My main research area is in data management, with a special focus on enabling data analysis tasks on private, dirty, and federated data, which are fundamental to data-driven population research. In particular, I'm interested in helping domain experts to collect, analyze, release large scale of population data with privacy and fairness guarantees, and building computer systems to support those activities for interdisciplinary population researchers, teachers, and professionals in MPC.
Chang Ge is an assistant professor in the Department of Computer Science and Engineering at the University of Minnesota. He is broadly interested in data management, with a special focus on new algorithms and systems for enabling large-scale data analysis in the presence of private, dirty and siloed data. In addition to publications at SIGMOD, VLDB and ICDE, his research has been adopted into the products and services by Apple, Microsoft, IBM and SAP.