I’m a Data Scientist and PhD Candidate in Technology and Social Behaviour, a joint program in computer science and communication at Northwestern University. I work with Professor Ágnes Horvát in the Laboratory on Innovation, Networks, and Knowledge (LINK) where we strive to understand and predict group behavior in networks and socio-technical systems. My research, at the intersection of machine learning and complex networks analysis, examines how people’s social networks and their opinion diversity impact their judgments in collaborative settings. The goal of my research is to devise innovative ways to support reliable collective decision-making in complex settings by identifying novel and robust collective intelligence signals and by systematically investigating the primary conditions necessary to generate crowd wisdom. As a problem-solving approach, I apply collective intelligence concepts to solve high-stakes problems, for instance, to generate more informed and inclusive decisions in group settings, improve access to capital for groups underserved by traditional financial institutions, and to help design better strategies for implementing peace agreements after civil wars.
July, 2021: I will be presenting our work on An Experimental Study of the Effectiveness of Crowd Signals in Online Fundraising at the 7th International Conference on Computational Social Science (IC2S2).
May, 2021: I’m happy to announce that I’ve been awarded a Presidential Fellowship by Northwestern University.
April, 2021: Our recent work on collective intelligence in online fundraising1, auditing the Alexa voice assistant for information quality2, and characterizing COVID-19 online media3 is now available online.
February, 2021: I presented our work on Auditing the Information Quality of News-Related Queries on the Alexa Voice Assistant at the Computation + Journalism Symposium 2021: Data Journalism in an Expanded Field.