Chad Lieberman

About

Chad Lieberman is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Chad Lieberman has authored 9 papers receiving a total of 277 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Statistical and Nonlinear Physics, 5 papers in Artificial Intelligence and 3 papers in Statistics, Probability and Uncertainty. Recurrent topics in Chad Lieberman’s work include Model Reduction and Neural Networks (5 papers), Gaussian Processes and Bayesian Inference (4 papers) and Probabilistic and Robust Engineering Design (3 papers). Chad Lieberman is often cited by papers focused on Model Reduction and Neural Networks (5 papers), Gaussian Processes and Bayesian Inference (4 papers) and Probabilistic and Robust Engineering Design (3 papers). Chad Lieberman collaborates with scholars based in United States. Chad Lieberman's co-authors include Karen Willcox, Omar Ghattas, Mikhail Zaslavsky, Vladimir Druskin, Krzysztof Fidkowski, Bart van Bloemen Waanders, Jeffrey M. Aristoff and John W. M. Bush and has published in prestigious journals such as Physics of Fluids, SIAM Review and SIAM Journal on Scientific Computing.

In The Last Decade

Co-authorship network of co-authors of Chad Lieberman i

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Fields of papers citing papers by Chad Lieberman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chad Lieberman. 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 Chad Lieberman. The network helps show where Chad Lieberman may publish in the future.

Countries citing papers authored by Chad Lieberman

Since Specialization

Citations

This map shows the geographic impact of Chad Lieberman'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 Chad Lieberman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chad Lieberman 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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