Hello and Welcome

Hi! I'm Karthik, a former PhD student in the Computer Science Department at Cornell. I was advised by Prof. Thorsten Joachims and worked on applications in Machine Learning, Data Science and Information Retrieval for my thesis. You can find a complete list of my publications here. After graduating in August 2015, I joined Google as a Research Scientist.

At SIGIR, 2010


I have graduated and joined Google as a Research Scientist.



Contact:     1600 Amphitheatre Parkway
                Mountain View, CA 94043
Email At:     (first-name)(last-name)[at]google[dot]com


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




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.


  • 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)




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