Presentations

You can browse through some of my slides on Issuu.

  1. Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
    University of Maryland

  2. Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
    Ohio State University

  3. Dense subgraph discovery
    Google Research

  4. Large-Scale Graph Mining
    IBM T.J. Watson Research Center

  5. Streaming Graph Partitioning in the Planted Partition Model
    ACM Conference on Online Social Networks (COSN’15)

  6. Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
    Stanford University

  7. Scalable Large Near-Clique Detection in Large-Scale Networks
    Signals, Inference, and Networks (SINE) Seminar
    University of Illinois Urbana-Champaign

  8. Dense subgraph discovery
    Data-driven Algorithmics

  9. Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
    21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2015)

  10. Dense subgraph discovery
    Tutorial at 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2015)

  11. Scalable dense subgraph discovery
    Random Structures and Algorithms (RSA), July ’15

  12. Scalable dense subgraph discovery
    International Symposium on Optimization (ISMP), July ’15

  13. Space- and Time-Efficient Algorithms for Maintaining Dense Subgraphs on One-Pass Dynamic Streams
    STOC 2015, June ’15

  14. Scalable dense subgraph discovery
    University of Cyprus, June ’15

  15. Provably Fast Inference of Latent Features from Networks
    24th International World Wide Web Conference (WWW 2015), May’15

  16. The k-clique Densest Subgraph Problem
    24th International World Wide Web Conference (WWW 2015), May’15

  17. Algorithmic Analysis of Large Datasets
    Universitat Pompeu Fabra, May ’15

  18. Modern Data Mining Algorithms
    Draper Laboratory, December ’14

  19. Algorithmic Analysis of Large Datasets
    SEAS Harvard University, November ’14
    Youtube video

  20. Algorithmic Analysis of Large Datasets (pptx)
    Brown University, May ’14
    Host: Philip Klein

  21. Large-Scale Graph Mining
    Imperial College London, May ’14
    Host: Moez Draief

  22. Algorithmic Analysis of Large Datasets
    Google NYC, April ’14
    Host: Vahab Mirrokni

  23. Mathematical Techniques for Modeling and Analyzing Large Graphs (pdf)
    Aalto Science Institute, January ’14, Helsinki

  24. Modeling Intratumor Gene Copy Number Heterogeneity using Fluorescence in Situ Hybridization data (pptx, pdf)
    WABI ’13, September ’13, Nice

  25. Fennel: Streaming Graph Partitioning for Massive Scale Graphs (pdf)
    MASSIVE ’13, September ’13, Nice

  26. Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees (pptx, pdf)
    KDD ’13, August ’13, Chicago

  27. Mathematical and Algorithmic Analysis of Network and Biological data
    Thesis Defense, Carnegie Mellon University, May 2013

  28. Processing, Analyzing and Mining Big Graph Data
    Machine learning lunch seminar, Carnegie Mellon University, April 2013
    Video

  29. Random Graphs and Complex Networks
    Guest lecture, TELCOM2125: Network Science and Analysis
    Host: Konstantinos Pelechrinis
    April 2013

  30. Mathematical and Algorithmic Analysis of Biological data and Networks
    Abstract
    Brown University, April 2013
    Host: Eli Upfal

  31. Fennel: Streaming Graph Partitioning for Massive Scale Graphs
    Microsoft Research, Cambridge UK, November 2012
    Host: Milan Vojnovic

  32. On Certain Topics on Networks and Optimization: Theorems, Algorithms and Applications
    Yahoo! Research Barcelona, Barcelona, August 2012
    Host: Aris Gionis

  33. On Certain Properties of Random Apollonian Networks (pptx, pdf)
    WAW 2012, June 2012, Halifax

  34. Triangle Counting and Vertex Similarity
    Canadian Mathematical Society, December 2011, Toronto
    Invited Speaker

  35. High Degree Vertices, Eigenvalues and Diameter of Random Apollonian Networks
    15th International Conference on Random Structures and Algorithms RSA 2011, Atlanta

  36. Counting Triangles in Real-World Networks
    SIAM Conference on Computational Science and Engineering (CSE11), Reno Invited Speaker

  37. Approximate Dynamic Programming using Halfspace Queries and Multiscale Monge Analysis (pptx)
    SODA 2011, San Francisco

  38. Approximate Dynamic Programming and Denoising aCGH data (pptx)
    Machine Learning Seminar 2011, Carnegie Mellon University
    Video

  39. Efficient Triangle Counting via Degree-based Partitioning (pptx)
    Machine Learning Seminar 2011, Carnegie Mellon University
    Video

  40. Approximate Dynamic Programming and Denoising aCGH data (pptx)
    ACO Seminar 2011, Carnegie Mellon University

  41. Efficient Triangle Counting via Degree-based Partitioning (pptx)
    ACO Seminar 2011, Carnegie Mellon University

  42. Efficient Triangle Counting via Degree-based Partitioning (pptx)
    WAW 2010, Stanford University

  43. The Determinant of Random Bernoulli Matrices
    Discrete Math 21701, Carnegie Mellon University

  44. Approximate Dynamic Programming
    Carnegie Mellon University

  45. Unmixing of Tumor States in aCGH data
    Carnegie Mellon University

  46. Data Mining with MapReduce: Graph and Tensor Algorithms with Applications
    Master Thesis, Carnegie Mellon University

  47. MACH: Fast Randomized Tensor Decompositions
    SIAM Data Mining 2010, Columbus OH

  48. Algorithms for Denoising aCGH Data
    MLD Speaking Skills, Carnegie Mellon University

  49. Welcome Talk (MLD Open House) (welcome.ppt)
    MLD Open House, Carnegie Mellon University

  50. Spectral Counting of Triangles in Power-Law Networks via Element-Wise Sparsification
    ASONAM 2009, Athens

  51. DOULION: Counting Triangles in Massive Graphs with a Coin
    KDD 2009, Paris

  52. Approximate Triangle Counting
    Poster Presentation, Machine Learning Summer School 2009, Chicago

  53. Basics of Spectral Graph Theory
    Carnegie Mellon University, Paris

  54. On Polygonal Numbers and Fermat's Conjecture
    Additive Number Theory, Carnegie Mellon University

  55. Graph Mining Guest Lecture 15-826 Multimedia Databases and Data Mining (CMU)

  56. Fast Counting of Triangles in Large Real Networks without counting: Algorithms and Laws (pps)
    IEEE Data Mining (ICDM), 2008 Italy

  57. Fast Counting of triangles in large networks: Algorithms and laws (ppt)
    Theory Seminar of Rensselaer Polytechnic Institute
    Host: Petros Drineas
    Invited Talk

  58. Two heads better than one: pattern discovery in time-evolving multi-aspect data (ppt)
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
    (ECML-PKDD 2008), 2008 Belgium