Sijia Tian
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies 5
- Infectious Diseases top 2%
- COVID-19 Clinical Research Studies 3
- Neurology top 2%
- Parkinson's Disease Mechanisms and Treatments 8
- Amyotrophic Lateral Sclerosis Research 5
- Neurological diseases and metabolism 4
- Neuroinflammation and Neurodegeneration Mechanisms 3
- Long-Term Effects of COVID-19 3
- Neurology top 10%
- Parkinson's Disease Mechanisms and Treatments 8
- Amyotrophic Lateral Sclerosis Research 5
- Neurological diseases and metabolism 4
- Neuroinflammation and Neurodegeneration Mechanisms 3
- Long-Term Effects of COVID-19 3
- Clinical Psychology top 10%
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- Nanoplatforms for cancer theranostics 3
- Co-authors
- Jing LouHuixin LianXuqin KangShengmei NiuLuxi ZhangJinjun ZhangJianren LiNing Liu
- Journals
- SHILAP Revista de lepidopterología (1 paper)Scientific Reports (1 paper)Journal of Colloid and Interface Science (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Sijia Tian
63 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Modeling and Simulation 223
- Infectious Diseases 632
- Neurology 511
- Neurology 98
- Clinical Psychology 207
Countries citing papers authored by Sijia Tian
This map shows the geographic impact of Sijia Tian'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 Sijia Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sijia Tian more than expected).
Fields of papers citing papers by Sijia Tian
This network shows the impact of papers produced by Sijia Tian. 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 Sijia Tian. The network helps show where Sijia Tian may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sijia Tian, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 5 | |
| 4 | 2022 | 1 | |
| 5 | 2021 | 19 | |
| 6 | 2021 | 5 | |
| 7 | 2021 | 4 | |
| 8 | 2020 | 15 | |
| 9 | 2020 | 12 | |
| 10 | 2020 | 11 | |
| 11 | 2020 | 1 | |
| 12 | Characteristics of COVID-19 infection in Beijingbreakdown → | 2020 | 783 |
| 13 | 2017 | 6 | |
| 14 | 2017 | 3 | |
| 15 | 2017 | 6 | |
| 16 | 2016 | 9 | |
| 17 | 2016 | 14 | |
| 18 | 2016 | 7 | |
| 19 | 2013 | 46 | |
| 20 | 2012 | 33 |
About Sijia Tian
Sijia Tian is a scholar working on Neurology, Modeling and Simulation and Neurology, having authored 66 papers that have together received 1.6k indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (8 papers), Amyotrophic Lateral Sclerosis Research (5 papers), COVID-19 epidemiological studies (5 papers), Neurological diseases and metabolism (4 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers), Nanoplatforms for cancer theranostics (3 papers), Long-Term Effects of COVID-19 (3 papers) and COVID-19 Clinical Research Studies (3 papers). The work is most often cited by research in Modeling and Simulation (223 citations), Infectious Diseases (632 citations) and Neurology (511 citations). Sijia Tian has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jing Lou, Huixin Lian, Xuqin Kang, Shengmei Niu, Luxi Zhang, Jinjun Zhang, Jianren Li, Ning Liu, Dou Li and Gang Chen. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Colloid and Interface Science.
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.