Two Michigan State University computer science and engineering faculty from the College of Engineering have received NSF CAREER Awards.
H. Metin Aktulga will use his CAREER Award to develop algorithms and software to help computational scientists and big data researchers tackle the challenges they face when performing large-scale computations on parallel computer systems. The five-year, $500,000 grant began in February 2019.
“Developing parallel software to execute efficiently on high-end systems with many core processors, GPUs, and deep memory hierarchies can be an insurmountable,” Aktulga said. “In this project, we focus on computations involving sparse matrices and graphs as they appear in several areas of big data analytics and scientific computing. We aim to develop a framework which will allow scientists and engineers to express their sparse matrix-based solvers through a simple interface. Parallelization, performance optimization and efficient access to large data sets would then be handled behind the scenes,”
Jiliang Tang will use his five-year, $507,000 NSF CAREER grant, which began in March 2019, to improve the analytics of social networks.
Tang said users who “like” or “block” messages are creating significant challenges to traditional network analysis.
“In today’s social systems, engagement between people can be both positive and negative in terms of blocked and unfriended users,” Tang said. “Networks end up with both positive and negative links, known as ‘signed networks,’ which have different properties and principles from unsigned ones. This poses tremendous challenges to traditional network analysis, so our project will enable the analysis of networks with negative links and various data-information areas. The new algorithms will assist in more comprehensive modeling, measuring and mining.”
Aktulga and Tang are the 17th and 18th Engineering faculty to receive NSF CAREER Awards since 2010. NSF CAREER Awards, which are among NSF’s most prestigious honors, support junior faculty who exemplify the role of teacher-scholars through outstanding research and education.
