September 9, 2016 – September 10, 2016

Digital Economics Conference

Location: New York, NY, USA

Friday, September 9

Time Session Speaker
8:00-8:30
Breakfast and welcome
8:30-10:00
Keynote: Causal Inference in Machine Learning
  • Susan Athey, Stanford University
  • Alex Belloni, Duke University
  • Discussant: Xiaohong Chen, Yale University
10:00-10:30
Coffee
10:30-12:00
Session 1: New Approaches to Causal Inference
  • Greg Lewis, Microsoft Research
  • Denis Nekipelov, University of Virginia
  • Amit Sharma, Microsoft Research
  • David Sontag, New York University
12:00-1:00
Lunch
1:00-3:00
Session 2: Understanding Demand
  • David Blei, Columbia University
  • Matt Harding, University of California–Irvine
  • Matt Taddy, Microsoft Research
3:00-3:30
Coffee
3:30-5:00
Session 3: Learning from Phone and Image Data
  • Daniel Bjorkegren, Brown University
  • Nikil Naik, Massachusetts Institute of Technology
  • Discussant: Gautam Rao, Harvard University

Saturday, September 10

Time Session Speaker
8:00-8:30
Breakfast
8:30-10:00
Keynote: Machine Learning for Economic Policy
  • Sendhil Mullainathan, Harvard University
  • Serena Ng, Columbia University
  • Discussant: Emily Oster, Brown University
10:00-10:30
Coffee
10:30-12:30
Session 4: Media and Advertising
  • Shawndra Hill, Microsoft Research
  • Markus Mobius, Microsoft Research
  • Justin Rao, Microsoft Research
  • Discussant: Dean Eckles, Massachusetts Institute of Technology
12:30
Close