# Yi Li

> Ph.D. University of Washington 2005

**Wikidata**: [Q102243274](https://www.wikidata.org/wiki/Q102243274)  
**Source**: https://4ort.xyz/entity/yi-li-q102243274

## Summary
Yi Li is a computer scientist who earned her Ph.D. from the University of Washington in 2005. Her research focused on object and concept recognition for content-based image retrieval, under the supervision of Linda Shapiro. She is known for her contributions to computer vision and image processing.

## Biography
- Born: 1971
- Nationality: United States
- Education: Ph.D. in Computer Science from the University of Washington (2005)
- Known for: Research in object and concept recognition for image retrieval
- Employer(s): University of Washington (as a doctoral student)
- Field(s): Computer vision, image processing

## Contributions
Yi Li's doctoral work, titled *Object and Concept Recognition for Content-based Image Retrieval*, was supervised by Linda Shapiro. Her research contributed to advancements in image retrieval systems by improving methods for recognizing objects and concepts within images. While specific publications or ongoing projects are not detailed in the provided material, her work aligns with broader efforts in computer vision and content-based image analysis. Her thesis reflects the intersection of computer science and engineering, leveraging machine learning and pattern recognition to enhance image retrieval technologies.

## FAQs
### Q: What was Yi Li's doctoral thesis about?
A: Yi Li's thesis focused on *Object and Concept Recognition for Content-based Image Retrieval*, advancing methods for identifying objects and concepts in images to improve retrieval systems.

### Q: Who was Yi Li's doctoral advisor?
A: Yi Li's doctoral advisor was Linda Shapiro, an American computer scientist and university teacher.

### Q: What field did Yi Li specialize in?
A: Yi Li specialized in computer vision and image processing, particularly in content-based image retrieval.

## Why They Matter
Yi Li's work in image recognition and retrieval has laid foundational research for advancements in computer vision. Her thesis contributed to the development of systems that can more accurately retrieve and analyze images based on their content. While her specific impact may not be widely documented, her research aligns with ongoing efforts to improve image retrieval technologies, which are critical for applications in search engines, medical imaging, and autonomous systems. Her work reflects the broader evolution of computer science in addressing complex data analysis challenges.

## Notable For
- Earned a Ph.D. in Computer Science from the University of Washington in 2005.
- Supervised by Linda Shapiro, a prominent figure in computer science.
- Focused on object and concept recognition for content-based image retrieval.
- Contributed to advancements in image processing and computer vision.

## Body
### Education and Training
Yi Li completed her Ph.D. in Computer Science at the University of Washington in 2005. Her doctoral work was supervised by Linda Shapiro, a renowned computer scientist. Her thesis, *Object and Concept Recognition for Content-based Image Retrieval*, explored techniques for improving image retrieval systems by recognizing objects and concepts within images.

### Research Focus
Yi Li's research centered on enhancing content-based image retrieval, a critical area in computer vision. Her work likely involved developing algorithms to identify and categorize objects and concepts in images, which is essential for applications requiring efficient image search and analysis.

### Academic Affiliations
During her doctoral studies, Yi Li was affiliated with the University of Washington, contributing to the academic community's research in computer science and engineering. Her work was part of a broader effort to advance image processing and retrieval technologies.

### Legacy and Influence
While specific publications or ongoing projects are not detailed in the provided material, Yi Li's contributions reflect the intersection of computer science and engineering, particularly in the development of image recognition systems. Her work aligns with the broader evolution of computer vision, which has seen significant advancements in recent years. Her thesis and research likely influenced subsequent work in content-based image retrieval and related fields.

## References

1. Mathematics Genealogy Project
2. WorldCat