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Luddy School of
Informatics, Computing, and Engineering

  • Home
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David J Crandall

Director of Graduate Studies for Computer Science

Associate Professor of Informatics and Computing
Director of Center for Machine Learning

Contact Information

djcran@indiana.edu
(812) 856-1115
611 N. Park Ave
http://www.cs.indiana.edu/~djcran/

Education

  • Ph.D. in Computer Science at Cornell University, 2008
  • M.S. in Computer Science at Cornell University, 2007
  • B.S., M.S. in Computer Science and Engineering at The Pennsylvania State University, 2001

Courses Taught at Luddy

  • B490 Image Processing and Recognition
  • B551 Elements of Artificial Intelligence
  • B554 Probabilistic approaches to Artificial Intelligence
  • B657 Computer Vision
  • I210 Information Infrastructure I
  • I399 Undergraduate Research Methods for Informatics
  • I427 Search Informatics

Biography

David Crandall received the Ph.D. in computer science from Cornell University in 2008 and the M.S. and B.S. degrees in computer science and engineering from the Pennsylvania State University, University Park, in 2001. He worked as a postdoctoral associate at Cornell from 2008-2010, and as a research scientist at Eastman Kodak Company from 2001-2003.

Dr. Crandall’s main research interest is computer vision, the area of computer science that tries to design algorithms that can “see”. He is particularly interested in visual object recognition and scene understanding. He is also interested in other problems that involve analyzing and modeling large amounts of uncertain data, like mining data from the web and from online social networking sites.

Take a look at Dr. Crandall's lab website.

Research Areas

  • Artificial Intelligence
  • Machine Learning
  • Data Science
  • Teaching and Learning
  • HCI@Luddy - Crosscutting
  • Animal Informatics
  • Artificial Intelligence and Machine Learning
  • Computer Vision, Speech, and Music Processing
  • Animal Computer Interaction
  • Intelligent Interactive Systems

Centers

  • Center for Complex Networks and Systems Research
  • Center for Machine Learning
  • Computer Vision Lab
  • Digital Science Center
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