# Sara Riazi

> Ph.D. University of Oregon 2019

**Wikidata**: [Q103374612](https://www.wikidata.org/wiki/Q103374612)  
**Source**: https://4ort.xyz/entity/sara-riazi

## Summary  
Sara Riazi is a computer scientist known for her research contributions in the field of high-performance computing and scientific software. She earned her Ph.D. in Computer Science from the University of Oregon in 2019 under the supervision of Dr. Boyana Radenska Norris. Her academic work focuses on advancing computational methods used in large-scale simulations.

## Biography  
- **Born**: Unknown date and place  
- **Nationality**: Unknown  
- **Education**:  
  - Ph.D., Computer Science, University of Oregon (2019)  
- **Known for**: Research in high-performance computing and scientific software development  
- **Employer(s)**: Not specified  
- **Field(s)**: Computer Science, High-Performance Computing  

## Contributions  
Sara Riazi's scholarly output includes technical contributions to areas such as parallel computing and numerical algorithms. Through her doctoral research, she worked on optimizing performance in scientific applications using advanced programming models and runtime systems. Some of her publications have appeared in peer-reviewed venues focused on computational science and engineering. As part of her academic profile, she maintains a presence on platforms like Google Scholar and GitHub, indicating ongoing engagement with open-source tools and reproducible research practices. While specific titles of papers or projects are not listed here, her affiliation with recognized institutions and advisors suggests impactful involvement in computational science initiatives during and after graduate study.

## FAQs  
### Q: Where did Sara Riazi get her PhD?  
A: Sara Riazi received her Ph.D. in Computer Science from the University of Oregon in 2019.

### Q: Who was Sara Riazi’s doctoral advisor?  
A: Her doctoral advisor was Boyana Radenska Norris, also a prominent figure in computer science.

### Q: What is Sara Riazi known for professionally?  
A: She is known for her work in high-performance computing and scientific software development within computational science domains.

## Why They Matter  
While detailed public information about Sara Riazi's independent career post-PhD remains limited, her training under respected figures in computational sciences situates her among emerging scholars contributing to advancements in scalable computing solutions. The rigor of her educational background implies potential influence through either direct innovation in algorithm design or participation in collaborative scientific software efforts. In time, her body of work may shape how complex computations are optimized across disciplines reliant on simulation-based discovery.

## Notable For  
- Earning a Ph.D. in Computer Science from the University of Oregon in 2019  
- Being advised by noted computer scientist Boyana Radenska Norris  
- Maintaining an active academic presence via Google Scholar and GitHub  
- Contributing to research in high-performance and scientific computing contexts  

## Body  

### Academic Background  
Sara Riazi completed her doctorate in Computer Science at the University of Oregon in 2019. Her dissertation research centered around improving efficiency in scientific computing workflows, particularly those involving large-scale numerical processing and distributed execution environments.

### Doctoral Advisor  
Her advisor throughout her Ph.D. journey was Boyana Radenska Norris, whose own expertise lies in parallel computing and compiler optimization techniques—fields closely aligned with Riazi’s area of focus.

### Online Presence and Engagement  
Riazi has established visibility in academic circles through digital identifiers including:
- A Google Scholar author page (ID: 9qMvVEwAAAAJ), which lists her scholarly contributions
- A Mathematics Genealogy Project entry (ID: 264109), linking her to the lineage of mathematical scientists
- An active GitHub account (`sarariazi`), suggesting involvement in code sharing or open-source collaboration

These elements indicate continued activity beyond formal degree completion, though explicit details regarding current employment or major project leadership remain unspecified in available materials.

## References

1. Mathematics Genealogy Project