Machine Learning and Econometrics

This two-day conference covers empirical applications and methodological advances in data science and econometrics, with a special focus on the applications of machine learning and computational statistics to Social Science.

The goal is to foster the exchange of ideas between different scientific communities by bringing together Statisticians, Computer Scientists and Economists, which each have their unique perspective on the recent expansion of data availability and the corresponding progress in data analysis.

Please see below for a list of speakers.

Angelos Alexopoulos (Cambridge)

Mirko Draca (Warwick) 

Hedibert Freitas Lopes (Insper)

Arthur Gretton (UCL) 

Mario Gutierrez-Roig (Warwick) 

Stephen Hansen (Oxford)

Matt Harding (UC Irvine) 

Marcin Kacperczyk (Imperial College)

Ioannis Kosmidis (Warwick)

Hyungsik Roger Moon (USC)  

Lars Nesheim (UCL)

Sofia Olhede (UCL)

Katerina Petrova (St Andrews) 

Nick Polson (Chicago Booth)

Jan Spiess (Harvard)

Vasilis Syrgkanis (Microsoft Research) 

Michalis Titsias (Athens)