# Hadi Esmaeilzadeh

> Ph.D. University of Washington 2013

**Wikidata**: [Q102417948](https://www.wikidata.org/wiki/Q102417948)  
**Source**: https://4ort.xyz/entity/hadi-esmaeilzadeh

## Summary
Hadi Esmaeilzadeh is a computer scientist who earned his Ph.D. from the University of Washington in 2013. His doctoral work focused on approximate acceleration for a post-multicore era. He studied under advisors Douglas Burger and Luis Ceze.

## Biography
- Born: Not specified
- Nationality: Not specified
- Education: Ph.D. in computer science/computer engineering, University of Washington, 2013
- Known for: Research in approximate computing and computer architecture
- Employer(s): Not specified
- Field(s): Computer science, computer engineering

## Contributions
Hadi Esmaeilzadeh's primary contribution is his doctoral dissertation titled "Approximate Acceleration for a Post Multicore Era," completed at the University of Washington in 2013. This work explored techniques for improving computational efficiency through approximation methods, addressing challenges in the transition beyond traditional multicore processing. His research under advisors Douglas Burger and Luis Ceze contributed to the field of computer architecture, specifically in developing strategies for energy-efficient computing through controlled approximation of computational results.

## FAQs
### Q: What was the title of Hadi Esmaeilzadeh's doctoral dissertation?
A: His dissertation was titled "Approximate Acceleration for a Post Multicore Era," completed at the University of Washington in 2013.

### Q: Who were Hadi Esmaeilzadeh's doctoral advisors?
A: His doctoral advisors were Douglas Burger and Luis Ceze, both at the University of Washington.

### Q: When did Hadi Esmaeilzadeh complete his Ph.D.?
A: He completed his Ph.D. in 2013 from the University of Washington.

## Why They Matter
Hadi Esmaeilzadeh's research on approximate computing represents an important contribution to addressing the limitations of traditional multicore processors. His work on "Approximate Acceleration for a Post Multicore Era" explored how controlled approximation of computational results could lead to significant improvements in energy efficiency and performance. This approach has become increasingly relevant as computing systems face physical and power constraints. By developing methods to trade off precision for efficiency in appropriate contexts, Esmaeilzadeh's research has influenced how computer scientists approach the design of future computing systems, particularly in domains where perfect accuracy is not always necessary.

## Notable For
- Completed Ph.D. in computer science/computer engineering at University of Washington in 2013
- Authored dissertation on "Approximate Acceleration for a Post Multicore Era"
- Conducted research under advisors Douglas Burger and Luis Ceze
- Contributed to field of approximate computing and computer architecture
- Mathematics Genealogy Project ID: 181402

## Body
### Educational Background
Hadi Esmaeilzadeh earned his Ph.D. from the University of Washington in 2013, specializing in computer science and computer engineering. His doctoral work was completed under the supervision of Douglas Burger and Luis Ceze, both established researchers in computer architecture.

### Research Focus
His dissertation, "Approximate Acceleration for a Post Multicore Era," addressed a critical challenge in computer architecture: how to continue improving computational performance as traditional multicore scaling approaches its limits. The work explored approximate computing techniques that could provide significant energy and performance benefits by allowing controlled errors in computation where perfect accuracy is not essential.

### Academic Lineage
Esmaeilzadeh is listed in the Mathematics Genealogy Project with ID 181402, connecting his academic lineage to the broader network of computer science researchers. His work represents a contribution to the ongoing evolution of computer architecture research, particularly in developing strategies for the post-scaling era of computing.

## References

1. Mathematics Genealogy Project
2. WorldCat