Jun Fan

3.2k citations
91 papers · 2.1k · 1 hit paper · h-index 20

Impact in

Papers in

Jun Fan

83 papers receiving 2.0k citations

Jun Fan's Hit Papers

Local Polynomial Modeling and Its Applications 1998 · 748 citations
7480+9+18Years since publication200400600

Peers

Jun Fan
Comparison fields: 5 of 160
  • Statistics and Probability 560
  • Internal Medicine 99
  • Cardiology and Cardiovascular Medicine 548
  • Computational Mechanics 234
  • Artificial Intelligence 361
Replace Andreas Christmann with:
Andreas Christmann Germany
Christian Weiß Germany
Xuming He United States
Menahem Friedman Israel
Rafał Weron Poland
Liwei Wang China
Chi-Jie Lu Taiwan
Balaji Krishnapuram United States
Klaus Nordhausen Finland
Hao Helen Zhang United States
Jun Fan relative to Andreas Christmann Germany Andreas Christmann's profile →
Citations per field
00.5×8.8×
Andreas Christmann · 1×
Citations per year

Countries citing papers authored by Jun Fan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Local Polynomial Modeling and Its Applications
Hit paper breakdown →
1998748
2 2015143
3 201786
4 201477
5 201672
6 201465
7 201959
8 201459
9 201950
10 202048
11
A Statistical Learning Approach to Modal Regression
202045
12 201444
13 201736
14 201335
15 201433
16 201531
17 201724
18 201923
19 201621
20
Structure-Leveraged Methods in Breast Cancer Risk Prediction.
201619

About Jun Fan

Jun Fan is a scholar working on Cardiology and Cardiovascular Medicine, Artificial Intelligence, Computational Mechanics, Computer Vision and Pattern Recognition and Statistics and Probability, having authored 91 papers that have together received 2.1k indexed citations. Recurring topics across this work include Atrial Fibrillation Management and Outcomes (22 papers), Sparse and Compressive Sensing Techniques (15 papers), Cardiac Arrhythmias and Treatments (13 papers), Statistical Methods and Inference (8 papers), Neural Networks and Applications (8 papers), Control Systems and Identification (6 papers), Face and Expression Recognition (6 papers) and Cardiac electrophysiology and arrhythmias (6 papers). The work is most often cited by research in Statistics and Probability (560 citations), Internal Medicine (99 citations), Cardiology and Cardiovascular Medicine (548 citations), Computational Mechanics (234 citations) and Artificial Intelligence (361 citations). Jun Fan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Irène Gijbels, Hans‐Georg Müller, Mintu P. Turakhia, Susan Schmitt, Chi Harold Liu, Kin K. Leung, Claire T. Than, Ding‐Xuan Zhou, Ting Hu and Paul A. Heidenreich. Their work appears in journals such as Analysis and Applications, Journal of the American College of Cardiology, Journal of Complexity, Journal of Fourier Analysis and Applications and Applied and Computational Harmonic Analysis.

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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