Marco Serafini was awarded a grant from the National Science Foundation for the project “Transparently Scaling Graph Neural Network Training to Large-Scale Models and Graphs”. Summary: Large-scale graphs with billions of edges are ubiquitous in many industry, science, and engineering fields such as recommendation systems, social graph analysis, knowledge bases, […]

Peter Haas and Alexandra Meliou were awarded a $600K grant from the National Science Foundation for the project “Scalable In-Database Prescriptive Analytics for Dynamic Environments”. Summary: The project aims to augment prior work on in-database support for constrained optimization problems with capabilities to handle dynamic environments. Specifically, the project will […]

Ryan McKenna, Joie Wu, Arisa Tajima, Brett Mullins, Siddhant Pradhan, and Cecilia Ferrando have recently won the first prize in the National Institute of Standards and Technology (NIST) Differential Privacy Temporal Map Challenge. The challenge seeks new tools with which to push the boundaries of current technologies for de-identifying data […]

Two papers from DREAM Lab won the Best Demonstration and Best Demonstration Runner-up awards at VLDB 2020. Matteo Brucato, Miro Mannino, Azza Abouzied, Peter J. Haas, Alexandra Meliou won the 2020 VLDB Best Demonstration award for their work on “sPaQLTooLs: A Stochastic Package Query Interface for Scalable Constrained Optimization“. Anna […]

College of Information and Computer Sciences (CICS) doctoral candidate Anna Fariha has recently been awarded a 2020 Microsoft Research Dissertation Grant for her proposal, “Enhancing Usability and Explainability of Data Systems.” Fariha’s work focuses on reducing the usability gap between non-expert users and complex data systems. Her thesis aims to […]