John Quan

About

John Quan is a scholar working on Artificial Intelligence, Economics and Econometrics and Electrical and Electronic Engineering. According to data from OpenAlex, John Quan has authored 10 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 2 papers in Economics and Econometrics and 1 paper in Electrical and Electronic Engineering. Recurrent topics in John Quan’s work include Reinforcement Learning in Robotics (7 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Sports Analytics and Performance (2 papers). John Quan is often cited by papers focused on Reinforcement Learning in Robotics (7 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Sports Analytics and Performance (2 papers). John Quan collaborates with scholars based in United States, United Kingdom and Israel. John Quan's co-authors include Razvan Pascanu, James Kirkpatrick, Raia Hadsell, Neil C. Rabinowitz, Claudia Clopath, Dharshan Kumaran, Joel Veness, Andrei A. Rusu, Kieran Milan and Demis Hassabis and has published in prestigious journals such as Proceedings of the National Academy of Sciences, IT Professional and arXiv (Cornell University).

In The Last Decade

Co-authorship network of co-authors of John Quan i

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Fields of papers citing papers by John Quan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by John Quan

Since Specialization

Citations

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