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 […]

Chenghao Lyu and Yanlei Diao’s paper “Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing” is accepted to VLDB 2022. Authors: Chenghao Lyu, Qi Fan, Fei Song, Arnab Sinha, Yanlei Diao, Wei Chen, Li Ma, Yihui Feng, Yaliang Li, Kai Zeng, and Jingren Zhou