Peng Dai

18 papers and 250 indexed citations
i
.

About

Peng Dai is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Science Applications. According to data from OpenAlex, Peng Dai has authored 18 papers receiving a total of 250 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 7 papers in Computational Theory and Mathematics and 6 papers in Computer Science Applications. Recurrent topics in Peng Dai’s work include Formal Methods in Verification (7 papers), Data Stream Mining Techniques (6 papers) and Reinforcement Learning in Robotics (6 papers). Peng Dai is often cited by papers focused on Formal Methods in Verification (7 papers), Data Stream Mining Techniques (6 papers) and Reinforcement Learning in Robotics (6 papers). Peng Dai collaborates with scholars based in United States, Lithuania and Taiwan. Peng Dai's co-authors include Mausam Mausam, Daniel S. Weld, Daniel S. Weld, Judy Goldsmith, Christopher H. Lin, Praveen Paritosh, Andrey Kolobov, Jeffrey M. Rzeszotarski, Eric A. Hansen and Ed H. and has published in prestigious journals such as Artificial Intelligence, Complexity and ACM Transactions on Intelligent Systems and Technology.

In The Last Decade

Co-authorship network of co-authors of Peng Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Peng Dai. A scholar is included among the top collaborators of Peng Dai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peng Dai. Peng Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

Fields of papers citing papers by Peng Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Peng Dai

Since Specialization
Citations

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

Explore authors with similar magnitude of impact

Rankless by CCL
2026