I am passionate about tackling complex problems, wherever they may be. To that end, I balance my time between research in behavioral economics, machine learning applications to a wide variety of topics, and collaborating with local community leaders to build up opportunities and break down barriers to success. This site is a venue for me to house milestones on those three fronts and to solicit feedback on my approaches.
This site will evolve as my interests and projects take me in various directions. But I hope the unifying theme through all the iterations is a constant commitment to a scientific approach to understanding and improving the world around me.
Diag is a Behavioral Science PhD student at the University of Chicago Booth School of Business, where he studies various topics at the intersection of big data and behavioral economics. Much of his research has been informed by his industry experience as an economic consultant for corporate litigation and as a data analyst at a variety of organizations, ranging from a small DC startup to the Board of Governors of the Federal Reserve. His research blends a mix of theoretical, experimental, and field methods to describe and predict how people act on information. Before matriculating to UChicago, he earned a Master’s degree in Mathematics & Statistics at Georgetown University while conducting research under the supervision of Dr. Kimberly Sellers in the Mathematics department. Prior to that, he earned Bachelor’s degrees in Economics and Management at Penn State under the keen tutelage of Jamie Campbell.
Diag was born in Washington, DC and grew up bouncing between Washington, DC; London, England; and Kingston, Jamaica. Across these experiences he witnessed firsthand the process and peril of non-inclusive economic development. He is now committed to building coalitions focused on inclusive economic growth alongside his academic research.
A more formal summary of Diag's experience can be found in his CV.
I have diverse experiences ranging from direct implementation of ML applications to providing guidance on high-level strategic issues. I have developed pricing algorithms and recommendation systems, built R packages and APIs, contributed to industry white papers, as well as directly advised executives of small and large companies on strategic data issues.
As a researcher, I use tools from economics, psychology, and machine learning to study how people process information and update their beliefs about the world. The following projects document some of the progress I’ve made.
Works in Progress:
The Impact of Disamenities on Housing Prices: Evidence from the 1992 Los Angeles Riots
All Predictions Are Created Equal: Systematic Misjudgments in the Reliability of Forecasts (w/ Jane Risen)
Group Conformity and the Fear of Indecision: Evidence from Louisiana Juries and the Lab (w/ Yuji Winet)
Strong communities are the bedrock for our individual and collective growth. Nonetheless, there are many tangled social and institutional forces that threaten communities I call home, and many others like them around the country. For this reason, I am committed to contributing to grassroots efforts to facilitate wealth creation, including affordable housing, education, and criminal justice reform.