Eric Poe Xing is an American computer scientist whose research spans machine learning, computational biology, and statistical methodology.[2][3] Xing is founding President of the world’s first artificial intelligence university,[4]Mohamed bin Zayed University of Artificial Intelligence (MBZUAI).
Xing became a faculty member at Carnegie Mellon University in 2004, directing the SAILING Lab,[6] whose research spans a broad spectrum of topics ranging from theoretical foundations to real-world applications in machine learning, distributed systems, computer vision, natural language processing, and computational biology. He became a tenured professor in 2011 and became a full professor in 2014.
In 2010, Xing served as a visiting research professor at Meta, formerly known as Facebook, as well as a visiting professor at Stanford University’s Department of Statistics.
Xing’s major research contribution lies in the foundational work of statistical machine learning methodology, including pioneering work in distance metric learning (DML);[7] statistical models and analyses of networks and graphs;[8][9] methods for learning and analyzing graphical models;[10] and new system, theory, and algorithms for distributed machine learning, such as the development of the “parameter server”.[11]
In 2016, Xing co-founded Petuum Inc., a US-based startup dedicated to democratizing the ownership and use of AI systems and solutions and make even the most advanced AI technology accessible and affordable. In 2016 and 2017, Petuum was named by CB Insight as one of the AI 100 around the world.[12] In 2017, Petuum raised $93 million in a round of venture funding from SoftBank.[13] With his collaborators, Xing developed the Petuum framework for distributed machine learning with massive data, big models, and a wide spectrum of algorithms.[14]
In January 2021, Xing became President of the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI).[15]
^S. Hanneke, W. Fu and E. P. Xing (2010). "Discrete Temporal Models of Social Networks, Electronic Journal of Statistics". Electronic Journal of Statistics. 4. arXiv:0908.1258. doi:10.1214/09-EJS548.