface serves as a critical resource for advancing statistical knowledge and cultivating a deeper understanding of its applications in real-world contexts.

Theoretical Computer Science, published by Elsevier, serves as a pivotal platform in the field of computational theory, exploring the foundational aspects of computer science and mathematical logic since its inception in 1975. With both a print ISSN of 0304-3975 and an E-ISSN of 1879-2294, this journal is esteemed for its rigorous peer-review process and commitment to advancing knowledge in theoretical frameworks and algorithms. Positioned in the Q2 quartile for both Computer Science (miscellaneous) and Theoretical Computer Science categories, it ranks #124 out of 232 in general computer science and #73 out of 130 in theoretical computer science according to Scopus metrics, reflecting its significant influence and reach within the academic community. Researchers and professionals can access this journal through institutional subscriptions, providing a plethora of high-quality articles that contribute to ongoing debates and developments in the discipline. The journal's scope encompasses a wide array of topics, ensuring relevance across various subfields, thus making it an essential resource for anyone dedicated to furthering their understanding of theoretical computer science.

Statistics and Computing is a premier journal published by Springer, dedicated to advancing the fields of statistics and computational theory. With a strong focus on interdisciplinary research, this journal covers a broad spectrum of topics including, but not limited to, statistical methodologies, computational algorithms, and the latest advancements in data analysis. As of 2023, it proudly holds a Q1 ranking in multiple categories including Computational Theory and Mathematics and Statistics and Probability, underscoring its significant influence and recognition within the academic community. The journal's impact is further demonstrated by its commendable positions in Scopus ranks, making it a valuable resource for researchers, professionals, and students alike. Published in the Netherlands, Statistics and Computing is known for its rigorous peer-review process and commitment to quality, ensuring that only the most impactful research is disseminated to the global audience. Submissions from a diverse range of backgrounds are encouraged, fostering an inclusive environment for innovation and collaboration in the statistics and computing realm.

Information and Inference: A Journal of the IMA, published by Oxford University Press, is a leading interdisciplinary journal that spans key domains such as analysis, applied mathematics, computational theory, and statistics. Recognized for its rigorous peer-review process, this journal holds a prestigious Q1 ranking across multiple mathematical categories in the latest 2023 metrics, underscoring its influence and reach within the academic community. With an ISSN of 2049-8764 and an E-ISSN of 2049-8772, the journal aims to foster innovative research and applications in methods of inference and statistical modeling, further enriching the fields it covers. Researchers, professionals, and students alike are encouraged to access cutting-edge studies that drive advancements in theory and practice, contributing significantly to the landscape of contemporary mathematics and computer science. Join the discourse in a journal that not only represents excellence in scholarship but also serves as a vital resource for future developments in information theory and statistical analysis.

Mathematical Foundations of Computing, published by the American Institute of Mathematical Sciences (AIMS), is a distinguished open-access journal that has been actively disseminating influential research in the fields of Artificial Intelligence, Computational Mathematics, Computational Theory and Mathematics, and Theoretical Computer Science since its inception in 2009. With its E-ISSN 2577-8838, this journal is committed to providing researchers and practitioners with cutting-edge mathematical theories and methodologies that underpin modern computational practices, which is critical for advancing the field. The journal proudly holds a Q3 categorization in several relevant domains as of 2023, reflecting its contribution and accessibility amid an evolving academic landscape. By offering open access to its content, it ensures that vital research is freely available to a global audience, enhancing collaboration and innovation. Positioned in the heart of the United States, Mathematical Foundations of Computing serves as a crucial resource for advancing knowledge and fostering discussions among researchers, professionals, and students passionate about the mathematical underpinnings of computing.

COMPUTATIONAL STATISTICS & DATA ANALYSIS, published by Elsevier, is a leading academic journal that has made significant contributions to the fields of Applied Mathematics, Computational Mathematics, Computational Theory and Mathematics, and Statistics and Probability. With an impressive ranking of Q1 in multiple categories, this journal stands at the forefront of scholarly research and innovation. Leveraging its digital accessibility through E-ISSN 1872-7352, the journal facilitates the dissemination of high-quality research findings and methodologies essential for advancing statistical techniques and data analysis applications. Operating from its base in Amsterdam, Netherlands, the journal features rigorous peer-reviewed articles that cater to a diverse readership including researchers, professionals, and students. As a vital resource for cutting-edge developments from 1983 to its ongoing publication in 2025, COMPUTATIONAL STATISTICS & DATA ANALYSIS continues to foster academic discourse and propel the field forward, ensuring that emerging trends and established theories are effectively communicated to the scientific community.

Data Science and Engineering is a premier open access journal published by SPRINGERNATURE, dedicated to advancing the fields of data science, artificial intelligence, computational mechanics, and information systems. Since its inception in 2016, this journal has rapidly established itself as a leader in the academic community, boasting an impressive Q1 ranking in multiple computer science categories, including Artificial Intelligence, Software, and Information Systems. With a commitment to disseminating high-quality research, it caters to a diverse audience of researchers, professionals, and students eager to explore the intersection of data and technology. The journal's robust global reach, combined with its respected reputation, empowers authors to share their findings widely, facilitating breakthroughs and innovations across the digital landscape. Join the vibrant community of scholars contributing to this integral field of study, and stay informed with the latest research by accessing the journal freely online.

SIAM Journal on Mathematics of Data Science is an esteemed publication within the fields of applied mathematics and data science, published by SIAM PUBLICATIONS. This journal serves as a vital platform for researchers and practitioners, dedicated to disseminating high-quality research that addresses complex mathematical problems arising in the context of data science. The journal aims to bridge the gap between rigorous mathematical theory and practical applications, fostering interdisciplinary collaboration among mathematicians, data scientists, and statisticians. With its commitment to excellence, the SIAM Journal on Mathematics of Data Science contributes significantly to advancing the understanding and development of mathematical methodologies that analyze and interpret large datasets effectively. Researchers and professionals will find it an invaluable resource with its comprehensive articles, insightful reviews, and original research papers, which represent the forefront of innovative mathematical approaches in the evolving landscape of data science. For those interested in contributing to this dynamic field, the journal provides an array of access options tailored to diverse audiences.

Canadian Journal of Statistics - Revue Canadienne de Statistique is a prestigious publication in the field of statistics, managed by Wiley. Since its inception in 1973, this journal has served as an essential resource for researchers, practitioners, and students, offering insights into a diverse range of statistical methodologies and applications. With its impact reflected in its 2023 categorization as Q2 in Statistics and Probability and Q3 in Statistics, Probability and Uncertainty, the journal stands out among its peers, exemplifying rigorous standards in empirical research. The journal's ISSN is 0319-5724 and its E-ISSN is 1708-945X, providing a robust platform for the dissemination of knowledge in the field. While it does not offer open access, the journal remains highly regarded and well-cited, contributing significantly to the advancement of statistical theory and practice. As it continues to publish cutting-edge research through to 2024, the Canadian Journal of Statistics is a must-read for anyone seeking to stay informed on the latest trends and developments in statistics.

Wiley Interdisciplinary Reviews: Computational Statistics is a leading journal published by WILEY, renowned for its influential contributions to the field of statistics and its application in computational studies. With an impressive impact factor reflected in its 2023 categorization as Q1 in Statistics and Probability, this journal ranks among the top in its category, positioned at 20 out of 278 in Scopus, placing it in the 92nd percentile for its discipline. The journal spans from 2009 to 2024 and offers a rich repository of interdisciplinary insights that encompass both theoretical advancements and practical applications of computational statistics, making it an invaluable resource for researchers, professionals, and students alike. While it does not currently offer open access, the journal's commitment to high-quality, peer-reviewed content ensures that it remains a trusted source for cutting-edge developments and methodologies in the rapidly evolving realm of computational statistics.