Matthew Riemer

15 papers and 187 indexed citations i.

About

Matthew Riemer is a scholar working on Artificial Intelligence, Management Science and Operations Research and Molecular Biology. According to data from OpenAlex, Matthew Riemer has authored 15 papers receiving a total of 187 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 6 papers in Management Science and Operations Research and 2 papers in Molecular Biology. Recurrent topics in Matthew Riemer’s work include Reinforcement Learning in Robotics (10 papers), Adversarial Robustness in Machine Learning (3 papers) and Advanced Bandit Algorithms Research (3 papers). Matthew Riemer is often cited by papers focused on Reinforcement Learning in Robotics (10 papers), Adversarial Robustness in Machine Learning (3 papers) and Advanced Bandit Algorithms Research (3 papers). Matthew Riemer collaborates with scholars based in United States, Mexico and China. Matthew Riemer's co-authors include Doina Precup, Irina Rish, Tim Klinger, Gerald Tesauro, Dong Ki Kim, Jonathan P. How, Miao Liu, Djallel Bouneffouf, Michele Franceschini and Shayegan Omidshafiei and has published in prestigious journals such as Journal of Artificial Intelligence Research, arXiv (Cornell University) and International Conference on Machine Learning.

In The Last Decade

Co-authorship network of co-authors of Matthew Riemer i

Fields of papers citing papers by Matthew Riemer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Matthew Riemer

Since Specialization
Citations

This map shows the geographic impact of Matthew Riemer'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 Matthew Riemer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Riemer 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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2025