Rujun Han

556 citations
17 papers · 294 · h-index 9

Impact in

Papers in

Journals
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2 papers)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)International Conference of Learning Sciences (1 paper)

In The Last Decade

Rujun Han

16 papers receiving 288 citations

Peers

Rujun Han
Comparison fields: 5 of 29
  • Artificial Intelligence 266
  • Computer Vision and Pattern Recognition 58
  • Management Science and Operations Research 32
  • General Social Sciences 7
  • Signal Processing 20
Replace Braden Hancock with:
Braden Hancock United States
Yixin Nie United States
Maud Ehrmann Switzerland
Tim O’Gorman United States
Varvara Logacheva Russia
Leonhard Hennig Germany
Runxin Xu China
Jinhao Jiang China
Egoitz Laparra Spain
Karl Pichotta United States
Rujun Han relative to Braden Hancock United States Braden Hancock's profile →
Citations per field
00.5×3.2×
Braden Hancock · 1×
Citations per year

Countries citing papers authored by Rujun Han

Since Specialization
Citations

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

Fields of papers citing papers by Rujun Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Rujun Han, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Rujun Han Line = papers co-authored together Rujun Han links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 201978
2 202040
3 201937
4 202025
5 202123
6 202119
7 202118
8 202114
9 202211
10 20217
11 20246
12 20186
13 20226
14 20202
15 20231
16 20231
17 20250

About Rujun Han

Rujun Han is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Management Science and Operations Research and Molecular Biology, having authored 17 papers that have together received 294 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (9 papers), Multimodal Machine Learning Applications (6 papers), Advanced Text Analysis Techniques (3 papers), Speech and dialogue systems (2 papers), Data Quality and Management (2 papers), Time Series Analysis and Forecasting (1 paper) and Expert finding and Q&A systems (1 paper). The work is most often cited by research in Artificial Intelligence (266 citations), Computer Vision and Pattern Recognition (58 citations), Management Science and Operations Research (32 citations), General Social Sciences (7 citations) and Signal Processing (20 citations). Rujun Han has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Nanyun Peng, Ning Qiang, Dan Roth, Mu Yang, Yichao Zhou, Hao Wu, Matt Gardner, Aram Galstyan, Ralph Weischedel and Jiao Sun. Their work appears in journals such as Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the AAAI Conference on Artificial Intelligence and International Conference of Learning Sciences.

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