# Siddhartha Srinivasa

> American computer scientist and academic

**Wikidata**: [Q80862797](https://www.wikidata.org/wiki/Q80862797)  
**Source**: https://4ort.xyz/entity/siddhartha-srinivasa

## Summary
Siddhartha Srinivasa is an American computer scientist and academic known for his work in robotics and artificial intelligence. He is a professor at the University of Washington and has made significant contributions to the field of robotic manipulation and perception.

## Biography
- Born: Not specified
- Nationality: American
- Education: PhD from Carnegie Mellon University (2005)
- Known for: Robotics, computer science, and computer engineering
- Employer(s): University of Washington
- Field(s): Computer science, computer engineering, robotics

## Contributions
Siddhartha Srinivasa has made significant contributions to the field of robotics, particularly in robotic manipulation and perception. His work focuses on enabling robots to interact with and understand their environment, which has applications in areas such as autonomous systems and human-robot interaction. Srinivasa has published numerous papers on these topics and has been involved in developing algorithms and systems that improve robotic capabilities in real-world scenarios.

## FAQs
### Q: What is Siddhartha Srinivasa known for?
A: Siddhartha Srinivasa is known for his work in robotics, particularly in robotic manipulation and perception. He has contributed to the development of algorithms and systems that enable robots to interact with and understand their environment.

### Q: Where does Siddhartha Srinivasa work?
A: Siddhartha Srinivasa is a professor at the University of Washington, where he is affiliated with the Paul G. Allen School of Computer Science & Engineering.

### Q: What is Siddhartha Srinivasa's educational background?
A: Siddhartha Srinivasa earned his PhD from Carnegie Mellon University in 2005, where he studied under advisors Matthew T. Mason and Michael Andreas Erdmann.

## Why They Matter
Siddhartha Srinivasa's work in robotics has advanced the field's ability to create robots that can effectively interact with and understand their environment. His contributions to robotic manipulation and perception have laid the groundwork for more sophisticated autonomous systems and have influenced the development of human-robot interaction technologies. Srinivasa's research has helped bridge the gap between theoretical robotics and practical applications, making robots more capable and adaptable in real-world scenarios.

## Notable For
- Professor at the University of Washington
- PhD from Carnegie Mellon University (2005)
- Research in robotic manipulation and perception
- Advisor to notable students including Gilwoo Lee and Patrick Lancaster
- Contributions to the field of artificial intelligence and robotics

## Body
### Academic Background
Siddhartha Srinivasa completed his doctoral studies at Carnegie Mellon University in 2005, focusing on robotics under the guidance of Matthew T. Mason and Michael Andreas Erdmann. His dissertation work laid the foundation for his future research in robotic manipulation and perception.

### Research Focus
Srinivasa's research primarily centers on enabling robots to interact with and understand their environment. This includes developing algorithms for robotic manipulation, perception systems, and human-robot interaction. His work has applications in various fields, including autonomous systems and assistive robotics.

### Professional Career
After completing his PhD, Srinivasa joined the faculty at the University of Washington, where he is currently a professor in the Paul G. Allen School of Computer Science & Engineering. He has mentored numerous students, including Gilwoo Lee and Patrick Lancaster, who have gone on to make their own contributions to the field of computer science and robotics.

### Publications and Impact
Throughout his career, Srinivasa has published numerous papers on topics related to robotics and artificial intelligence. His work has been influential in advancing the field's understanding of how robots can effectively interact with and perceive their environment, leading to more sophisticated and capable robotic systems.

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## References

1. Mathematics Genealogy Project
2. WorldCat
3. Virtual International Authority File