Shen Li

180 papers receiving 2.7k citations

Shen Li's Hit Papers

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel 2023 · 89 citations
890+1+2Years since publication50100150200

Peers

Shen Li
Comparison fields: 5 of 193
  • Transplantation 63
  • Computer Science Applications 116
  • Computer Vision and Pattern Recognition 305
  • Biological Psychiatry 28
  • Transportation 71
Replace Anna Goldenberg with:
Anna Goldenberg Canada
Dan Chen China
Riccardo Bellazzi Italy
Johanne Tremblay Canada
Tingting Zhu China
Feng Tian China
Murali Ramanathan United States
Shuang Wang China
David Chen United States
Sai Zhang China
Shen Li relative to Anna Goldenberg Canada Anna Goldenberg's profile →
Citations per field
00.5×7.3×
Anna Goldenberg · 1×
Citations per year

Countries citing papers authored by Shen Li

Since Specialization
Citations

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

Fields of papers citing papers by Shen Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 192 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Neighborhood Attention Transformer
Hit paper breakdown →
2023246
2 2003140
3 2014124
4 2012101
5
PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
Hit paper breakdown →
202389
6 202178
7 202272
8 202266
9 202060
10 202160
11
Wiki-ly Supervised Part-of-Speech Tagging
201255
12 201553
13 202252
14 201851
15 201648
16 201944
17 202343
18 201440
19 201838
20 201337

About Shen Li

Shen Li is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence and Control and Systems Engineering, having authored 192 papers that have together received 2.7k indexed citations. Recurring topics across this work include Schizophrenia research and treatment (8 papers), Cloud Computing and Resource Management (7 papers), Mobile Crowdsensing and Crowdsourcing (6 papers), Topic Modeling (5 papers), Natural product bioactivities and synthesis (5 papers), Video Coding and Compression Technologies (5 papers), Natural Language Processing Techniques (5 papers) and Caching and Content Delivery (5 papers). The work is most often cited by research in Transplantation (63 citations), Computer Science Applications (116 citations), Computer Vision and Pattern Recognition (305 citations), Biological Psychiatry (28 citations) and Transportation (71 citations). Shen Li has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Humphrey Shi, Ali Hassani, Steven Walton, Jiachen Li, Tarek Abdelzaher, Jing Sun, Liang Li, Xiangmei Wu, Shaohan Hu and Ben Taskar. Their work appears in journals such as Journal of Neural Transmission, Current Neurovascular Research, Scientific Reports, Blood and The Journal of Clinical Pharmacology.

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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