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Make Data Work
Oct 15–17, 2014 • New York, NY

The Aha! Moment: From Data to Insight

Dafna Shahaf (The Hebrew University of Jerusalem)
4:30pm–5:00pm Wednesday, 10/15/2014
Hardcore Data Science
Location: E14 / E15
Average rating: ****.
(4.50, 6 ratings)
Slides:   1-PPTX 

The amount of data in the world is increasing at incredible rates. Large-scale data has potential to transform almost every aspect of our world, from science to business; for this potential to be realized, we must turn data into insight. In this talk, Dafna will describe two of his efforts to address this problem computationally:

The first project, Metro Maps of Information, aims to help people understand the underlying structure of complex topics, such as news stories or research areas. Metro Maps are structured summaries that can help us understand the information landscape, connect the dots between pieces of information, and uncover the big picture.

The second project proposes a framework for automatic discovery of insightful connections in data. In particular, we focus on identifying gaps in medical knowledge: our system recommends directions of research that are both novel and promising.

Dafna will formulate both problems mathematically and provide efficient, scalable methods for solving them. User studies on real-world datasets demonstrate that our methods help users acquire insight efficiently across multiple domains.

Photo of Dafna Shahaf

Dafna Shahaf

The Hebrew University of Jerusalem

Dafna Shahaf is a postdoctoral fellow at Stanford University. She received her Ph.D. from Carnegie Mellon University; prior to that, she earned an M.S. from the University of Illinois at Urbana-Champaign and a B.Sc. from Tel-Aviv university. Dafna’s research focuses on helping people make sense of massive amounts of data. She has won a best research paper award at KDD 2010, a Microsoft Research Fellowship, a Siebel Scholarship, and a Magic Grant for innovative ideas.

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Ojustwin Naik
10/15/2014 2:11pm EDT

Dafna, Excellent session today. Very impressed by the work you have done on the Metro Maps project. What is the technology stack you used to implement Metro Maps? Are the components open source or proprietary? Thanks!