I have led a fascinating and challenging 15-year career helping the U.S. government respond to complex political, governance, and security crises in Africa, the Middle East, and Eastern Europe. I've also helped U.S. agencies strategize and learn to better work together to achieve national security objectives. My mother was a social worker for the City of Chicago, so ever since I was a kid I wanted to understand why people had such different life experiences from one another--why some lives were plagued by conflict and others weren't. In grad school I used hyper-local field research methods and hyper-macro econometric regression approaches to distill relevant factors, and came to the conclusion that a person's many communities (school, work, religious, political, sports, and other more deeply structural and historical factors etc.) strongly influence why they make decisions that they make, or fail/choose not to make decisions at all. Advancements in AI & big data analysis have inspired me to dust off my quantitative analysis skills and take some online courses to catch up on the evolving world of use cases for machine learning in particular; I want to use ML and probably also some big data analytical approaches to gain useful insights from micro-data that we can harness from the web and from app-based research tools to increase the nuance with which we understand communities that we are trying to help or influence overseas.
Other than beefing up my AI and research methods knowledge, in my spare time I ski and hike, pay attention to some pet social justice and counter-violence projects I'm working on, hang out with my husband and dogs, garden, read a ton, try not to feel bad for failing to keep up with my podcast downloads, and endlessly browse AirBNB homes and zillow just to look around.