About MeI am an Assistant Professor of Econometrics and Statistics at the University of Chicago, Booth School of Business.
I received the Ph.D. in Statistics from Harvard University under the supervision of Edo Airoldi, David Parkes and Don Rubin in 2016, and the MS in Computer Science (from Harvard) under the supervision of David Parkes in 2011.
My research is split in two areas:
- ♦causal inference in complex systems, such as networks or markets, with focus on nonparametric randomization methods (also known as randomization inference) and machine learning;
- ♦statistical machine learning, with focus on large-scale statistical inference through stochastic gradient descent (SGD) with stable implicit updates.
Randomization tests of causal effects with interference between units, with Basse, G; Feller, A.
Biometrika, 2018, forthcoming
Stochastic gradient methods for estimation with large datasets, with Tran, D.; Airoldi, EM.
Journal of Statistical Software, 2018, forthcoming
Convergence diagnostics for stochastic gradient descent with constant step size, with Chee, J.
AI and Statistics, 2018 (AISTATS'18)
Asymptotic and finite-sample properties of estimators based on stochastic gradients, with Airoldi, EM.
Annals of Statistics, Volume 45, Number 4 (2017), 1694-1727