Nandana Sengupta

Postdoctoral Scholar, University of Chicago

My research revolves around improving the predictive performance of traditional Econometric models using modern Statistics and Machine Learning. I'm very interested in developing these techniques with a special focus on Public Policy applications. I am currently a doctoral candidate of Economics at the Tepper School of Business, Carnegie Mellon University. I also hold a Bachelor's degree in Physics from St. Stephen’s College (New Delhi, India) and a Master's degree in Development Economics from Indira Gandhi Institute of Development Research (Mumbai, India).
 
I've had the opportunity to participate in a number of interdisciplinary research groups including the Machine Learning in Social Sciences group at Carnegie Mellon University and the Computational Social Science Workshop at the Santa Fe Institute. I’m looking forward to continuing this line of work at the Knowledge Lab, where my projects will include developing computational tools to more deeply engage user input as well as developing new techniques to assess and predict the impact of academic research.