Gunce E. Walton is a manager of a development team in SAS R&D. She researches, implements, and oversees econometric techniques in SAS Econometrics procedures and action sets for cross-sectional and panel data analysis. She also plays a critical role in promoting SAS Econometrics products. Her recent research focus has been on implementation of machine learning techniques for causal analysis in policy research. Prior to working at SAS, Gunce was an assistant professor at Instituto Tecnologico Autonomo de Mexico, Mexico City. She taught graduate and undergraduate level empirical micro-econometrics classes. She has many published articles in the areas of instrumental variable estimation, instrument selection methods, and dynamic panel data model estimation. Gunce has a Ph.D. in Economics from North Carolina State University.
SAS' Gunce Walton introduces to you a new scoring capability, how it utilizes Deep Neural Networks (DNNs) and shares use cases with PROC DEEPCAUSAL.
