Michael

Research Expertise and Interest

computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization

Research Description

Michael Jordan is a professor of Statistics and Computer Sciences.  His research focuses on the relationships between computation, inference, and incentives. He also works on applications in molecular biology, natural language processing, signal processing and mechanism design. Specific areas of focus in recent years include convex and nonconvex optimization theory, gradient-based stochastic processes, variational inequalities, and statistical contract theory.

In the News

UC Berkeley Launches Sky Computing Lab to Revolutionize the Cloud Industry

UC Berkeley formally launched this week The Sky Computing Lab aimed at establishing a two-sided market mediated by services that identify and harness for users the best combination of compatible clouds for their needs and building a new backbone for interconnected cloud computing, a milestone that would revolutionize the industry.

EECS professor Michael Jordan named to Royal Society

Michael Jordan, UC Berkeley’s Pehong Chen Distinguished Professor in the Departments of Electrical Engineering and Computer Sciences and of Statistics, is among 10 foreign members elected today to the Royal Society, a prestigious honor accorded to researchers who have made “exceptional contributions to science.”

Big Thinking About Big Data

To Michael Jordan, the smart way to extract and analyze key information embedded in mountains of “Big Data” is to ignore most of it. Instead, zero in on collections of small amounts of data.

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