Juliana Freire

Juliana Freire is a Professor at New York University, affiliated with the Department of Computer Science. She is also an Institute Professor at the NYU Tandon School of Engineering and a Professor of Data Science. Her research focuses on data management, analytics, visualization, and data science engineering. She has developed methods and systems that enable users to obtain trustworthy insights from data, spanning topics such as large-scale data analysis, visualization, machine learning, and provenance management. Freire has received numerous awards, including ACM Fellow and AAAS Fellow honors, and has been recognized for her contributions to the database and Web research communities. Her work has been funded by various organizations, including the National Science Foundation, DARPA, and Google.

Juliana Freire is a researcher at New York University, focusing on data management, visualization, provenance, reproducibility, and big data. Her work addresses challenges in ensuring the reproducibility of scientific results and the management of complex data workflows. She has contributed to the development of open provenance models and tools like VisTrails, which integrate visualization with data management. Her research also explores the visualization of large-scale urban data and the use of provenance to support computational reproducibility. Freire's publications highlight the importance of transparency and replicability in scientific workflows and the role of provenance in enabling trust in data-driven research.