Daniel Guo

About

Daniel Guo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Daniel Guo has authored 3 papers receiving a total of 101 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Computational Mechanics. Recurrent topics in Daniel Guo’s work include Topic Modeling (1 paper), Inverse Problems in Mathematical Physics and Imaging (1 paper) and Reinforcement Learning in Robotics (1 paper). Daniel Guo is often cited by papers focused on Topic Modeling (1 paper), Inverse Problems in Mathematical Physics and Imaging (1 paper) and Reinforcement Learning in Robotics (1 paper). Daniel Guo collaborates with scholars based in United States and Sweden. Daniel Guo's co-authors include Geoffrey Zweig, Wen-tau Yih, Gökhan Tür, Ashkan Panahi, Christos Thrampoulidis, Babak Hassibi, Martín Arjovsky, Charles Blundell, Adrià Puigdomènech Badia and Alexander Pritzel and has published in prestigious journals such as CaltechAUTHORS (California Institute of Technology), International Conference on Learning Representations and 2022 IEEE Spoken Language Technology Workshop (SLT).

In The Last Decade

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

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Fields of papers citing papers by Daniel Guo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Daniel Guo

Since Specialization

Citations

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