# Michael J. Kearns

> American computer scientist

**Wikidata**: [Q18749034](https://www.wikidata.org/wiki/Q18749034)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Michael_Kearns_(computer_scientist))  
**Source**: https://4ort.xyz/entity/michael-j-kearns

## Summary
Michael J. Kearns is an American computer scientist and university professor known for his contributions to machine learning, artificial intelligence, and algorithmic game theory. He is a professor at the University of Pennsylvania and a fellow of the Association for Computing Machinery (ACM) and the National Academy of Sciences.

## Biography
- Born: California, United States
- Nationality: United States
- Education: Harvard University, University of California, Berkeley
- Known for: Contributions to machine learning, artificial intelligence, and algorithmic game theory
- Employer(s): University of Pennsylvania (2002–present), Bell Labs (1991–2001)
- Field(s): Computer science, informatics

## Contributions
Michael J. Kearns has made significant contributions to the fields of machine learning, artificial intelligence, and algorithmic game theory. His work has advanced the understanding of computational learning theory, reinforcement learning, and multi-agent systems. Kearns has published numerous influential papers and has been recognized with several prestigious awards, including the ACM Fellow award in 2015 for his contributions to these fields. He has also supervised several notable doctoral students, including Jennifer Wortman Vaughan and Ryan Rogers, who have gone on to make their own significant contributions to computer science.

## FAQs
### Q: What is Michael J. Kearns known for?
A: Michael J. Kearns is known for his contributions to machine learning, artificial intelligence, and algorithmic game theory. He has made significant advancements in computational learning theory and reinforcement learning.

### Q: Where does Michael J. Kearns work?
A: Michael J. Kearns is a professor at the University of Pennsylvania, where he has been employed since 2002. He previously worked at Bell Labs from 1991 to 2001.

### Q: What awards has Michael J. Kearns received?
A: Michael J. Kearns has received several awards, including the ACM Fellow award in 2015 and the AAAI Fellow award in 2003. He is also a member of the National Academy of Sciences.

### Q: Who were Michael J. Kearns' doctoral advisors and students?
A: Michael J. Kearns' doctoral advisor was Leslie Valiant. His notable doctoral students include Jennifer Wortman Vaughan, Ryan Rogers, and Seth Neel.

### Q: What are Michael J. Kearns' primary fields of work?
A: Michael J. Kearns' primary fields of work are computer science and informatics, with a focus on machine learning, artificial intelligence, and algorithmic game theory.

## Why They Matter
Michael J. Kearns has had a profound impact on the fields of computer science and informatics. His work in machine learning and artificial intelligence has advanced the understanding of computational learning theory and reinforcement learning, influencing both academic research and practical applications. His contributions to algorithmic game theory have also been significant, providing new insights into multi-agent systems and their behaviors. Kearns' influence extends to his students, many of whom have become leading researchers in their own right, further amplifying his impact on the field.

## Notable For
- ACM Fellow (2015) for contributions to machine learning, artificial intelligence, and algorithmic game theory
- AAAI Fellow (2003) for significant contributions to computational learning theory and multi-agent systems
- Member of the National Academy of Sciences (2021)
- Doctoral advisor to notable computer scientists such as Jennifer Wortman Vaughan and Ryan Rogers
- Author of influential papers and books in the fields of machine learning and artificial intelligence

## Body
### Early Life and Education
Michael J. Kearns was born in California, United States. He earned his degrees from Harvard University and the University of California, Berkeley.

### Career
Kearns began his career at Bell Labs in 1991, where he worked until 2001. He then joined the University of Pennsylvania in 2002, where he has been a professor ever since. His research focuses on machine learning, artificial intelligence, and algorithmic game theory.

### Awards and Honors
Kearns has received numerous awards and honors throughout his career. In 2015, he was named an ACM Fellow for his contributions to machine learning, artificial intelligence, and algorithmic game theory. He was also named an AAAI Fellow in 2003 for his significant contributions to computational learning theory and multi-agent systems. In 2021, he was elected a member of the National Academy of Sciences.

### Research and Publications
Kearns has published extensively in the fields of computer science and informatics. His work has advanced the understanding of computational learning theory, reinforcement learning, and multi-agent systems. He has also supervised several notable doctoral students, including Jennifer Wortman Vaughan and Ryan Rogers.

### Influence and Legacy
Kearns' work has had a lasting impact on the fields of computer science and informatics. His contributions to machine learning and artificial intelligence have influenced both academic research and practical applications. His influence extends to his students, many of whom have become leading researchers in their own right.

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## References

1. Czech National Authority Database
2. [Source](https://www.cis.upenn.edu/~mkearns/)
3. [Source](https://www.nasonline.org/about-nas/events/annual-meeting/nas159/2021-ceremony.html)
4. [Source](https://www.acm.org/media-center/2015/january/fellows-2014)
5. [Source](https://aaai.org/about-aaai/aaai-awards/the-aaai-fellows-program/elected-aaai-fellows/)
6. Mathematics Genealogy Project
7. Virtual International Authority File
8. CiNii Research
9. [2021](https://www.nasonline.org/news-and-multimedia/news/2021-nas-election.html)
10. Google Knowledge Graph
11. National Library of Israel Names and Subjects Authority File