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Xiaoli Shen

Researcher / author (OpenAlex)
Person academia

Facts

1 property
Instance of
human[2]
🔖 Identifiers · 2
ORCID iD
0000-0003-2749-1121
OpenAlex ID
A5101705935as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
📚 Sources · 1

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📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 6
Corrosion grade recognition for weathering steel plate based on a convolutional neural network, Deep Learning for Medication Recommendation: A Systematic Survey, MU R-CNN: A Two-Dimensional Code Instance Segmentation Network Based on Deep Learning, Pressure-Induced Superconductivity In Polycrystalline <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi>La</mml:mi></mml:mrow><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mi>Ni</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">O</mml:mi></mml:mrow><mml:mrow><mml:mn>7</mml:mn><m, Progress and Challenges of Integrated Machine Learning and Traditional Numerical Algorithms: Taking Reservoir Numerical Simulation as an Example, Regional scalable priorities for national biodiversity and carbon conservation planning in Asia
← Authored by 6
Corrosion grade recognition for weathering steel plate based on a convolutional neural network, Deep Learning for Medication Recommendation: A Systematic Survey, MU R-CNN: A Two-Dimensional Code Instance Segmentation Network Based on Deep Learning, Pressure-Induced Superconductivity In Polycrystalline <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi>La</mml:mi></mml:mrow><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mi>Ni</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">O</mml:mi></mml:mrow><mml:mrow><mml:mn>7</mml:mn><m, Progress and Challenges of Integrated Machine Learning and Traditional Numerical Algorithms: Taking Reservoir Numerical Simulation as an Example, Regional scalable priorities for national biodiversity and carbon conservation planning in Asia
Affiliated with 4
University of Tokyo, Chinese Academy of Sciences, Southeast University, Institute of Botany, Chinese Academy of Sciences
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Summary

Xiaoli Shen is a human[1].

Related Entities

Institute of Botany, Chinese Academy of Sciences Southeast University

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Xiaoli Shen. Retrieved October 25, 2026, from https://4ort.xyz/entity/xiaoli-shen
MLA “Xiaoli Shen.” 4ort.xyz Knowledge Graph, 4ort.xyz, 25 Oct. 2026, https://4ort.xyz/entity/xiaoli-shen.
BibTeX @misc{4ortxyz_xiaoli-shen_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Xiaoli Shen}}, year = {2026}, url = {https://4ort.xyz/entity/xiaoli-shen}, note = {Accessed: 2026-10-25}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Xiaoli Shen — https://4ort.xyz/entity/xiaoli-shen (retrieved 2026-10-25)

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