Michael Gubanov

Postdoctoral Associate
Computer Science and Artifical Intelligence Laboratory (CSAIL)
Massachusetts Institute of Technology

The Stata Center
32 Vassar St., 32-G904B
Cambridge, MA 02139

About

I am a Postdoc at MIT CSAIL working on Web-search, Large-scale data integration, analytics, and machine-learning with Michael Stonebraker.

Before MIT, I earned my PhD in Computer Science from the University of Washington, working with IBM Almaden Research Center. During my PhD program I also spent some time at Google doing research on large-scale machine learning and Web-search that has been successfully deployed on production clusters at Google. I completed my undergraduate education at St. Petersburg National Research University ITMO (ACM-ICPC World Champions 2013).

Selected publications

  1. Large-scale Semantic Profile Extraction  [bib] [pdf]
    Michael Gubanov, Michael Stonebraker EDBT 2014, Athens, Greece
  2. Text and Structured Data Fusion in DataTamer at Scale  [bib] [pdf]
    Michael Gubanov, Michael Stonebraker, Daniel Bruckner IEEE ICDE 2014, Chicago, Illinois
  3. ReadFast: High-relevance Search-engine for Big Text [bib] [pdf]
    Michael Gubanov, Anna Pyayt. ACM CIKM 2013, San Francisco, California
  4. Using Unified Famous Objects (UFO) to Automate Alzheimer's Disease Diagnostics. [bib] [pdf]
    Michael Gubanov, Linda Shapiro. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2010, Atlanta, Georgia
  5. IBM UFO Repository: Object-oriented Data Integration [bib] [pdf] [book]
    Michael Gubanov, Lucian Popa, Howard Ho, Hamid Pirahesh, Jeng-Yih Chang, Shr-Chang Chen. VLDB 2009, Lyon, France

Selected talks

  1. Large-scale sublinear logistic regression
    Intel Research, Santa Clara, CA, 2014.
  2. Taming Big Data Variety
    State University of New York at Stony Brook, Stony Brook, NY, 2014.
  3. Taming Big Data Variety
    Florida Atlantic University, Boca Raton, FL, 2014.
  4. Fusion of text and structured data at scale
    MIT CSAIL, Cambridge, MA, 2013.
  5. Towards gaining control over Big medical data.
    University of California, Irvine, CA, 2012.
  6. Towards gaining control over information overflow.
    University of Central Florida, Orlando, FL, 2012.
  7. Towards gaining control over information overflow.
    University of Kentucky, Lexington, KY, 2012.
  8. Simplifying access to structured and unstructured data.
    Stanford University, Stanford, CA, 2011.

Links

Massachusetts Institute of Technology MIT Database Group

© Copyright 2014 Michael Gubanov. All rights reserved.