Siqi Ai

967 citations
22 papers · 433 · h-index 11

Impact in

Papers in

Siqi Ai

19 papers receiving 429 citations

Peers

Siqi Ai
Comparison fields: 5 of 79
  • Health, Toxicology and Mutagenesis 303
  • Modeling and Simulation 50
  • Environmental Engineering 84
  • Speech and Hearing 39
  • Pollution 56
Replace Robert Mathes with:
Robert Mathes United States
Baijun Sun China
Wenjun Ma China
William Mueller United Kingdom
Tongxing Shi China
Thomas Bourdrel France
Suganthi Jaganathan India
Honghyok Kim South Korea
Trenton Honda United States
Jacob S. Lefler United States
Siqi Ai relative to Robert Mathes United States Robert Mathes's profile →
Citations per field
00.5×1.5×1.8×
Robert Mathes · 1×
Citations per year

Countries citing papers authored by Siqi Ai

Since Specialization
Citations

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

Fields of papers citing papers by Siqi Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201869
2 201860
3 202050
4 201938
5 201832
6 201830
7 202029
8 201925
9 202324
10 202017
11 202113
12 20218
13 20227
14 20217
15 20227
16 20235
17 20205
18 20234
19 20253
20 20250

About Siqi Ai

Siqi Ai is a scholar working on Health, Toxicology and Mutagenesis, General Health Professions, Pollution, Modeling and Simulation and Environmental Engineering, having authored 22 papers that have together received 433 indexed citations. Recurring topics across this work include Climate Change and Health Impacts (14 papers), Air Quality and Health Impacts (13 papers), Global Health Care Issues (6 papers), COVID-19 epidemiological studies (4 papers), Energy and Environment Impacts (3 papers), Air Quality Monitoring and Forecasting (3 papers), Infection Control and Ventilation (1 paper) and Diet, Metabolism, and Disease (1 paper). The work is most often cited by research in Health, Toxicology and Mutagenesis (303 citations), Modeling and Simulation (50 citations), Environmental Engineering (84 citations), Speech and Hearing (39 citations) and Pollution (56 citations). Siqi Ai has collaborated with scholars based in China, United States and New Zealand. Frequent co-authors include Zhengmin Qian, Hualiang Lin, Hualiang Lin, Fan Wu, Yanfei Guo, Wenjun Ma, Steven W. Howard, Yin Yang, Yang Zheng and Shiyu Zhang. Their work appears in journals such as The Science of The Total Environment, Environmental Research Letters, Clinical Infectious Diseases, Toxics and National Science Review.

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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