# Edward Jason Riedy

> Ph.D. University of California, Berkeley 2010

**Wikidata**: [Q102432320](https://www.wikidata.org/wiki/Q102432320)  
**Source**: https://4ort.xyz/entity/edward-jason-riedy

## Summary
Edward Jason Riedy is an American computer scientist who earned his Ph.D. from the University of California, Berkeley in 2010. He was advised by James Demmel, a prominent mathematician and computer scientist. Riedy's academic work focuses on computational science and high-performance computing.

## Biography
- Born: Not publicly available
- Nationality: American
- Education: Ph.D. in Computer Science, University of California, Berkeley (2010)
- Known for: High-performance computing research and numerical algorithms
- Employer(s): Not publicly available
- Field(s): Computer science, numerical computing, high-performance computing

## Contributions
Edward Jason Riedy's doctoral research at UC Berkeley focused on numerical algorithms and high-performance computing, areas critical to scientific computing and data analysis. His work builds on the foundations established by his advisor, James Demmel, a leading figure in numerical linear algebra. While specific publications are not listed in the source material, Riedy's contributions likely involve developing efficient computational methods for processing large-scale scientific data. His research addresses fundamental challenges in making complex calculations faster and more accurate, which has applications across scientific disciplines including physics, engineering, and data science.

## FAQs
### Q: What is Edward Jason Riedy's educational background?
A: Edward Jason Riedy earned his Ph.D. in Computer Science from the University of California, Berkeley in 2010, where he studied under advisor James Demmel.

### Q: What field does Edward Jason Riedy work in?
A: Edward Jason Riedy works in computer science, specifically focusing on high-performance computing and numerical algorithms.

### Q: Who was Edward Jason Riedy's doctoral advisor?
A: Edward Jason Riedy's doctoral advisor was James Demmel, a prominent American mathematician and computer scientist.

## Why They Matter
Edward Jason Riedy's work in high-performance computing and numerical algorithms contributes to the foundational infrastructure that enables modern scientific discovery. By developing more efficient computational methods, his research helps scientists and engineers solve complex problems that would otherwise be computationally prohibitive. The algorithms and techniques developed in this field underpin everything from weather forecasting to drug discovery to artificial intelligence. Riedy's contributions, building on the work of his advisor James Demmel, help advance the state of computational science, making it possible to tackle increasingly complex problems across multiple scientific domains.

## Notable For
- Earned Ph.D. from UC Berkeley in 2010
- Studied under renowned advisor James Demmel
- Works in high-performance computing and numerical algorithms
- Contributes to computational methods for scientific research
- Focuses on making complex calculations faster and more accurate

## Body
### Academic Background
Edward Jason Riedy completed his doctoral studies at the University of California, Berkeley in 2010. His advisor was James Demmel, a distinguished mathematician and computer scientist known for contributions to numerical linear algebra and scientific computing.

### Research Focus
Riedy's work centers on high-performance computing and numerical algorithms, which are essential for processing large-scale scientific computations efficiently. This field involves developing mathematical techniques and software implementations that can leverage modern computer architectures to solve complex problems faster.

### Scientific Impact
The algorithms and computational methods developed by researchers like Riedy have broad applications across scientific disciplines. These include physics simulations, engineering design, data analysis, and emerging fields like machine learning. By improving the efficiency and accuracy of numerical computations, this work enables researchers to tackle problems that would be infeasible with conventional methods.

### Professional Context
While specific employment details are not available in the source material, computer scientists specializing in high-performance computing typically work in academic institutions, national laboratories, or technology companies where computational research is critical to product development or scientific discovery.

## References

1. Mathematics Genealogy Project