Daniel Russo

23 papers and 949 indexed citations i.

About

Daniel Russo is a scholar working on Management Science and Operations Research, Artificial Intelligence and Statistics and Probability. According to data from OpenAlex, Daniel Russo has authored 23 papers receiving a total of 949 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Management Science and Operations Research, 15 papers in Artificial Intelligence and 3 papers in Statistics and Probability. Recurrent topics in Daniel Russo’s work include Advanced Bandit Algorithms Research (13 papers), Machine Learning and Algorithms (7 papers) and Reinforcement Learning in Robotics (6 papers). Daniel Russo is often cited by papers focused on Advanced Bandit Algorithms Research (13 papers), Machine Learning and Algorithms (7 papers) and Reinforcement Learning in Robotics (6 papers). Daniel Russo collaborates with scholars based in United States and United Kingdom. Daniel Russo's co-authors include Benjamin Van Roy, Ian Osband, Zheng Wen, Abbas Kazerouni, James Zou, Diego Klabjan, Simcha Pollack, Nishant Prasad, Liang Chen and Carl Urban and has published in prestigious journals such as Management Science, IEEE Transactions on Information Theory and Operations Research.

In The Last Decade

Co-authorship network of co-authors of Daniel Russo i

Fields of papers citing papers by Daniel Russo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Daniel Russo

Since Specialization
Citations

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