With a hybrid background in physics, computer science, film, and media, Dr. Horvát deploys social computing to measure, understand, and forecast the collective behavior of connected crowds in large-scale sociotechnical systems like peer-to-peer platforms. Her current research develops empirical and theoretical methods to support creativity and predict success in culture industries, identify expressions of collective intelligence and opportunities for innovation in crowdsourcing communities, as well as detect shared misconceptions and biases in online capital markets. Her work uses an interdisciplinary data-driven approach and builds on techniques from network science, machine learning, statistics, and exploratory visualization. She developed and teaches the ‘Cultural Analytics’ graduate course that is designed to train students for careers at the intersection of creative occupations and Data Science. She serves on the editorial board of PLOS One. Her current research is funded by the National Science Foundation through a CISE CRII award.