Mihalis Yannakakis




He studied at the National Technical University of Athens (Diploma in Electrical Engineering, 1975), and at Princeton University (PhD in Computer Science, 1979).

He worked at Bell Labs Research from 1978 until 2001, as Member of Technical Staff (1978-1991) and as Head of the Computing Principles Research Department (1991-2001). He was Director of Computing Principles Research at Avaya Labs (2001-2002), and Professor of Computer Science at Stanford University (2002-2003). He joined Columbia University in 2004.

His research interests include design and analysis of algorithms, complexity theory, combinatorial optimization, game theory, databases, and modeling, verification and testing of reactive systems.

Customize your search:

E.g., 2017-06-27
E.g., 2017-06-27
E.g., 2017-06-27
Self Paced

Learn the principles of machine learning and the importance of algorithms. Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications. This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.

Average: 8 (3 votes)