# James M. Rehg

> computer scientist

**Wikidata**: [Q95946476](https://www.wikidata.org/wiki/Q95946476)  
**Source**: https://4ort.xyz/entity/james-m-rehg

## Summary
James M. Rehg is an American computer scientist known for his work in computer vision and robotics. He is a professor at Georgia Tech and has made significant contributions to the field through research, teaching, and mentorship.

## Biography
- Born: Not specified
- Nationality: American
- Education: Ph.D. in Computer Science from Carnegie Mellon University (1995)
- Known for: Computer vision, robotics, and machine learning research
- Employer(s): Georgia Tech (Professor, Director, Co-Director), Carnegie Mellon University (Research Assistant)
- Field(s): Computer Science, Computer Vision, Robotics

## Contributions
James M. Rehg has made substantial contributions to computer vision and robotics through his research and academic leadership. As a professor at Georgia Tech since 2001, he has supervised numerous doctoral students including Tucker Hermans, Jay W. Summet, Sangmin Oh, Ping Wang, Yushi Jing, and Arridhanna Ciptadi. His work has been widely cited and recognized in the academic community, with publications indexed in major databases including Google Scholar (ID: 8kA3eDwAAAAJ), DBLP (ID: r/JMRehg), and IEEE Xplore (ID: 37272058600). Rehg's research has advanced the field of computer vision, particularly in areas related to visual tracking, activity recognition, and human-computer interaction.

## FAQs
### Q: What is James M. Rehg's primary area of research?
A: James M. Rehg specializes in computer vision, robotics, and machine learning, with a focus on visual tracking, activity recognition, and human-computer interaction.

### Q: Where did James M. Rehg receive his Ph.D.?
A: James M. Rehg earned his Ph.D. in Computer Science from Carnegie Mellon University in 1995, where he studied under advisor Takeo Kanade.

### Q: What is James M. Rehg's current position?
A: James M. Rehg is a professor at Georgia Tech, where he has served in various roles including professor, director, and co-director since 2001.

## Why They Matter
James M. Rehg's work has significantly advanced the field of computer vision and robotics through both his research contributions and his mentorship of the next generation of computer scientists. His academic leadership at Georgia Tech has helped establish the institution as a major center for computer vision research. Through his supervision of numerous doctoral students who have gone on to successful careers in academia and industry, Rehg has created a lasting impact that extends far beyond his own publications. His research has contributed to practical applications in areas such as visual tracking and activity recognition, which are fundamental to many modern AI systems.

## Notable For
- Supervised multiple successful doctoral students who have become prominent researchers
- Long-standing professor at Georgia Tech with multiple leadership roles
- Published extensively in computer vision and robotics with high citation counts
- Mentored by pioneering computer vision researcher Takeo Kanade
- Maintained active research presence across multiple academic databases and platforms

## Body
### Academic Background
James M. Rehg completed his doctoral studies at Carnegie Mellon University in 1995, working under the supervision of Takeo Kanade, a pioneering figure in computer vision. This training at one of the world's leading computer vision institutions laid the foundation for his future research career.

### Career at Georgia Tech
Rehg joined Georgia Tech in 2001 as an associate professor and has since held multiple positions including professor, director, and co-director. His long tenure at the institution demonstrates his commitment to both research and academic leadership.

### Research Impact
Through his Google Scholar profile (ID: 8kA3eDwAAAAJ) and other academic databases, Rehg has established a significant research presence. His work spans computer vision, robotics, and machine learning, with particular emphasis on visual tracking and activity recognition.

### Mentorship Legacy
Rehg has supervised numerous doctoral students who have gone on to successful careers. His students include Tucker Hermans, Jay W. Summet, Sangmin Oh, Ping Wang, Yushi Jing, and Arridhanna Ciptadi, creating a network of researchers who continue to advance the field.

### Academic Recognition
His work is indexed across multiple academic platforms including DBLP (ID: r/JMRehg), IEEE Xplore (ID: 37272058600), and zbMATH (ID: rehg.james-m), indicating the breadth and impact of his research contributions to computer science.

## References

1. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-1793-5462/employment/10771854)
2. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-1793-5462/employment/10771847)
3. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-1793-5462/employment/10771775)
4. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-1793-5462/employment/10771830)
5. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-1793-5462/employment/10771773)
6. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-1793-5462/employment/10771701)
7. Mathematics Genealogy Project
8. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0003-1793-5462/external-identifiers/1682885)