Jiawei Han

123.0k citations
742 papers · 66.1k indexed · 26 hit papers · h-index 110

Jiawei Han

716 papers receiving 61.2k citations

Hit Papers

Large ...10719962026200620164.0k8.0k12.0k

Peers

Jiawei Han
Comparison fields: 5 of 231
  • Signal Processing 14.2k
  • Information Systems 27.1k
  • Artificial Intelligence 34.7k
  • Computational Theory and Mathematics 9.8k
  • Statistical and Nonlinear Physics 6.6k
Replace Philip S. Yu with:
Philip S. Yu United States
Michael I. Jordan United States
George Karypis United States
Qiang Yang Hong Kong
Andrew Y. Ng United States
Jian Pei Canada
Jürgen Schmidhuber Switzerland
Jure Leskovec United States
Francisco Herrera Spain
Jon Kleinberg United States
Jiawei Han relative to Philip S. Yu United States Philip S. Yu's profile →
Citations per field
00.5×1.5×
Philip S. Yu · 1×
Citations per year

Countries citing papers authored by Jiawei Han

Since Specialization
Citations

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

Fields of papers citing papers by Jiawei Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Jiawei 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 Jiawei Han Line = papers co-authored together Jiawei Han links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20240
3 20242
4 202414
5 20234
6 20236
7
Large Language Models Can Self-Improvebreakdown →
2023107
8 20231
9 20233
10 20232
11 20223
12 20225
13 2021134
14 20194
15 2018180
16 201833
17 201661
18 2012166
19 2011284
20 2006105

About Jiawei Han

Jiawei Han is a scholar working on Signal Processing, Artificial Intelligence and Information Systems, having authored 742 papers that have together received 66.1k indexed citations. Recurring topics across this work include Topic Modeling (211 papers), Data Mining Algorithms and Applications (156 papers), Data Management and Algorithms (155 papers), Complex Network Analysis Techniques (113 papers), Natural Language Processing Techniques (112 papers), Advanced Graph Neural Networks (103 papers), Advanced Database Systems and Queries (93 papers) and Text and Document Classification Technologies (85 papers). The work is most often cited by research in Signal Processing (14.2k citations), Information Systems (27.1k citations) and Artificial Intelligence (34.7k citations). Jiawei Han has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Micheline Kamber, Jian Pei, Yiwen Yin, Xifeng Yan, Philip S. Yu, Xiaofei He, Yizhou Sun, Deng Cai, Thomas S. Huang and Jing Gao. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment, Data Mining and Knowledge Discovery, Knowledge and Information Systems and Statistical Analysis and Data Mining The ASA Data Science Journal.

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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