Latest Seminar

Abstract: Despite decades since court-ordered desegregation mandates, public schools across the US remain segregated by race, socioeconomic status, and other demographics. Segregation is concerning in educational settings because it can exacerbate achievement gaps and impede the development of empathic connections across lines of difference. This talk presents ongoing work from a researcher-practitioner partnership with a large US public school district through the recent “Fostering Diverse Schools Grant” by the Department of Education. It describes the development of a community + machine framework for designing new school attendance boundaries—a popular mechanism for determining student assignments to schools, but one that often recapitulates underlying patterns of residential segregation in educational settings. Through a combination of human-centered design practices and multi-objective algorithmic redistricting, the project seeks to diversify school attendance boundaries while also attending to concerns about travel distances, school feeder patterns, and other factors voiced by families, students, and staff members in the district.  The talk additionally describes community feedback in response to this contentious topic, and efforts to capture input from historically underheard voices in order to foster a fairer and more representative policymaking process. It concludes with reflections on the challenges and opportunities of conducting this work in light of recent federal efforts to curtail diversity-promoting initiatives in public education.

Bio: Nabeel is an Assistant Professor of Design and Data Analysis at Northeastern University between the College of Arts, Media and Design and the D'Amore-McKim School of Business, where he directs the Plural Connections Group (PCG). PCG’s mission is to use tools from computation and design to foster pluralism—an inclusive response to differences in society—in ways that promote educational, economic, and social inclusion. More specifically, he seeks to apply methods from machine learning, data science, and civic design to foster connection, mutual support, and learning across segregated spaces like: 1) educational inequalities stemming from segregated schools and neighborhoods, and 2) echo chambers and empathy gaps in social and mainstream media environments.

Nabeel received his PhD from the MIT Media Lab. Prior to graduate school, he worked as a Product Manager and member of the analytics team at Khan Academy, where he helped design digital learning experiences. He studied Applied Mathematics and Computer Science at Brown University as an undergraduate, and received Masters degrees in Education and Information Engineering (Machine Learning) at the University of Oxford as a Rhodes Scholar.