Michael I. Jordan Learning

- 10.36

photo src: twitter.com

Michael Irwin Jordan is an American scientist, Professor at the University of California, Berkeley and leading researcher in machine learning, statistics, and artificial intelligence.


Post-Doc: “Machine Learning Applied to the Social Sciences ...
photo src: www.knowledgelab.org


Maps, Directions, and Place Reviews



Biography

Jordan received his BS magna cum laude in Psychology in 1978 from the Louisiana State University, his MS in Mathematics in 1980 from Arizona State University and his PhD in Cognitive Science in 1985 from the University of California, San Diego. At the University of California, San Diego Jordan was a student of David Rumelhart and a member of the PDP Group in the 1980s.

Jordan is currently a full professor at the University of California, Berkeley where his appointment is split across the Department of Statistics and the Department of EECS. He was a professor at MIT from 1988-1998.


photo src: twitter.com


Work

In the 1980s Jordan started developing recurrent neural networks as a cognitive model. In recent years, though, his work is less driven from a cognitive perspective and more from the background of traditional statistics.

He popularised Bayesian networks in the machine learning community and is known for pointing out links between machine learning and statistics. Jordan was also prominent in the formalisation of variational methods for approximate inference and the popularisation of the expectation-maximization algorithm in machine learning.

Resignation from Machine Learning Journal

In 2001, Michael Jordan and others resigned from the Editorial Board of Machine Learning. In a public letter, they argued for less restrictive access and pledged support for a new open access journal, the Journal of Machine Learning Research (JMLR), which was created by Leslie Kaelbling to support the evolution of the field of machine learning.


Postdoctoral Researcher, Econometrics and Machine Learning job ...
photo src: inomics.com


Honors and awards

Jordan received numerous awards, including a best student paper award (with X. Nguyen and M. Wainwright) at the International Conference on Machine Learning (ICML 2004), a best paper award (with R. Jacobs) at the American Control Conference (ACC 1991), the ACM - AAAI Allen Newell Award, the IEEE Neural Networks Pioneer Award, and an NSF Presidential Young Investigator Award. In 2010 he was named a Fellow of the Association for Computing Machinery "for contributions to the theory and application of machine learning."

Prof. Jordan is a member of the National Academy of Science, a member of the National Academy of Engineering and a member of the American Academy of Arts and Sciences.

He has been named a Neyman Lecturer and a Medallion Lecturer by the Institute of Mathematical Statistics. He received the David E. Rumelhart Prize in 2015 and the ACM/AAAI Allen Newell Award in 2009.

In 2016, Jordan was identified as the "most influential computer scientist", based on an analysis of the published literature by the Semantic Scholar project.

Source of the article : Wikipedia



EmoticonEmoticon

 

Start typing and press Enter to search