Beidi Chen

1.6k citations
29 papers · 767 · h-index 12

Impact in

Papers in

Beidi Chen

28 papers receiving 756 citations

Peers

Beidi Chen
Comparison fields: 5 of 111
  • Biological Psychiatry 36
  • Gastroenterology 52
  • Rheumatology 124
  • Immunology 138
  • Infectious Diseases 91
Replace Yongkang Wu with:
Yongkang Wu China
Haruyasu Ueda Japan
Anna Justyna Milewska Poland
Shanshan Huang China
Adam P. Levine United Kingdom
Rohit Divekar United States
Cláudio Saddy Rodrigues Coy Brazil
Stefano Realdon Italy
Panagiota Kitsanta United Kingdom
Beidi Chen relative to Yongkang Wu China Yongkang Wu's profile →
Citations per field
00.5×2×3.3×
Yongkang Wu · 1×
Citations per year

Countries citing papers authored by Beidi Chen

Since Specialization
Citations

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

Fields of papers citing papers by Beidi Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020174
2 2020163
3 2017129
4 202365
5 202257
6 202123
7
Analyzing log analysis: an empirical study of user log mining
201423
8
Scatterbrain: Unifying Sparse and Low-rank Attention
202114
9 201814
10 202313
11 202412
12 202411
13 202211
14 202311
15 20238
16 20215
17
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training
20215
18
SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems
20205
19
Angular Visual Hardness
20204
20 20224

About Beidi Chen

Beidi Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Pathology and Forensic Medicine and Immunology, having authored 29 papers that have together received 767 indexed citations. Recurring topics across this work include Gut microbiota and health (6 papers), Advanced Neural Network Applications (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Systemic Sclerosis and Related Diseases (3 papers), Anomaly Detection Techniques and Applications (2 papers), Data Quality and Management (2 papers), Stochastic Gradient Optimization Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Biological Psychiatry (36 citations), Gastroenterology (52 citations), Rheumatology (124 citations), Immunology (138 citations) and Infectious Diseases (91 citations). Beidi Chen has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Xuan Zhang, Lidan Zhao, Hao Li, Luxi Sun, Jun Wang, Bingxuan Wu, Xinmiao Jia, Yue Ma, Wenyou Pan and Alain Lescoat. Their work appears in journals such as Journal of Autoimmunity, Microbiome, Lara D. Veeken, Science Bulletin and Trends in Molecular Medicine.

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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