# Xiaoyun Li

> computer scientist

**Wikidata**: [Q131116319](https://www.wikidata.org/wiki/Q131116319)  
**Source**: https://4ort.xyz/entity/xiaoyun-li

## Summary
Xiaoyun Li is a female computer scientist educated at Sun Yat-sen University. She is known for her doctoral research under advisor Pengfei Chen, as evidenced by her academic profiles and advisor reference dated February 25, 2025.

## Biography
- **Education:** Doctoral studies at Sun Yat-sen University (advisor: Pengfei Chen, reference date: 2025-02-25)
- **Known for:** Doctoral research under Pengfei Chen
- **Field(s):** Computer Science
- **Academic Identifiers:** GitHub (humanlee1011), Arnet Miner (63156db3cd729caec637570e), Google Scholar (NZ2hM5kAAAAJ), Google Knowledge Graph (/g/11rnr_r_gm), ACM Digital Library (99659731929)

## Contributions
Xiaoyun Li's contributions are primarily documented through her active academic presence and doctoral research. She maintains a professional GitHub profile (humanlee1011) and is indexed in major academic databases including Arnet Miner, Google Scholar, Google Knowledge Graph, and the ACM Digital Library. Her most significant documented contribution is her doctoral research conducted under the supervision of Pengfei Chen at Sun Yat-sen University, with a specific advisor reference dated February 25, 2025. While specific publications or projects are not detailed in the source material, her academic identifiers confirm her engagement in computer science research and scholarship.

## FAQs
### Q: Who is Xiaoyun Li's doctoral advisor?
A: Xiaoyun Li's doctoral advisor is Pengfei Chen, as referenced on her academic profile dated February 25, 2025.

### Q: Where did Xiaoyun Li pursue her doctoral studies?
A: Xiaoyun Li pursued her doctoral studies at Sun Yat-sen University.

### Q: How can Xiaoyun Li's academic work be found?
A: Xiaoyun Li's academic work is indexed under identifiers like Google Scholar (NZ2hM5kAAAAJ), Arnet Miner (63156db3cd729caec637570e), and ACM Digital Library (99659731929), and she has a GitHub profile (humanlee1011).

### Q: What is Xiaoyun Li's primary field?
A: Xiaoyun Li's primary field is Computer Science.

## Why They Matter
Xiaoyun Li's significance lies in her documented role within the computer science academic community. Her doctoral research under Pengfei Chen contributes to the body of knowledge in the field. Her presence across multiple academic platforms (Google Scholar, ACM DL, Arnet Miner) and her GitHub activity indicate active participation in scholarly work and open-source practices. Her academic profile serves as a node connecting researchers within the computer science network, particularly through her advisor relationship. Her work, while specifics are not detailed in the source, contributes to the ongoing research ecosystem at Sun Yat-sen University and beyond.

## Notable For
*   Doctoral research under advisor Pengfei Chen at Sun Yat-sen University (reference date: 2025-02-25)
*   Maintains an active academic profile indexed in Google Scholar (ID: NZ2hM5kAAAAJ)
*   Listed in the ACM Digital Library (Author ID: 99659731929)
*   Profiled in Arnet Miner (Author ID: 63156db3cd729caec637570e)
*   Maintains a GitHub account (username: humanlee1011)

## Body
### Education and Advisor
Xiaoyun Li is a doctoral student at Sun Yat-sen University. Her doctoral advisor is Pengfei Chen. This advisor relationship is formally documented with a reference date of February 25, 2025, on her academic profile hosted at humanlee1011.github.io.

### Academic Presence
Xiaoyun Li is recognized within major academic computer science databases:
*   **Google Scholar:** Author ID NZ2hM5kAAAAJ
*   **ACM Digital Library:** Author ID 99659731929
*   **Arnet Miner:** Author ID 63156db3cd729caec637570e
*   **Google Knowledge Graph:** Entity ID /g/11rnr_r_gm
*   **GitHub:** Username humanlee1011

### Research Context
Her work falls within the broader field of Computer Science. Her primary documented contribution is her doctoral research conducted under the supervision of Pengfei Chen. Specific publications, projects, or patents resulting from this research are not detailed in the provided source material.

## References

1. [Source](https://humanlee1011.github.io/)