Christina develops and leads teams and services that support Northwestern researchers throughout the research data lifecycle, including data science, research software engineering, data visualization, and research data management. She has collaborated with Northwestern researchers on widely varied projects, including applying natural language processing (NLP), predictive modeling, and visualization techniques to narrative student feedback; assessing gender and racial bias in student feedback; developing visualizations of the international art market; analyzing MS patients’ healthcare utilization patterns; and building customized tools for data collection and coding. She developed and teaches workshops for Northwestern researchers on multiple topics, but she specializes in R.
She is active with national organizations that support those working in research computing and data (RCD) and research software engineering (RSE) careers. She has is a founding member of the US Research Software Engineer Association (US-RSE) Steering Committee, founding co-coordinator of the RSE Group Leaders’ Network (RSE-GLN), former co-chair of the Campus Research Computing Consortium (CaRCC) RCD Professionalization Working Group, an organizer of the Academic Data Science Alliance (ADSA)/US-RSE 2022 Career Support Workshop, and a regular presenter at the PEARC conference. She has mentored aspiring data scientists and research software engineers through programs such as Women in Data Science (WiDS) Chicago and rOpenSci Champions.
In addition to teaching workshops through Research Computing and Data Services, Christina teaches Data Visualization and Storytelling in Northwestern’s MS in Health Analytics program. Her background is in computational social science. Prior to Northwestern, she supported researchers at the Stanford Graduate School of Business and a variety of government clients working with a small company in Washington, DC. She has an MS in statistics and PhD in political science from Stanford University.