Hello and Welcome

Hi! I'm Karthik, a final-year PhD candidate in the Computer Science Department at Cornell. I am advised by Prof. Thorsten Joachims, working on Machine Learning, Data Science and Information Retrieval. I am grateful to be supported by the Google PhD Fellowship and the Yahoo! Key Scientific Challenge Award. You can find a complete list of my publications here.

At SIGIR, 2010

Contact:     349 Gates Hall, Cornell University
                Ithaca, NY, 14853-7501
Email At:     (my-first-name)[at]cs[dot]cornell[dot]edu

 

Latest News

  • Invited talk on Learning with Humans in the Loop at NIPS-2014 Personalization workshop. Slides online.
  • Paper on Bayesian Ordinal Peer Grading accepted into ACM L@S 2015 conference. An older version that was presented at the NIPS-2014 workshop on Human-Propelled Machine Learning can be found here. Short set of slides available here.
  • Journal paper on Understanding Intrinsic Diversity in Web Search published in ACM TOIS Journal (Oct 2014 issue).
  • Invited talk on Interactive Machine Learning with Humans in the Loop at Los Alamos National Laboratory. Slides online.
  • Paper on machine learning methods for ordinal peer-grading at scale at KDD 2014. Datasets and Code available. Recording of talk available here. Slides available here.
  • Launched web service for peer-grading at scale using machine learning techniques. Details of our method can be found in our Paper. Our toolkit can also be downloaded as a software.
  • Won the Best Student Paper Award at SIGIR 2013 for work on Intrinsic Diversity in Web Search. Paper and Slides are online. A recording of a longer version of the talk (by Paul) is also online.
  • Paper on online learning of socially optimal information systems at ECML 2013. Slides and Poster are online.
  • Awarded Google PhD Fellowship.
  • Paper on improving inference in big data pipelines at KDD 2013. Slides and Poster are online.
  • Paper on stable coactive learning at ICML 2013. Slides and Poster are online.
  • Awarded Yahoo! Key Scientific Challenge Award.

 

Research Interests

  • Machine Learning, Structured Prediction, Online Learning
  • Web Search, Information Retrieval, Learning to Rank, Rank Aggregation, Recommender Systems
  • Educational Analytics, Peer Grading, Machine Learning for MOOCs
  • Data Science, Big Data Analytics, Data Pipelines, Data Mining

  • I am also interested in Natural Langauge Processing, Information Networks and Game Theory

 

Software

 

Selected Publications

You can find a complete list of my publications along with additional resources including presentations, posters, bibtex and talk videos here.


 

You can also find me on Google Scholar, DBLP and ACM.


Education


  • Ph.D. in Computer Science (Minor in Applied Mathematics) at Cornell University (Expected: June 2015)
  • M.S. in Computer Science at Cornell University (2013)
  • B.Tech at IIT Bombay (2010)

 

Awards


 

Work Experience


  • Intern at Google: May-August 2014
  • Research Intern at MSR, Redmond: May-August 2012
  • Research Intern at MSR, Redmond: May-August 2011
  • Research Intern at MSR,Bangalore: May-July 2009

 

Invited Talks


Teaching Experience


  • TA: CS4780/5780 (Machine Learning) Fall 2011, Fall 2013, Fall 2014
  • Lectures: CS4780/5780 (Machine Learning) on 9/11/12
  • Students Mentored/Co-Advised: Ashueep Singh (Fall 2014), Ziyu Fan (Fall 2013, Spring 2014), Akhilesh Potti (Fall 2013, Spring 2014), Tobias Schnabel (Spring 2012), Diego Accame (Spring 2012)


Reviewing Experience


  • PC Member: WWW (2014, 2015); WSDM (2015); ICML (2014, 2015); KDD (2015); SIGIR (2014); ECML (2013, 2014); CIKM (2013), MOD (2015); IKDD (2014); CaRR (2013)
  • Reviewer: KDD(2014); ICML (2013); CIKM (2012); SIGIR (2012); AAAI (2012); IJCNLP (2011)
  • Journal Reviewing: JMLR, Machine Learning, ACM TOIS

 

Last Edited: Dec 22th, 2014