Jason K. Johnson

875 total citations
25 papers, 498 citations indexed

About

Jason K. Johnson is a scholar working on Artificial Intelligence, Computer Networks and Communications and Clinical Psychology. According to data from OpenAlex, Jason K. Johnson has authored 25 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 7 papers in Computer Networks and Communications and 6 papers in Clinical Psychology. Recurrent topics in Jason K. Johnson's work include Bayesian Modeling and Causal Inference (8 papers), Error Correcting Code Techniques (7 papers) and Autism Spectrum Disorder Research (5 papers). Jason K. Johnson is often cited by papers focused on Bayesian Modeling and Causal Inference (8 papers), Error Correcting Code Techniques (7 papers) and Autism Spectrum Disorder Research (5 papers). Jason K. Johnson collaborates with scholars based in United States and United Kingdom. Jason K. Johnson's co-authors include Alan S. Willsky, Dmitry Malioutov, Clark McKown, Nicole M. Russo‐Ponsaran, Venkat Chandrasekaran, Myung Jin Choi, Venkat Chandrasekaran, Louis Fogg, Michael Chertkov and Shrinivas Kudekar and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Signal Processing and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

Jason K. Johnson

24 papers receiving 463 citations

Peers

Jason K. Johnson

CNC

EDUCA

Robert Dixon United States

Luca Stefanutti Italy

J.M.F. ten Berge Netherlands

Paul Cooper United Kingdom

Kartik Audhkhasi United States

George Miller United States

Georges Haddad Lebanon

George P. Barker United States

D. M. Boulton Australia

Robert Dixon United States

Jason K. Johnson

95 ×0.6

263 ×1.8

CNC

174 ×1.6

EDUCA

11 ×0.1

30 ×0.3

Citations per year, relative to Jason K. Johnson Jason K. Johnson (= 1×) peers Robert Dixon

Countries citing papers authored by Jason K. Johnson

Since Specialization

Citations

This map shows the geographic impact of Jason K. Johnson's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jason K. Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason K. Johnson more than expected).

Fields of papers citing papers by Jason K. Johnson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jason K. Johnson. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jason K. Johnson. The network helps show where Jason K. Johnson may publish in the future.

Co-authorship network of co-authors of Jason K. Johnson

This figure shows the co-authorship network connecting the top 25 collaborators of Jason K. Johnson. A scholar is included among the top collaborators of Jason K. Johnson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jason K. Johnson. Jason K. Johnson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Russo‐Ponsaran, Nicole M., et al.. (2017). Virtual Environment for Social Information Processing: Assessment of Children with and without Autism Spectrum Disorders. Autism Research. 11(2). 305–317. 14 indexed citations

McKown, Clark, Nicole M. Russo‐Ponsaran, & Jason K. Johnson. (2016). Measuring Social-Emotional Skills to Advance Science and Practice.. Society for Research on Educational Effectiveness. 2 indexed citations

Russo‐Ponsaran, Nicole M., et al.. (2015). Efficacy of a Facial Emotion Training Program for Children and Adolescents with Autism Spectrum Disorders. Journal of Nonverbal Behavior. 40(1). 13–38. 32 indexed citations

Russo‐Ponsaran, Nicole M., et al.. (2015). Social‐Emotional Correlates of Early Stage Social Information Processing Skills in Children With and Without Autism Spectrum Disorder. Autism Research. 8(5). 486–496. 15 indexed citations

McKown, Clark, et al.. (2015). Social–Emotional Factors and Academic Outcomes Among Elementary‐Aged Children. Infant and Child Development. 25(2). 119–136. 28 indexed citations

Russo‐Ponsaran, Nicole M., et al.. (2014). A Pilot Study Assessing the Feasibility of a Facial Emotion Training Paradigm for School-Age Children With Autism Spectrum Disorders. Journal of Mental Health Research in Intellectual Disabilities. 7(2). 169–190. 9 indexed citations

McKown, Clark, et al.. (2013). Direct assessment of children’s social-emotional comprehension.. Psychological Assessment. 25(4). 1154–1166. 37 indexed citations

Srinivasan, R., et al.. (2013). Operating air velocities for fiber separation from corn flour using the Elusieve process. Industrial Crops and Products. 45. 100–105.

McKown, Clark, et al.. (2011). Diagnostic efficiency of several methods of identifying socially rejected children and effect of participation rate on classification accuracy. Journal of School Psychology. 49(5). 573–595. 27 indexed citations

10.

Kudekar, Shrinivas, Jason K. Johnson, & Michael Chertkov. (2011). Linear programming based detectors for two-dimensional intersymbol interference channels. e91. 2999–3003. 3 indexed citations

11.

Choi, Myung Jin, Venkat Chandrasekaran, Dmitry Malioutov, Jason K. Johnson, & Alan S. Willsky. (2008). Multiscale stochastic modeling for tractable inference and data assimilation. Computer Methods in Applied Mechanics and Engineering. 197(43-44). 3492–3515. 12 indexed citations

12.

Malioutov, Dmitry, Jason K. Johnson, Myung Jin Choi, & Alan S. Willsky. (2008). Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches. IEEE Transactions on Signal Processing. 56(10). 4621–4634. 20 indexed citations

13.

Chandrasekaran, Venkat, et al.. (2008). Estimation in Gaussian Graphical Models Using Tractable Subgraphs: A Walk-Sum Analysis. IEEE Transactions on Signal Processing. 56(5). 1916–1930. 28 indexed citations

14.

Johnson, Jason K., Venkat Chandrasekaran, & Alan S. Willsky. (2007). Learning Markov Structure by Maximum Entropy Relaxation. CaltechAUTHORS (California Institute of Technology). 203–210. 9 indexed citations

15.

Chandrasekaran, Venkat, Alan S. Willsky, & Jason K. Johnson. (2007). Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis. CaltechAUTHORS (California Institute of Technology). 20. 249–256. 1 indexed citations

16.

Johnson, Jason K. & Alan S. Willsky. (2007). A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields. IEEE Transactions on Image Processing. 17(1). 70–83. 9 indexed citations

17.

Malioutov, Dmitry, Jason K. Johnson, & Alan S. Willsky. (2007). GMRF Variance Approximation using Splicedwavelet Bases. III–1101. 4 indexed citations

18.

Malioutov, Dmitry, Jason K. Johnson, & Alan S. Willsky. (2006). Walk-Sums and Belief Propagation in Gaussian Graphical Models. Journal of Machine Learning Research. 7(73). 2031–2064. 160 indexed citations

19.

Malioutov, Dmitry, Jason K. Johnson, & Alan S. Willsky. (2006). Low-Rank Variance Estimation in Large-Scale Gmrf Models. 3. III–676. 10 indexed citations

20.

Malioutov, Dmitry, Alan S. Willsky, & Jason K. Johnson. (2005). Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation. Neural Information Processing Systems. 18. 579–586. 32 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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