Danielle C. Maddix

About

Danielle C. Maddix is a scholar working on Artificial Intelligence, Computational Mechanics and Management Science and Operations Research. According to data from OpenAlex, Danielle C. Maddix has authored 7 papers receiving a total of 168 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 2 papers in Computational Mechanics and 2 papers in Management Science and Operations Research. Recurrent topics in Danielle C. Maddix’s work include Time Series Analysis and Forecasting (2 papers), Stock Market Forecasting Methods (2 papers) and Differential Equations and Numerical Methods (1 paper). Danielle C. Maddix is often cited by papers focused on Time Series Analysis and Forecasting (2 papers), Stock Market Forecasting Methods (2 papers) and Differential Equations and Numerical Methods (1 paper). Danielle C. Maddix collaborates with scholars based in United States, Germany and Italy. Danielle C. Maddix's co-authors include Tim Januschowski, Jan Gasthaus, Konstantinos Benidis, Syama Sundar Rangapuram, Lorenzo Stella, Valentín Flunkert, David Salinas, Michael Schneider, Laurent Callot and François-Xavier Aubet and has published in prestigious journals such as Nature Communications, Journal of Computational Physics and ACM Computing Surveys.

In The Last Decade

Co-authorship network of co-authors of Danielle C. Maddix i

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Fields of papers citing papers by Danielle C. Maddix

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danielle C. Maddix. 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 Danielle C. Maddix. The network helps show where Danielle C. Maddix may publish in the future.

Countries citing papers authored by Danielle C. Maddix

Since Specialization

Citations

This map shows the geographic impact of Danielle C. Maddix'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 Danielle C. Maddix with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle C. Maddix more than expected).

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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