journals

Journals Related to Brad’s Research

Eigenfactor 1, Journal 1: documents the theoretical underpinnings of numeric, symbolic, algebraic, and geometric computing applications. It focuses on analysis and construction of algorithms and programs, and the interaction of programs and architecture. Algorithms documented in TOMS are available as the Collected Algorithms of the ACM at http://calgo.acm.org.

Annals of Applied Statistics 

Eigenfactor 2, Journal 2: Statistical research spans an enormous range from direct subject-matter collaborations to pure mathematical theory. The Annals of Applied Statistics, the newest journal from the IMS, is aimed at papers in the applied half of this range. Published quarterly in both print and electronic form, our goal is to provide a timely and unified forum for all areas of applied statistics.

Automatica 

Eigenfactor 3, Journal 3: publishes papers on original theoretical and experimental research and development in the control of systems, involving all facets of automatic control theory and its applications. Preferably, theoretical papers should include applications; papers dealing with components and systems should include theoretical background and, where appropriate.

Biometrics 

Eigenfactor 4, Journal 4: is published quarterly in electronic form with print subscription available. Its general objective is to promote the use of statistical and mathematical theory and methods in the biosciences through articles describing the development of novel biometrical techniques and their application to new and ongoing subject-matter challenges. A centerpiece of most Biometrics articles is a scientific application that sets scientific or policy objectives, motivates methods development and demonstrates their operation.

Computational Statistics 

Eigenfactor 5, Journal 5: publication of applications and methodological research in the field of computational statistics. The journal provides a forum for computer scientists, mathematicians, and statisticians working in a variety of areas in statistics, including biometrics, econometrics, data analysis, graphics, simulation, algorithms, knowledge-based systems, and Bayesian computing.

Computational Statistics and Data Analysis 

Eigenfactor 6, Journal 6: dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of three refereed sections, 1) Computational Statistics and Software/Algorithms 2) Statistical Methodology for Data Analysis 3) Special Applications.

Data Mining and Knowledge Discovery 

Eigenfactor 7, Journal 7: advances in data gathering, storage, and distribution have created a need for computational tools and techniques to aid in data analysis. Data Mining and Knowledge Discovery in Databases (KDD) is a rapidly growing area of research and application that builds on techniques and theories from many fields, including statistics, databases, pattern recognition and learning, data visualization, uncertainty modelling, data warehousing and OLAP, optimization, and high performance computing.

Journal of Biometrics & Biostatistics 

Journal 8: To publish the most exciting researches with respect to the subjects of Biometrics & Biostatistics. Secondly, to provide a rapid turn-around time possible for reviewing and publishing, and to disseminate the articles freely for research, teaching and reference purposes.

Journal of Computational Science 

Eigenfactor 9, Journal 9: Computational science typically unifies three distinct elements: 1) Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); 2) Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; 3) Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).

Journal of Machine Learning Research 

Eigenfactor 10, Journal 10: JMLR seeks previously unpublished papers on machine learning that contain: 1) new principled algorithms with sound empirical validation, and with justification of theoretical, psychological, or biological nature; 2) experimental and/or theoretical studies yielding new insight into the design and behavior of learning in intelligent systems; 3) accounts of applications of existing techniques that shed light on the strengths and weaknesses of the methods; 4) formalization of new learning tasks (e.g., in the context of new applications) and of methods for assessing performance on those tasks; 5) development of new analytical frameworks that advance theoretical studies of practical learning methods; 6) computational models of data from natural learning systems at the behavioral or neural level

Journal of Statistical Software 

Eigenfactor 11, Journal 11: Present research that demonstrates the joint evolution of computational and statistical methods and techniques.

Lifetime Data Analysis 

Eigenfactor 12, Journal 12: is the only journal dedicated to statistical methods and applications for lifetime data. The journal advances and promotes statistical science in various applied fields that deal with lifetime data, including actuarial science, economics, engineering, environmental sciences, management, medicine, operations research, public health, and social and behavioral sciences.

Optimization Methods and Software 

Eigenfactor 13, Journal 13:, publishes refereed papers on the latest developments in the theory and realization of optimization methods, with particular emphasis on the interface between software development and algorithm design.

PLoS Computational Biology 

Eigenfactor 14, Journal 14: is a peer-reviewed, open-access journal featuring works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. It is an official journal of the International Society for Computational Biology.

Theoretical Population Biology 

Eigenfactor 15, Journal 15: presents articles on the theoretical aspects of the biology of populations, particularly in the areas of ecology, genetics, demography, and epidemiology. Primary emphasis is on development of theory, but the journal also presents experimental results directly impinging on theoretical descriptions of populations and the dynamics of populations.

IEEE 

Peer review for journals author resources

Transactions on Automatic Control 

Eigenfactor 16, Journal 16: The theory, design and application of Control Systems. Integration of these components, as are necessary for the construction of such systems. Scientific, technical, industrial or other activities that contribute to this field,or utilize the techniques or products of this field, subject.

Transactions on Neural Networks and Learning Systems 

Eigenfactor 17, Journal 17: This journal added ‘and Learning Systems’ to its name in January 2012. It publishes technical articles that deal with the theory, design, and applications of neural networks and related learning systems. Emphasis will be given to artificial neural networks and learning systems.

Transactions on Parallel and Distributed Systems 

Eigenfactor 18, Journal 18: Architectures: design, analysis, implementation, and performance measurements. Software: parallel languages and compilers; scheduling and task partitioning; operating systems, and programming environments. Algorithms and applications: models of computation; analysis and design of parallel/distributed algorithms. Other issues: performance measurements, evaluation, modeling and simulation of multiple-processor systems; real-time, reliability and fault-tolerance issues. Conversion of software from sequential-to-parallel forms.

Transactions on Biomedical Engineering 

Eigenfactor 19, Journal 19: Basic and applied papers dealing with biomedical engineering and applied biophysics. Papers range from practical/clinical applications through experimental science and technological development to formalized mathematical theory.

Computing in Science & Engineering 

Eigenfactor 20, Journal 20: There is a need to share knowledge of algorithms, software, and architectures, and to transmit lessons-learned to a broad scientific audience. Computing in Science & Engineering (CiSE) is a cross-disciplinary, international publication that meets this need by presenting contributions of high interest and educational value from a variety of fields, including but not limited to: physics, biology, chemistry, and astronomy. CiSE emphasizes innovative applications in advanced computing, simulation, and analytics, among other cutting-edge techniques.

SIAM 

Journal on Control and Optimization 

Eigenfactor 21, Journal 21: contains research articles on the mathematics and applications of control theory and on those parts of optimization theory concerned with the dynamics of deterministic or stochastic systems in continuous or discrete time or otherwise dealing with differential equations, dynamics, infinite-dimensional spaces, or fundamental issues in variational analysis and geometry.

Journal on Scientific Computing 

Eigenfactor 22, Journal 22: contains research articles on numerical methods and techniques for scientific computation. Papers address computational issues relevant to the solution of scientific or engineering problems and include computational results demonstrating the effectiveness of the proposed techniques.

Journal on Uncertainty Quantification 

Journal 23: publishes research articles presenting significant mathematical, statistical, algorithmic, and application advances in uncertainty quantification and related fields such as sensitivity analysis, model validation, model calibration, data assimilation, and code verification. The journal also solicits papers describing new ideas that could lead to significant progress in methodology for uncertainty quantification as well as review articles on particular aspects. The journal is dedicated to nurturing synergistic interactions between the mathematical, statistical, computational, and applications communities involved in uncertainty quantification and related areas.

Stochastic Processes and their Applications 

Eigenfactor 24, Journal 24: publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests. Characterization, structural properties, inference and control of stochastic processes are covered.