Lili Su

2.3k total citations
70 papers, 1.3k citations indexed

About

Lili Su is a scholar working on Artificial Intelligence, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Lili Su has authored 70 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 16 papers in Computer Networks and Communications and 12 papers in Electrical and Electronic Engineering. Recurrent topics in Lili Su's work include Privacy-Preserving Technologies in Data (11 papers), Stochastic Gradient Optimization Techniques (9 papers) and Distributed Control Multi-Agent Systems (6 papers). Lili Su is often cited by papers focused on Privacy-Preserving Technologies in Data (11 papers), Stochastic Gradient Optimization Techniques (9 papers) and Distributed Control Multi-Agent Systems (6 papers). Lili Su collaborates with scholars based in China, United States and Canada. Lili Su's co-authors include Jiaming Xu, Yudong Chen, Nitin H. Vaidya, Ziyi Yang, Xia Lin, Shahin Shahrampour, Yang Hu, Na Li, Weide Li and Xuan Yang and has published in prestigious journals such as IEEE Transactions on Automatic Control, Chemical Communications and Environmental Pollution.

In The Last Decade

Lili Su

63 papers receiving 1.3k citations

Peers

Lili Su
Comparison fields: 5 of 126
  • Artificial Intelligence 530
  • Computer Networks and Communications 291
  • Electrical and Electronic Engineering 193
  • Pharmaceutical Science 159
  • Control and Systems Engineering 128
Replace Wenchao Li with:
Wenchao Li China
Chen Fu China
Xiangjun Zhao China
Feng China
Jens Schulz Germany
Tao Sun China
Yu Gao China
Babak Rezaee Iran
N.L. Ricker United States
Wenchao Li China View profile →
Citations per field, relative to Lili Su
Lili Su · 1×
Citations per year, relative to Lili Su
Lili Su · 1×

Countries citing papers authored by Lili Su

Since Specialization
Citations

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

Fields of papers citing papers by Lili Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lili Su

This figure shows the co-authorship network connecting the top 25 collaborators of Lili Su. A scholar is included among the top collaborators of Lili Su based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lili Su. Lili Su is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 0
3 2
4 0
5 10
6 8
7 1
8 5
9 0
10 5
11
On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective
6
12 46
13 10
14 118
15 103
16 55
17 258
18 21
19 64
20 5

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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