Research Interests

• causal inference: randomization inference, networks, interference, spillovers (see also residual randomization)
• machine learning: large-scale inference, stochastic gradient descent (SGD, see implicit SGD).

Education

• 2016 -- Ph.D. in Statistics, Harvard University (Advisors: Edo Airoldi, David Parkes, and Don Rubin)
• 2011 -- Masters in Computer Science, Harvard University (Advisor: David Parkes)
• 2006 -- M.Eng. in Electrical and Computer Engineering, Aristotle University (Advisor: Pericles Mitkas)