
About
Tim Davis is a Professor in the Department of Computer Science and Engineering at Texas A&M University. His research focuses on sparse matrix algorithms, applied mathematics, and graph theory, with contributions to software such as SuiteSparse and GraphBLAS. He holds Fellowships from SIAM, ACM, and IEEE, and received the 2018 Walston Chubb Award for Innovation.
Education and Affiliations
- PhD in Electrical Engineering from the University of Illinois
- Postdoctoral work with Iain Duff at CERFACS, Toulouse
- Adjunct roles and collaborations with NVIDIA, Intel, and Redis Labs
Research Interests
His work bridges graph theory and numerical linear algebra, emphasizing efficient sparse matrix algorithms. Key contributions include:
- Development of SuiteSparse, a suite of sparse matrix algorithms used in MATLAB, SPICE, and Google's Ceres Solver
- GraphBLAS: a standard for graph algorithms expressed via sparse linear algebra
- The SuiteSparse Matrix Collection, a benchmark for sparse matrix research
Publications
Recent work includes advancements in parallel GraphBLAS implementations, sparse QR factorization on GPUs, and algorithmic art. Over 50 peer-reviewed articles and two books highlight his impact.
Grants and Collaborations
- Funded by NVIDIA, Intel, Redis Labs, IBM, and Julia Computing
- Collaborators include Yifan Hu (AT&T), Tim Mattson (Intel), and Aydın Buluç (LBNL)
Labs and Teams
Leads the Texas A&M team for GraphBLAS development and maintains close ties with industry partners like Redis Labs for RedisGraph integration.
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