Jason Pazis

8 papers and 133 indexed citations i.

About

Jason Pazis is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jason Pazis has authored 8 papers receiving a total of 133 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Computational Theory and Mathematics and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Jason Pazis’s work include Reinforcement Learning in Robotics (7 papers), Machine Learning and Algorithms (2 papers) and Formal Methods in Verification (2 papers). Jason Pazis is often cited by papers focused on Reinforcement Learning in Robotics (7 papers), Machine Learning and Algorithms (2 papers) and Formal Methods in Verification (2 papers). Jason Pazis collaborates with scholars based in United States. Jason Pazis's co-authors include Jonathan P. How, Christopher Amato, Shayegan Omidshafiei, John Vian and Ronald Parr and has published in prestigious journals such as Autonomous Agents and Multi-Agent Systems, arXiv (Cornell University) and DSpace@MIT (Massachusetts Institute of Technology).

In The Last Decade

Co-authorship network of co-authors of Jason Pazis i

Fields of papers citing papers by Jason Pazis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Jason Pazis

Since Specialization
Citations

This map shows the geographic impact of Jason Pazis'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 Jason Pazis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason Pazis 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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2026