Professor, CSE Distinguished Professor, William Norris Land Grant Chair in Large-Scale Computing
Contact
5-225B Kenneth H. Keller Hall
200 Union Street Se
Minneapolis, MN 55455
Professor, CSE Distinguished Professor, William Norris Land Grant Chair in Large-Scale Computing
Saad’s research focuses on numerical linear algebra, sparse matrix computations, iterative methods for linear systems and eigenvalue problems, parallel algorithms in numerical linear algebra, and matrix methods for machine learning.
Research Division
Data Science and Machine Learning
Current Research
Google Scholar
pARMS: parallel Algebraic Recursive Multilevel Solvers
Ph.D. Graduates
Tianshi Xu (2023); Shashanka Ubaru (2018); Vasileios Kalantzis (2018); Ruipeng Li (2015); Thanh Ngo (2014); Daniel Osei-Kuffuor (2011); Jie Chen (2011); Na Li (2006); Bernard Sheehan (2005); Irene Moulitsas (2005; co-advised with George Karypis); Abdelkader Baggag (2003; co-advised with A. Sameh); Edmond Chow (1997); Kesheng Wu (1997); Sangback Ma (2003).
Ph.D., University of Grenoble, France (1983)
Ph.D., University of Grenoble, France (1974)
B. S. in Mathematics, University of Algiers (1970)
Yousef Saad joined the Department of Computer Science & Engineering as a professor in 1990. He also served as head of the Department from 1997-2000. Before coming to the University, Saad served as a senior computer scientist and associate professor at the University of Illinois at Urbana-Champaign from 1986-88 and as a senior scientist for the Research Institute for Advanced Computer Science from 1988-90. In 2005, he was recognized as a College of Science and Engineering Distinguished Professor and has been a William Norris Land Grant Chair since 2007.
2023: SIAM John von Neumann Prize
2007 - 2022: William Norris Land Grant Chair in Large-Scale Computing
2010: American Association for the Advancement of Science (AAAS) Fellow
2010: SIAM Fellows Program
2005: CSE Distinguished Professor
1997 - 2000: William Norris Land Grant Chair in Large-Scale Computing
Selected Grants
Collaborative Research: Robust acceleration and preconditioning methods for data-related applications: Theory and practice
Saad, Y.; National Science Foundation; 9/1/22 - 8/31/25
Multilevel graph-based methods for efficient data exploration
Saad, Y.; National Science Foundation; 8/1/20 - 7/31/23
Advances in robust multilevel preconditioning methods for sparse linear systems
Saad, Y.; National Science Foundation; 8/1/19 - 7/31/23
Saad, Y. (2023). Revisiting the (block) Jacobi subspace rotation method for the symmetric eigenvalue problem. Numerical Algorithms. 92 (1), [917-944].
DOI: 10.1007/s11075-022-01377-w
Shi, J., Li, R., Xi, Y., Saad, Y., de Hoop, M.V. (2022). A Non-perturbative Approach to Computing Seismic Normal Modes in Rotating Planets. Journal of Scientific Computing. 91 (2), [67].
DOI: 10.1007/s10915-022-01836-5
Chen, J., Saad, Y., Zhang, Z. (2022). Graph coarsening: from scientific computing to machine learning. SeMA Journal. 79 (1), [187-223].
DOI: 10.1007/s40324-021-00282-x
Xu, T., Kalantzis, V., Li, R., Xi, Y., Dillon, G., Saad, Y. (2022). parGeMSLR: A parallel multilevel Schur complement low-rank preconditioning and solution package for general sparse matrices. Parallel Computing. [102956].
DOI: 10.1016/j.parco.2022.102956
Saad, Y. (2022). The Origin and Development of Krylov Subspace Methods. Computing in Science and Engineering. 24 (4), [28-39].
DOI: 10.1109/MCSE.2022.3214388
Zheng, Q., Xi, Y., Saad, Y. (2021). A power schur complement low-rank correction preconditioner for general sparse linear systems. SIAM Journal on Matrix Analysis and Applications. 42 (4), [659-682].
DOI: 10.1137/20M1316445
Shi, J., Li, R., Xi, Y., Saad, Y., De Hoop, M.V. (2021). Planetary Normal Mode Computation: Parallel Algorithms, Performance, and Reproducibility. IEEE Transactions on Parallel and Distributed Systems. 32 (11), [9319555]. [2609-2622].
DOI: 10.1109/tpds.2021.3050448
YE, X.I.N., XI, Y.U.A.N.Z.H.E., SAAD, Y.O.U.S.E.F. (2021). Proxy-gmres: Preconditioning via gmres in polynomial space. SIAM Journal on Matrix Analysis and Applications. 42 (3), [1248-1267].
DOI: 10.1137/20m1342562
El-Guide, M., Miȩdlar, A., Saad, Y. (2020). A rational approximation method for solving acoustic nonlinear eigenvalue problems. Engineering Analysis with Boundary Elements. [44-54].
DOI: 10.1016/j.enganabound.2019.10.006
Polizzi, E., Saad, Y. (2020). Computational Materials Science and Engineering. In Modeling and Simulation in Science, Engineering and Technology. (123-150). (Modeling and Simulation in Science, Engineering and Technology. (2164-3679)). Birkhauser.
DOI: 10.1007/978-3-030-43736-7_5
Zheng, Q., Xi, Y., Saad, Y. (2020). Multicolor low-rank preconditioner for general sparse linear systems. Numerical Linear Algebra with Applications. 27 (4), [e2316].
DOI: 10.1002/nla.2316
Mahdi, M.A., Smaili, A., Saad, Y. (2020). Numerical investigations of turbulent natural convection heat transfer within a wind turbine nacelle operating in hot climate. International Journal of Thermal Sciences. [106143].
DOI: 10.1016/j.ijthermalsci.2019.106143
Liu, X., Xi, Y., Saad, Y., de Hoop, M.V. (2020). Solving the three-dimensional high-frequency Helmholtz equation using contour integration and polynomial preconditioning. SIAM Journal on Matrix Analysis and Applications. 41 (1), [58-82].
DOI: 10.1137/18M1228128
Fan, T., Shuman, D.I., Ubaru, S., Saad, Y. (2020). Spectrum-adapted polynomial approximation for matrix functions with applications in graph signal processing. Algorithms. 13 (11), [295]. [1-22].
DOI: 10.3390/a13110295
Shi, J., Li, R., Xi, Y., Saad, Y., De Hoop, M.V. (2019). Computing planetary interior normal modes with a highly parallel polynomial filtering eigensolver. In Proceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018. (894-906). (Proceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018.). Institute of Electrical and Electronics Engineers Inc..
DOI: 10.1109/SC.2018.00074
Ubaru, S., Seghouane, A.K., Saad, Y. (2019). Find the dimension that counts: Fast dimension estimation and Krylov PCA. In SIAM International Conference on Data Mining, SDM 2019. (720-728). (SIAM International Conference on Data Mining, SDM 2019.). Society for Industrial and Applied Mathematics Publications.
DOI: 10.1137/1.9781611975673.81
Ubaru, S., Saad, Y. (2019). Sampling and multilevel coarsening algorithms for fast matrix approximations. Numerical Linear Algebra with Applications. 26 (3), [e2234].
DOI: 10.1002/nla.2234
Petegrosso, R., Li, Z., Srour, M.A., Saad, Y., Zhang, W., Kuang, R. (2019). Scalable remote homology detection and fold recognition in massive protein networks. Proteins: Structure, Function and Bioinformatics. 87 (6), [478-491].
DOI: 10.1002/prot.25669
Li, R., Xi, Y., Erlandson, L., Saad, Y. (2019). The Eigenvalues Slicing Library (EVSL): Algorithms, implementation, and software. SIAM Journal on Scientific Computing. 41 (4), [C393-C415].
DOI: 10.1137/18M1170935
Dillon, G., Kalantzis, V., Xi, Y., Saad, Y. (2018). A hierarchical low rank schur complement preconditioner for indefinite linear systems. SIAM Journal on Scientific Computing. 40 (4), [A2234-A2252].
DOI: 10.1137/17M1143320