Publications  

Research

The focus of my work is on designing scalable and efficient algorithms for machine learning and artificial intelligence.

Bio

I am a senior research scientist at Microsoft Research, New England, a relatively new lab in Cambridge, MA. Previously, I was an associate professor at the Department of Statistics, Wharton, University of Pennsylvania (from 2010-2012), and I was an assistant professor at the Toyota Technological Institute at Chicago. Before this, I did a postdoc in the Computer and Information Science department at the University of Pennsylvania under the supervision of Michael Kearns. I completed my PhD at the Gatsby Unit where my advisor was Peter Dayan. Before Gatsby, I was an undergraduate at Caltech where I did my BS in physics.

Activities and Services

Co-chair for New York Computer Science and Economics Day V, Dec 3rd, 2012.

Program chair for the first New England Machine Learning Day, May 16th, 2012.

Program chair for the 24th Annual Conference on Learning Theory (COLT 2011) which took place in Budapest, Hungary, on July 9-11, 2011.

Course Links

Stat 928: Statistical Learning Theory

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods

Large Scale Learning

Learning Theory

Former Postdocs

Daniel Hsu (while at UPenn)

Former Students

Karthik Sridharan

Former Interns

Rong Ge

Adel Javanmard

Matus Telgarsky

Daniel Hsu

Sathyanarayan Anand

Contact Info

Email: skakade [at] microsoft [dot] com

Microsoft Research, Office 14060
One Memorial Drive
Cambridge, MA 02142