# Eric P. Xing

> American artificial intelligence researcher

**Wikidata**: [Q18719253](https://www.wikidata.org/wiki/Q18719253)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Eric_Xing)  
**Source**: https://4ort.xyz/entity/eric-p-xing

## Summary
Eric P. Xing is an American artificial intelligence researcher and computer scientist known for his contributions to machine learning, statistical modeling, and large-scale distributed systems. He is a professor at Carnegie Mellon University and the founding president of the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), the world's first graduate-level AI research university.

## Biography
- **Born**: 2000, Shanghai, China
- **Nationality**: People's Republic of China (later U.S. citizen)
- **Education**:
  - Bachelor of Science in Biology and Physics, Tsinghua University (1988–1993)
  - Ph.D. in Molecular Biology and Biochemistry, Rutgers University (1994–1999)
  - Ph.D. in Computer Science, University of California, Berkeley (1999–2004)
- **Known for**: Advances in machine learning algorithms, distributed AI systems, and applications in biology, social networks, and natural language processing.
- **Employer(s)**:
  - Carnegie Mellon University (2004–present)
  - Mohamed bin Zayed University of Artificial Intelligence (2021–present, as founding president)
- **Field(s)**: Artificial intelligence, machine learning, computer science, computational biology

## Contributions
Eric P. Xing has made significant contributions to machine learning theory, algorithms, and applications. His work includes:
- **Distributed Machine Learning**: Developed scalable architectures and systems for large-scale AI training, enabling efficient processing of massive datasets.
- **Probabilistic Graphical Models**: Pioneered algorithms for learning complex probabilistic models, applied to biological data analysis and social network modeling.
- **Biological Applications**: Integrated machine learning with genomics and proteomics, advancing computational biology through statistical methods.
- **AI Education and Leadership**: As founding president of MBZUAI, he established the first university dedicated to graduate-level AI research, shaping global AI education.
- **Mentorship**: Supervised over a dozen Ph.D. students, many of whom have become leading researchers in AI and machine learning (e.g., Steve Hanneke, Kyung-Ah Sohn).

His research has been published in top-tier conferences (e.g., NeurIPS, ICML) and journals, with applications spanning healthcare, finance, and social media.

## FAQs
### Q: What is Eric P. Xing best known for?
A: Eric P. Xing is best known for his work in machine learning, particularly in distributed AI systems, probabilistic modeling, and applications in biology and social networks. He is also the founding president of MBZUAI, the world's first AI-focused graduate university.

### Q: Where did Eric P. Xing earn his degrees?
A: He earned a B.S. in Biology and Physics from Tsinghua University, a Ph.D. in Molecular Biology from Rutgers University, and a Ph.D. in Computer Science from UC Berkeley.

### Q: What awards has Eric P. Xing received?
A: He is a Fellow of the AAAI (2016), ACM (2023), American Statistical Association (2022), and Institute of Mathematical Statistics (2023).

### Q: Who were Eric P. Xing’s doctoral advisors?
A: His advisors included Richard M. Karp, Michael I. Jordan, and Stuart J. Russell at UC Berkeley, and Chung S. Yang at Rutgers.

### Q: What is MBZUAI, and what is Xing’s role there?
A: MBZUAI (Mohamed bin Zayed University of Artificial Intelligence) is a graduate research university in Abu Dhabi. Xing serves as its founding president, leading its academic and research initiatives.

## Why They Matter
Eric P. Xing has shaped modern machine learning by bridging theory and large-scale applications. His work on distributed AI systems has enabled faster, more efficient training of models, critical for handling big data. His interdisciplinary research in biology and social sciences has expanded AI’s real-world impact. As MBZUAI’s president, he is influencing the next generation of AI researchers globally. Without his contributions, advancements in scalable AI and cross-disciplinary applications would lag, and the institutional framework for AI education might look very different.

## Notable For
- Founding president of the world’s first AI-focused graduate university (MBZUAI).
- Fellow of AAAI, ACM, American Statistical Association, and Institute of Mathematical Statistics.
- Pioneering research in distributed machine learning and probabilistic graphical models.
- Mentoring over a dozen Ph.D. students who are now leaders in AI.
- Interdisciplinary applications of AI in biology, social networks, and natural language processing.

## Body
### Early Life and Education
- Born in Shanghai, China, in 2000.
- Earned a B.S. in Biology and Physics from Tsinghua University (1988–1993).
- Completed a Ph.D. in Molecular Biology and Biochemistry at Rutgers University (1994–1999).
- Obtained a second Ph.D. in Computer Science from UC Berkeley (1999–2004), advised by Richard M. Karp, Michael I. Jordan, and Stuart J. Russell.

### Academic Career
- Joined Carnegie Mellon University in 2004 as a faculty member in the Machine Learning Department.
- Founded and directs the CMU Center for Machine Learning and Health.
- Appointed founding president of MBZUAI in 2021, overseeing its establishment as a global hub for AI research.

### Research Focus
- **Machine Learning Theory**: Developed algorithms for learning probabilistic models and distributed training frameworks.
- **Applications**:
  - Computational biology (e.g., gene regulatory network inference).
  - Social network analysis (e.g., community detection).
  - Natural language processing (e.g., topic modeling).
- **Systems**: Designed architectures for large-scale AI, including Petuum, an open-source platform for distributed machine learning.

### Awards and Honors
- AAAI Fellow (2016) for contributions to statistical machine learning.
- ACM Fellow (2023) for advancements in AI algorithms and architectures.
- Fellow of the American Statistical Association (2022) and Institute of Mathematical Statistics (2023).

### Mentorship and Legacy
- Advised Ph.D. students who have become prominent researchers, including Steve Hanneke (machine learning theory) and Kyung-Ah Sohn (bioinformatics).
- His work is widely cited, with a Google Scholar h-index of over 100.

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## References

1. [Source](https://www.cs.cmu.edu/~epxing/)
2. [Source](https://aaai.org/about-aaai/aaai-awards/the-aaai-fellows-program/elected-aaai-fellows/)
3. [Source](https://www.amstat.org/docs/default-source/amstat-documents/pdfs/fellows/fellows2022.pdf)
4. [Source](https://imstat.org/2023/05/02/2023-ims-fellows-announced/)
5. [Source](https://www.acm.org/media-center/2023/january/fellows-2022)
6. Mathematics Genealogy Project