Update: I defended my thesis and graduated in July-August 2013. Starting October, 2013 I work at Twitter.

I am was a PhD candidate at the Language Technologies Institute in the School of Computer Science at Carnegie Mellon University. My advisor is Prof. William Cohen.

My primary research interest is in the use of machine learning for network analysis and text mining. Specifically, I am interested in latent topic and blockstructure analysis using topic models and stochastic block models. My research is motivated by a need to address the disquietude brought about by the overwhelming complexity of reality. Graphical models allows us to explain and understand complex real world phenomena using grok-able approximations. I am especially interested in using them to uncover patterns in human interaction and communicaiton.

About me

I am a news junkie who grew up in Bangalore, India where the dosas are reason enough for living. After graduating from PESIT with a Bachelor's degree in Computer Science and Engineering in 2003, I worked on text categorization and information extraction problems at the Applied Research division at Yahoo! for four years before starting in the PhD program at the LTI. My very supportive wife and I have been living in Pittsburgh since 2007; ergo I am a Steelers fan in addition to being a fan of the Indian cricket team.

In my non-researcher avatar, I try to practice Vipassana meditation and adopt a minimalist lifestyle.

Research Projects

  • Most recently, I have been developing techniques to regularize mixed membership stochastic models to incorporate some of the advantages of spectral clustering methods into stochastic network models and topic models.
  • We have been colloborating with political scientists to model decision making in politics by analyzing political blogs.
  • In 2008 and 2009, I worked on developing nonparametric topic models for text with temporal variation.
  • In 2007 and 2008, I worked on the Message Task Linking (aka MeTaL) part of the RADAR project during which Vitor Carvalho and I developed CutOnce - a Thunderbird extension to do recipient recommendation and leak detection.

    Code

    Code for most of my work is on github. A lot of is rough around the edges. Please email me if you notice anything's broken.

    Recent Activities

  • I defended my thesis on July 17th.
  • Attended the NSF SoCS consortium for doctoral students in Seattle (June 2013).
  • Guest lecture for the Analysis of Social Media course on Nov 1, 2012.
  • I was an intern in the User Modeling team at Twitter during the summer of 2012.
  • Attended the NSF SoCS consortium for doctoral students and PI meeting held at the University of Michigan, Ann Arbor in June 2012.
  • Proposed my dissertation topic in May 2012. woot!
  • Teaching Assistant for Language & Statistics I - Spring 2011
  • Teaching Assistant for Machine Learning 10-601 - Spring 2010
  • Intern at Google Pittsburgh during the summer of 2009 where I worked on Product Search.
  • Webmaster for ICWSM - 2009 and 2010.

    Publications

         

    2014

    Block-LDA: Jointly Modeling Entity-Annotated Text and Entity-Entity Links
    Ramnath Balasubramanyan and William W. Cohen.
    Chapter in Handbook of Mixed Membership Models and Their Applications (Editors: Edoardo M. Airoldi, David Blei, Elena A. Erosheva, Stephen E. Fienberg)

    2013

    Specifying Latent Structure Characteristics in Mixed-membership Models [pdf | slides]
    Ramnath Balasubramanyan.
    Thesis document. Language Technologies Institute, School of Computer Science, Carnegie Mellon University.

    From Topic Models to Semi-Supervised Learning: Biasing Mixed-membership Models to Exploit Topic-Indicative Features in Entity Clustering [pdf | bib]
    Ramnath Balasubramanyan, Bhavana Dalvi Mishra and William W. Cohen.
    In ECML PKDD 2013, European Conference on Machine Learning and Principles and practice of Knowledge Discovery in Databases.

    “w00t! feeling great today!” Chatter in Twitter: Identification and Prevalence [pdf | bib]
    Ramnath Balasubramanyan and Alek Kolcz.
    In ASONAM 2013, The 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

    Inferring Actor Communities from Videos[pdf | bib]
    Sumit Negi, Ramnath Balasubramanyan and Santanu Chaudhury.
    In Interspeech 2013.

    Regularization of Latent Variable Models to Obtain Sparsity [pdf | bib]
    Ramnath Balasubramanyan and William W. Cohen.
    In SDM 2013, SIAM Conference on Data Mining.

    2012

    Characterizing User-Subgroups in Flickr Group : A Block LDA Based Approach [pdf | bib]
    Sumit Negi, Ramnath Balasubramanyan and Santanu Chaudhury.
    In ICPR 2012, International Conference on Pattern Recognition, Tsukuba Science City, Japan.

    Entropic Regularization of Mixed-membership Network Models using Pseudo-observations [pdf | bib]
    Ramnath Balasubramanyan and William W. Cohen.
    In MLG 2012: Workshop on Mining and Learning with Graphs at ICML 2012.

    Evaluating Joint Modeling of Yeast Biology Literature and Protein-Protein Interaction Networks [pdf | bib]
    Ramnath Balasubramanyan, Kathryn Rivard, William W. Cohen, Jelena Jakovljevic and John Woolford.
    In BioNLP 2012: Workshop at NAACL 2012.

    Modeling Polarizing Topics: When Do Different Political Communities Respond Differently to the Same News? [pdf | bib]
    Ramnath Balasubramanyan, William W. Cohen, Doug Pierce and David Redlawsk.
    In ICWSM 2012: Proceeedings of the fourth International AAAI Conference on Weblogs and Social Media.

    2011

    What pushes their buttons? Predicting comment polarity from the content of political blog posts [pdf | bib]
    Ramnath Balasubramanyan, William W. Cohen, Doug Pierce and David Redlawsk.
    In Workshop on Language in Social Media (LSM 2011) at ACL-2011

    Combining stochastic block models and topic models [pdf | bib]
    Ramnath Balasubramanyan and William W. Cohen.
    In SDM 2011, SIAM Conference on Data Mining.

    A shorter version was presented at the  ICML 2010: Workshop on Topic Modeling [pdf | bib].

    2010

    Node Clustering in Graphs: An Empirical Study [pdf | bib]
    Ramnath Balasubramanyan, Frank Lin and William W. Cohen.
    In NIPS 2010: Workshop on Networks Across Disciplines in Theory and Applications

    From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series [pdf | bib].
    Brendan O'Connor, Ramnath Balasubramanyan, Bryan R. Routledge, and Noah A. Smith.
    In ICWSM 2010: Proceeedings of the fourth International AAAI Conference on Weblogs and Social Media.
    Press coverage - Pittsburgh Tribune-Review, CNN Tech, Economic Times BBC Radio 5 (at 13:00) and others.

    2009

    From Episodes to Sagas: Understanding the News by Identifying Temporally Related Story Sequences [pdf | bib]
    Ramnath Balasubramanyan, Frank Lin, William Cohen, Matthew Hurst and Noah A. Smith
    In ICWSM '09: Proceeedings of the third International AAAI Conference on Weblogs and Social Media (Poster).

    Information Leaks and Suggestions: A Case Study using Mozilla Thunderbird [pdf | bib]
    Vitor Carvalho, William Cohen and Ramnath Balasubramanyan
    In CEAS '09: Conference on Email and Anti-Spam

    2008

    Activity-centred Search in Email [pdf | bib]
    Einat Minkov, Ramnath Balasubramanya and William Cohen
    In CEAS '08: Conference on Email and Anti-Spam

    CutOnce- Recipient Recommendation and Leak Detection in Action [pdf | bib]
    Ramnath Balasubramanyan, Vitor Carvalho and William Cohen
    In The AAAI 2008 Workshop on Enhanced Messaging

    Earlier

    Document preprocessing for naive Bayes classification and clustering with mixture of multinomials [pdf | bib]
    Dmitry Pavlov, Ramnath Balasubramanyan, Byron Dom, Shyam Kapur and Jignashu Parikh
    In KDD '04: The tenth ACM SIGKDD international conference on Knowledge discovery and data mining (Poster).

    Selected Coursework

  • Machine Learning
  • Optimization
  • Language & Statistics
  • Language & Statistics - II
  • Information Extraction
  • Text Driven Forecasting
  • Algorithms in NLP
  • Grammars and Lexicons
  • Active Learning Seminar
  • Advanced NLP Seminar
  • Lab in NLP