Pradeep Kumar Ravikumar
, Pradeep Ravikumar
Pradeep Kumar Ravikumar
Carnegie Mellon University
Names
How do you usually write your name as author of a paper? Also add any other names you have authored papers under.
Emails
Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. This information is crucial for deduplicating users, and ensuring you see your reviewing assignments.
****@cs.cmu.edu
, ****@gmail.com
, ****@cs.utexas.edu
Personal Links
Add links to your profiles on other sites. (Optional)
Education & Career History
Enter your education and career history. The institution domain is used for conflict of interest detection and institution ranking. For ongoing positions, leave the end field blank.
Associate Professor
Carnegie Mellon University
Present
Carnegie-Mellon University
Present
University of Texas at Austin
Present
Associate Professor
School of Computer Science, Carnegie Mellon University (cs.cmu.edu)
2016 – Present
Associate Professor
University of Texas, Austin (cs.utexas.edu)
2015 – 2016
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Coauthor
Xinnian Zheng
****@utexas.edu
2015 – 2015
Coauthor
Lizy Kurian John
****@ece.utexas.edu
2015 – 2015
Coauthor
Andreas Gerstlauer
****@ece.utexas.edu
2015 – 2015
Coauthor
Alekh Agarwal
****@cs.berkeley.edu
2012 – 2012
Coauthor
Peter L. Bartlett
****@berkeley.edu
2012 – 2012
Coauthor
Martin J. Wainwright
****@stat.berkeley.edu
2012 – 2012
Coauthor
Vincent Q. Vu
****@stat.cmu.edu
2011 – 2011
Coauthor
Thomas Naselaris
****@berkeley.edu
2011 – 2011
Coauthor
Kendrick Kay
****@stanford.edu
2011 – 2011
Coauthor
Jack L. Gallant
****@berkeley.edu
2011 – 2011
Expertise
For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing