I am a doctoral researcher in economics, on the job market 2024-25. My focus is developing machine learning tools for macroeconomic analysis, to obtain useful information for guiding important policy decisions.

My job market paper proposes a Transformer network for non-linear state space modeling. The input definition, architecture and training process are customized for nowcasting dynamic factors from small macroeconomic time series datasets. Conventional models, such as the Kalman filter, can be inserted as a prior to guide the estimation. The results can be interpreted with Attention matrices, which show the impact of each variable's every lag on the output.