I am a Postdoctoral Associate at the MIT Digital Supply Chain Transformation Lab,
Center for Transportation Logistics. My research at MIT focuses on two main areas. Firstly, I am studying
human-AI collaboration in demand planning through a field experiment conducted in collaboration with a major multinational fast-moving consumer goods (FMCG) company and its
customer. Using Mediation Analyses, I am investigating the conditions under which human-AI collaboration is beneficial and when the algorithm version appears Secondly, I am empirically analyzing
the impact of supply chain digitalization on firm productivity. To measure digitalization levels, I am using a firm's job posting data and employing text analytic tools to
develop a corresponding measure. The empirical findings from a large-scale panel data spanning from 2010 to 2020 reveal a significant correlation between this measure and
firm productivity.
I received my Ph.D. in Business Analytics at Tippie College of Business, University of Iowa,
under the guidance of Professor Jennifer Blackhurst
and Professor Gautam Pant. My dissertation focuses on applying econometrics,
machine learning/AI, and simulation to gain insights into the risks and disruptions in global supply chain networks. The papers derived from my dissertation have
received attention from both practitioners and policymakers. Notably, one of my research projects was recognized by the government with a grant of USD 189,000 to
implement and create a real-time dashboard for monitoring industries.
As part of my research, I analyze the influence of economic policy uncertainty (EPU) and political instability on firm performance and structure. Moreover, I have been working on resilient supply network (RSCN) design problems since my Master's program. Before starting my Ph.D. at the University of Iowa, I was in the Industrial Engineering (IE) program. This means my earlier works are focused on applying Operation Research (OR) tools for designing supply networks that are resilient against disruptions yet optimized and efficient during normal situations.
