Devin Schwab

About

Devin Schwab is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Science and Operations Research. According to data from OpenAlex, Devin Schwab has authored 4 papers receiving a total of 16 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Management Science and Operations Research. Recurrent topics in Devin Schwab’s work include Reinforcement Learning in Robotics (4 papers), Adversarial Robustness in Machine Learning (2 papers) and Adaptation to Concept Drift in Data Streams (2 papers). Devin Schwab is often cited by papers focused on Reinforcement Learning in Robotics (4 papers), Adversarial Robustness in Machine Learning (2 papers) and Adaptation to Concept Drift in Data Streams (2 papers). Devin Schwab collaborates with scholars based in United States. Devin Schwab's co-authors include Manuela Veloso and Soumya Ray and has published in prestigious journals such as Machine Learning, 2022 International Conference on Robotics and Automation (ICRA) and 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

In The Last Decade

Co-authorship network of co-authors of Devin Schwab i

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Fields of papers citing papers by Devin Schwab

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Devin Schwab

Since Specialization

Citations

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