Xiaochuang Han

55 total papers · 994 total citations
18 papers, 316 citations indexed

About

Xiaochuang Han is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Genetics. According to data from OpenAlex, Xiaochuang Han has authored 18 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Genetics. Recurrent topics in Xiaochuang Han's work include Topic Modeling (13 papers), Natural Language Processing Techniques (10 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Xiaochuang Han is often cited by papers focused on Topic Modeling (13 papers), Natural Language Processing Techniques (10 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Xiaochuang Han collaborates with scholars based in United States, Mexico and China. Xiaochuang Han's co-authors include Jacob Eisenstein, Yulia Tsvetkov, Byron Wallace, Umashanthi Pavalanathan, Scott F. Kiesling, Weijia Shi, Luke Zettlemoyer, Sachin Kumar, Wen-tau Yih and Michael Lewis and has published in prestigious journals such as Computational Linguistics, Proceedings of the ACM on Human-Computer Interaction and Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies.

In The Last Decade

Xiaochuang Han

16 papers receiving 297 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Xiaochuang Han 243 36 26 22 22 18 316
Gideon Kotzé 273 1.1× 33 0.9× 33 1.3× 56 2.5× 7 0.3× 13 349
Maria Antoniak 128 0.5× 19 0.5× 10 0.4× 10 0.5× 16 0.7× 23 235
Varada Kolhatkar 202 0.8× 19 0.5× 24 0.9× 13 0.6× 29 1.3× 13 238
Sravana Reddy 171 0.7× 27 0.8× 27 1.0× 35 1.6× 24 1.1× 18 316
Giovanni Moretti 172 0.7× 26 0.7× 37 1.4× 11 0.5× 10 0.5× 29 244
R. Schank 70 0.3× 26 0.7× 15 0.6× 21 1.0× 13 0.6× 11 217
Simone Ashby 173 0.7× 34 0.9× 18 0.7× 16 0.7× 7 0.3× 28 342
Annette Hautli-Janisz 224 0.9× 48 1.3× 26 1.0× 38 1.7× 8 0.4× 40 337
Kirk H. Smith 126 0.5× 13 0.4× 12 0.5× 22 1.0× 9 0.4× 24 353
Masato Hagiwara 217 0.9× 17 0.5× 38 1.5× 7 0.3× 17 0.8× 31 346

Countries citing papers authored by Xiaochuang Han

Since Specialization
Citations

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

Fields of papers citing papers by Xiaochuang Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaochuang Han

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaochuang Han. A scholar is included among the top collaborators of Xiaochuang Han 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 Xiaochuang Han. Xiaochuang Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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