Jianxi Gao
researcher
Facts
7 properties- Instance of
- human
- Occupation
- researcher
- Employer
- Rensselaer Polytechnic Institute (2017–present)[3]
- Position held
- associate professor[2]
- Educated at
- Shanghai Jiao Tong University (2006–2012)[4]
- Imported from
- wholeness_audit_2026-05-02
- Maintained by WikiProject
- WikiProject Mathematics[5]
🏷️ Also known as
en Jianxi Gao
🔖 Identifiers · 8
- ORCID iD
- 0000-0002-3952-208X
- OpenAlex ID
- A5031928873, A5129185216, A5136510666, A5137066762as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
- DBLP author ID
- 72/7131
- Google Knowledge Graph ID
- /g/11h2jvy2f5
- Google Scholar author ID
- qMcWVWgAAAAJ
- Loop ID
- 321155
- ResearcherID
- I-1300-2013, C-8494-2015
- ZbMATH author ID
- gao.jianxi
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 17
A mobility network approach to identify and anticipate large crowd gatherings,
An advanced multi-source data fusion method utilizing deep learning techniques for fire detection,
Collective Motion in a Network of Self-Propelled Agent Systems,
Controllability of multiplex, multi-time-scale networks,
Deep learning resilience inference for complex networked systems,
Discrimination reveals reconstructability of multiplex networks from partial observations,
DM-GAN: CNN hybrid vits for training GANs under limited data,
From data to complex network control of airline flight delays
+9 more
← Authored by 17
A mobility network approach to identify and anticipate large crowd gatherings,
An advanced multi-source data fusion method utilizing deep learning techniques for fire detection,
Collective Motion in a Network of Self-Propelled Agent Systems,
Controllability of multiplex, multi-time-scale networks,
Deep learning resilience inference for complex networked systems,
Discrimination reveals reconstructability of multiplex networks from partial observations,
DM-GAN: CNN hybrid vits for training GANs under limited data,
From data to complex network control of airline flight delays
+9 more
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