Name:
 Deepayan Chakrabarti
Contact info: Facebook
1601 Willow Rd, Menlo Park, CA 94025
Email:
 deepay <at> cs <dot> cmu <dot> edu
deepay <at> fb <dot> com

Publications
 Patents
 Software
CV and Resume
 		Photos



Thesis
 Tools for Large Graph Mining [pdf, 5MB],
and a 17-page summary [pdf, 1.7MB]
Publications
   In reverse chronological order:
  1. Nonparametric Link Prediction in Dynamic Networks,
    by P. Sarkar, D. Chakrabarti, and M. Jordan, in ICML 2012.
    pdf
  2. Traffic Shaping to Optimize Ad Delivery,
    by D. Chakrabarti, and E. Vee, in EC 2012.
    pdf and ppt
  3. Threshold Conditions for Arbitrary Cascade Models on Arbitrary Networks,
    by B. Aditya Prakash, D. Chakrabarti, M. Faloutsos, N. Valler, and C. Faloutsos, in ICDM 2011:
    pdf
  4. Preserving Pairwise Relationships in Subgraphs,
    by A. Vattani, M. Gurevich, and D. Chakrabarti, in ICML 2011:
    pdf
  5. Event Summarization using Tweets,
    by D. Chakrabarti, and K. Punera, in ICWSM 2011:
    pdf
  6. Theoretical Justification of Popular Link Prediction Heuristics,
    by P. Sarkar, D. Chakrabarti, and A. W. Moore, invited to IJCAI 2011 (best paper track):
    pdf, and ppt
    The original version of this paper was published in COLT 2010 (best student paper award).
  7. Non-parametric Link Prediction,
    by P. Sarkar, D. Chakrabarti, and M. Jordan:
    pdf on arXiv
  8. Theoretical Justification of Popular Link Prediction Heuristics,
    by P. Sarkar, D. Chakrabarti, and A. W. Moore, in COLT 2010 (Best Student Paper Award):
    pdf and ppt
    A more accessible version was published in IJCAI 2011 (best paper track).
  9. The Paths More Taken: Matching DOM Trees to Search Logs for Accurate Webpage Clustering,
    by D. Chakrabarti, and R. Mehta, in WWW 2010:
    pdf and ppt
  10. Kronecker Graphs: An Approach to Modeling Networks,
    by J. Leskovec, D. Chakrabarti, J. Kleinberg, C. Faloutsos, and Z. Ghahramani, in JMLR 2010, volume 11 (Feb), pages 985-1042:
    pdf
  11. Mining Broad Latent Query Aspects from Search Sessions,
    by X. Wang, D. Chakrabarti, and K. Punera, in KDD 2009:
    pdf
  12. Quicklink Selection for Navigational Query Results,
    by D. Chakrabarti, R. Kumar, K. Punera, in WWW 2009:
    pdf and ppt
  13. ShatterPlots: Fast Tools for Mining Large Graphs,
    by A. P. Appel, D. Chakrabarti, C. Faloutsos, R. Kumar, J. Leskovec, and A. Tomkins, in SDM, 2009:
    pdf
  14. Mortal Multi-Armed Bandits,
    by D. Chakrabarti, R. Kumar, F. Radlinkski, and E. Upfal, in NIPS 2008:
    pdf and 1-page poster
  15. Generating Succinct Titles for Web URLs,
    by D. Chakrabarti, R. Kumar, and K. Punera, in KDD 2008:
    pdf and ppt
  16. A Graph-Theoretic Approach to Webpage Segmentation,
    by D. Chakrabarti, R. Kumar, and K. Punera, in WWW 2008:
    pdf and ppt
  17. Contextual Advertising by Combining Relevance with Click Feedback,
    by D. Chakrabarti, D. Agarwal, and V. Josifovski, in WWW 2008:
    pdf and ppt (1hr, 30 min)
  18. Epidemic Thresholds in Real Networks,
    by D. Chakrabarti, Y. Wang, C. Wang, J. Leskovec, and C. Faloutsos, in ACM TISSEC, 10(4), 2008:
    pdf
  19. Estimating Rates of Rare Events at Multiple Resolutions,
    by D. Agarwal, A. Broder, D. Chakrabarti, D. Diklic, V. Josifovski, and M. Sayyadian, in KDD 2007:
    pdf and ppt
  20. Multi-armed Bandit Problems with Dependent Arms,
    by S. Pandey, D. Chakrabarti, and D. Agarwal, in ICML 2007:
    pdf and ppt
  21. Page-level Template Detection via Isotonic Smoothing,
    by D. Chakrabarti, R. Kumar, and K. Punera, in WWW 2007 (pages 61-70), Banff, Canada:
    pdf and ppt
  22. Bandits for Taxonomies: A Model-based Approach,
    by S. Pandey, D. Agarwal, D. Chakrabarti, and V. Josifovski, in SDM 2007, Minneapolis, Minnesota:
    pdf and ppt
  23. Information Survival Threshold in Sensor and P2P Networks,
    by J. Leskovec, D. Chakrabarti, C. Faloutsos, S. Madden, C. Guestrin, and M. Faloutsos, in IEEE INFOCOM 2007, Anchorage, Alaska:
    pdf
  24. Visualization of Large Networks with Min-cut Plots, A-plots and R-MAT,
    by D. Chakrabarti, C. Faloutsos and Y. Zhan, in the International Journal of Human-Computer Studies, 65(5), May 2007:
    pdf
  25. Graph Mining: Laws, Generators and Algorithms,
    by D. Chakrabarti and C. Faloutsos, in ACM Computing Surveys, 38(1), 2006:
    pdf
  26. Evolutionary Clustering,
    by D. Chakrabarti, Ravi Kumar and A. Tomkins, in KDD 2006, Philadelphia, Pennsylvania:
    pdf
  27. Neighborhood Formation and Anomaly Detection in Bipartite Graphs,
    by J. Sun, H. Qu, D. Chakrabarti, and C. Faloutsos, in ICDM 2005, Houston, Texas:
    pdf
    A related paper is the following one.
  28. Relevance Search and Anomaly Detection in Bipartite Graphs,
    by J. Sun, H. Qu, D. Chakrabarti, and C. Faloutsos, in SIGKDD Explorations 7(2), 2005.
  29. Realistic, Mathematically Tractable Graph Generation and Evolution, Using Kronecker Multiplication,
    by J. Leskovec, D. Chakrabarti, J. Kleinberg, and C. Faloutsos, in PKDD 2005, Porto, Portugal:
    pdf
  30. AutoPart: Parameter-Free Graph Partitioning and Outlier Detection,
    by D. Chakrabarti, in PKDD 2004 (pages 112-124), Pisa, Italy:
    ps.gz and ppt
  31. Fully Automatic Cross-Associations,
    by D. Chakrabarti, S. Papadimitriou, D. Modha and C. Faloutsos, in KDD 2004 (pages 79-88), Washington, USA:
    pdf and ppt
  32. R-MAT: A Recursive Model for Graph Mining,
    by D. Chakrabarti, Y. Zhan and C. Faloutsos, in SIAM Data Mining 2004, Orlando, Florida, USA:
    pdf
    This is the basis for the new Graph500 supercomputer benchmark.
  33. NetMine: New Mining Tools for Large Graphs,
    by D. Chakrabarti, Y. Zhan, D. Blandford, C. Faloutsos and G. Blelloch, in the SDM 2004 Workshop on Link Analysis, Counter-terrorism and Privacy:
    pdf, ps.gz and ppt
  34. A Real-Time Expectation Maximization Algorithm for Acquiring Multi-Planar Maps of Indoor Environments with Mobile Robots,
    by S. Thrun, C. Martin, Y. Liu, D. Hahnel, R. Emery-Montemerlo, D. Chakrabarti, and W. Burgard, in IEEE Transactions on Robotics and Automation, 20 (3), pp. 433-442, 2004:
    pdf
  35. Epidemic Spreading in Real Networks: An Eigenvalue Viewpoint,
    by Y. Wang, D. Chakrabarti, C. Wang and C. Faloutsos, in SRDS 2003 (pages 25-34), Florence, Italy:
    pdf, ps.gz and ppt
  36. F4: Large Scale Automated Forecasting using Fractals,
    by D. Chakrabarti and C. Faloutsos, in CIKM 2002 (pages 2-9), McLean, Virginia, USA:
    pdf, ps.gz and ppt
  37. Using EM to Learn 3D Models of Indoor Environments with Mobile Robots,
    by Y. Liu, R. Emery, D. Chakrabarti, W. Burgard and S. Thrun, in ICML 2001 (pages 329-336), Williamstown, MA, USA:
    pdf and ps.gz
  38. A Method for Acquiring Multi-Planar Volumetric Models with Mobile Robots based on the EM Algorithm,
    by S. Thrun, W. Burgard, D. Chakrabarti, R. Emery, and Y. Liu, in ISRR 2001:
    pdf
Invited Talks and Tutorials
  1. Nonparametric Link Prediction in Dynamic Graphs,
    by P. Sarkar, D. Chakrabarti, and M. Jordan, in the Purdue Statistics Symposium, 2012:
    ppt
  2. A Theoretical Justification of Link Prediction Heuristics,
    by P. Sarkar, D. Chakrabarti, and A. Moore, in MLG 2012:
    ppt
  3. Statistical Challenges in Computational Advertising,
    by D. Chakrabarti and D. Agarwal, in KDD 2009 and CIKM 2008:
    ppt
  4. Clustering Applications at Yahoo!,
    by D. Chakrabarti, in NIPS 2009 Workshop on Clustering:
    ppt
Books and Book Chapters
  1. Graph Mining: Laws, Tools, and Case Studies,
    by D. Chakrabarti, and C. Faloutsos, published by Morgan Claypool in 2012.
  2. Graph Mining,
    by D. Chakrabarti, in Encyclopedia of Machine Learning, 2010, Part 8:
    link
  3. Graph Mining: Laws and Generators,
    by D. Chakrabarti, C. Faloutsos, and M. McGlohon, in Managing and Mining Graph Data, 2010:
    link
  4. Graph Patterns and the R-MAT Generator,
    by D. Chakrabarti, and C. Faloutsos, in Mining Graph Data, edited by L. Holder and D. Cook, published by Wiley in 2006:
    book on Amazon
Technical Reports
  1. ShatterPlots: Fast Tools for Mining Large Graphs,
    by A. P. Apple, D. Chakrabarti, C. Faloutsos, R. Kumar, J. Leskovec, and A. Tomkins, in 2008: CMU-ML-08-116:
    pdf
  2. Fully Automatic Cross-Associations,
    by D. Chakrabarti, S. Papadimitriou, D. S. Modha and C. Faloutsos, in 2004: CMU-CALD-04-107:
    pdf.gz
  3. Large-scale Automated Forecasting using Fractals,
    by D. Chakrabarti, in 2002: CMU-CALD-02-101:
    pdf
Patents
  1. System and method for detecting a web page template , Patent number 7987417,
    by D. Chakrabarti, K. Punera, and S. Ravikumar.
  2. Method for segmenting webpages by parsing webpages into document object modules (DOMs) and creating weighted graphs , Patent number 7974934,
    by S. Ravikumar, D. Chakrabarti, and K. Punera.
  3. System and method for determining impression volumes of content items in a taxonomy hierarchy , Patent number 7921073,
    by D. Agarwal, D. Diklic, D. Chakrabarti, A. Broder, and V. Josifovski.
  4. System and method for smoothing hierarchical data using isotonic regression , Patent number 7870474,
    by D. Chakrabarti, K. Punera, and S. Ravikumar.
  5. System and method using hierarchical clustering for evolutionary clustering of sequential data sets , Patent number 7734629,
    by D. Chakrabarti, S. Ravikumar, and A. Tomkins.
  6. Customization of information retrieval through user-supplied code, Patent number 6611834,
    by G. Aggarwal, D. Chakrabarti, P. K. Dubey, N. P. Garg, S. Ghosal, A. K. Gupta, A. Kulshreshtha, Ashutosh and S. K. V. Murthy
  7. Patents Filed: Named as a co-inventor in 18 patents (applied and issued) and 2 defensive publications.
Honors
  1. Our COLT 2010 work received the best student paper award.
  2. Our R-MAT work is the basis for the new Graph500 supercomputer benchmark.
  3. Siebel Scholar, 2002
Software
  1. The CrossAssociations package for automatically grouping nodes in a large graph
  2. The NetMine package for extracting patterns from large graphs
  3. The F4 non-linear time series forecasting package