Email:
liuyangzhuan@lbl.gov

Address:
MS 50A-3111, 1 Cyclotron Road
Berkeley, CA 94720

Phone:
734-546-7392

Google Scholar:
[Here]

Welcome to my personal homepage! I am a career (tenured) research scientist in the Scalable Solvers Group of the Applied Mathematics and Computational Research Division at Lawrence Berkeley National Laboratory (LBNL). My broad research interests lie in the development of fast and parallel scientific computing tools for exascale applications. My researh topics include fast linear solvers for highly oscillatory problems, scalable direct sparse matrix solvers, randomized linear algebras, communication avoiding algorithms, uncertainty quantification and autotuning, multi-resolution algorithms, multi-physics and multi-scale modeling, and fast algorithms for machine-learning applications.   

EDUCATION

  • Ph.D. Electrical Engineering and Computer Science, 2015, University of Michigan
    Thesis: Solving Electrically Very Large Transient Electromagnetic Problems Using Plane-Wave Time-Domain Algorithms
  • M.S. Applied Mathematics, 2014, University of Michigan
    M.S. Electrical Engineering and Computer Science, 2013, University of Michigan
  • B.S. Electrical Engineering, 2010, Shanghai Jiao Tong University

RESEARCH INTERESTS

  • Scalable exact arithmetic, low-rank-based and butterfly-based sparse direct matrix solvers.
  • Frequency-domain integral equations, their direct method- and fast multipole method-based solutions.
  • Time-domain integral equations and their plane-wave-time-domain algorithm-accelerated solutions.
  • Butterfly schemes, compressive sensing techniques, randomized algorithms and their applications in wireless communication and electromagnetics.
  • Provably scalable parallelization schemes and communication-avoiding algorithms on morden computing platforms.
  • Surrogate model-based autotuning and uncertainty quantification tools for exascale applications     
  • Application of fast solvers to the scattering characterization of large objects, modeling electronic/optical devicec, bio tissues and other multi-scale and multi-physics systems
  • Fast and parallel machine learning frameworks    

BOOK CHAPTERS

  1. Y. Liu, and E. Michielssen, "Parallel fast time-domain integral-equation methods for transient electromagnetic analysis," Parallel algorithms in computational science and engineering., Birkhauser, 2020.

JOURNAL PUBLICATIONS

  1. Z. Wang, A. Aldossary, T. Shi, Y. Liu, X. S. Li, and M. Head-Gordon, "Local second order Møller-Plesset theory with a single threshold using orthogonal virtual orbitals: Theory, implementation and assessment," J. Chem. Theory Comput., 2023. [pdf]
  2. Y. Liu, T. Luo, A. Rani, H. Luo, and X. Li, "Detecting resonance of radio-frequency cavities using fast direct integral equation solvers and augmented Bayesian optimization," IEEE J. Multiscale Multiphysics Comput. Tech., 2023. [pdf]
  3. L. Claus, P. Ghysels, Y. Liu, T. Nhan, R. Thirumalaisamy, A. P. S. Bhalla, and X. Li, "Sparse approximate multifrontal factorization with composite compression methods," ACM Trans. Math. Softw., 2023. [pdf]
  4. X. Li, Y. Liu, P. Lin, and P. Sao, "Newly released capabilities in distributed-memory SuperLU sparse direct solver," ACM Trans. Math. Softw., 2023. [pdf]
  5. H. Luo, Y. Cho, J. W. Demmel, X. S. Li, and Y. Liu, "Hybrid models for mixed variables in Bayesian optimization," Journal of Machine Learning Research, submitted.
  6. W. Sheng, A. C. Yucel, Y. Liu, H. Guo, and E. Michielssen, "A domain decomposition based surface integral equation simulator for characterizing EM wave propagation in mine environments," IEEE Trans. Antennas Propag., 2023.
  7. M. Wang, Y. Liu, P. Ghysels, and A. C. Yucel, "VoxImp: impedance extraction simulator for voxelized structures," IEEE Trans. Antennas Propag., 2023.
  8. Y. Liu, J. Song, R. Burridge, and J. Qian, "A fast butterfly-compressed Hadamard-Babich integrator for high-frequency inhomogenous Helmholtz equations in variable media," SIAM J. Multiscale Model. Simul., 2022. [pdf]
  9. S. B. Sayed, Y. Liu, L. J. Gomez, and A. C. Yucel, "A butterfly-accelerated volume integral equation solver for broad permittivity and large-scale electromagnetic analysis," IEEE Trans. Antennas Propag., 2021.[pdf]
  10. H. Luo, J.W. Demmel, Y. Cho, X. S. Li, and Y. Liu, "Non-smooth Bayesian optimization in tuning problems," Journal of Machine Learning Research, submitted.[pdf]
  11. Y. Liu, P. Ghysels, L. Claus, and X. Sherry Li "Sparse approximate multifrontal factorization with butterfly compression for high frequency wave equations,” SIAM J. Sci. Comput., 2021. [pdf]
  12. Y. Liu, X. Xing, H. Guo, E. Michielssen, P. Ghysels, and X. Sherry Li, "Butterfly factorization via randomized matrix-vector multiplications," SIAM J. Sci. Comput., 2021. [pdf]
  13. Y. Liu, and H. Yang, "A hierarchical butterfly LU preconditioner for two-dimensional electromagnetic scattering problems involving open surfaces," J. Comput. Phys., 2019. [pdf]
  14. Y. Liu, W. Sid-Lakhdar, E. Rebrova, P. Ghysels, and X. Sherry Li, "A parallel hierarchical blocked adaptive cross approximation algorithm," Int. Journal of High Performance Computing Applications, 2019. [pdf]
  15. H. Guo, Y. Liu, J. Hu, and E. Michielssen, "A butterfly‐based direct solver using hierarchical LU factorization for Poggio‐Miller‐Chang‐Harrington‐Wu‐Tsai equations,Microw. Opt. Technol. Lett. 2018. [pdf]
  16. Y. Liu, A. C. Yucel, H. Bagci, A. C. Gilbert, and E. Michielssen, "Wavelet-enhanced plane-wave time-domain algorithm for analysis of transient scattering from electrically large conducting objects," IEEE Trans. Antennas Propag., 2017. [pdf]
  17. A. C. Yucel, W. Sheng, C. Zhou, Y. Liu, H. Bagci, and E. Michielssen, "An FMM-FFT accelerated SIE simulator for analyzing EM wave propagation in mine environments loaded with conductors,IEEE J. Multiscale and Multiphys. Comput. Techn., 2017. [pdf]
  18. Y. Liu, H. Guo, and E. Michielssen, "A HSS matrix-inspired butterfly-based direct solver for analyzing scattering from two-dimensional objects," IEEE Antennas Wireless Propag. Lett., 2016. [pdf]
  19. H. Guo, Y. Liu, J. Hu, and E. Michielssen, "A butterfly-based direct integral equation solver using hierarchical LU factorization for analyzing scattering from electrically large conducting objects," IEEE Trans. Antennas Propag., 2016. [pdf]
  20. Y. Liu, A. Al-Jarro, H. Bagci, and E. Michielssen, "Parallel PWTD-accelerated explicit solution of the time domain electric field volume integral equation," IEEE Trans. Antennas Propag., 2016. [pdf]
  21. Y. Liu, A. C. Yucel, H. Bagci, and E. Michielssen, "A scalable parallel PWTD-accelerated SIE solver for analyzing transient scattering from electrically large objects," IEEE Trans. Antennas Propag., 2016. [pdf]
  22. Y. Liu, A. C. Yucel, V. Lomakin, and E. Michielssen, "Graphics processing unit implementation of multilevel plane-wave time-domain algorithm," IEEE Antennas Wireless Propag. Lett., vol. 1, pp. 1-1, 2014. [pdf]
  23. A. C. Yucel, Y. Liu, H. Bagci, and E. Michielssen, "Statistical characterization of electromagnetic wave propagation in mine environments," IEEE Antennas Wireless Propag. Lett., vol. 12, pp. 1602-1605, 2013. [pdf]

CONFERENCE PUBLICATIONS

  1. Y. Liu, N. Ding, P. Sao, S. Williams, and X. S. Li, "Unified communication optimization strategies for sparse triangular solver on CPU and GPU clusters," The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), 2023. [pdf]
  2. G. Dinh, I. Kannan, H. Luo, C. Hong, Y. Cho, J. Demmel, X. S. Li, and Y. Liu, "Sample-Efficient Mapspace Optimization for DNN Accelerators with Bayesian Learning," ML for Computer Architecture and Systems (MLArchSys), ISCA, 2023. [pdf]
  3. Y. Cho, J. W. Demmel, J. King, X. S. Li, Y. Liu, and H. Luo, "Harnessing the crowd for autotuning high-performance computing applications," in IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2023. [pdf]
  4. Y. Liu, "A comparative study of butterfly-enhanced direct integral and differential equation solvers for high-frequency electromagnetic analysis involving inhomogeneous dielectrics," 3rd URSI Atlantic Radio Science Meeting (AT-AP-RASC), 2022. [pdf]
  5. X. Zhu, Y. Liu, P. Ghysels, D. Bindal, and X. S. Li, "GPTuneBand: multi-task and multi-fidelity Bayesian optimization for autotuning large-scale high performance computing applications," SIAM PP, 2022. [pdf]
  6. Y. Cho, J. W. Demmel, X. S. Li, Y. Liu, and H. Luo, "Enhancing autotuning capability with a history database," IEEE 14th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC), 2021. [pdf]
  7. Y. Liu, W. M. Sid-Lakhdar, O. Marques, X. Zhu, C. Meng, J. W. Demmel, and X. S. Li, "GPTune: multitask learning for autotuning exascale applications," PPoPP, 2021. [pdf]
  8. N. Ding, S. Williams, Y. Liu and X. S. Li, "A message-driven, multi-GPU parallel sparse triangular solver," SIAM ACDA, 2021. [pdf]
  9. NG. Chavez, E. Rebrova, Y. Liu, P. Ghysels and X. S. Li, "Scalable and memory-efficient kernel ridge regression," 34th IEEE International Parallel and Distributed Processing Symposium, 2020. [pdf]
  10. Nan Ding, Samuel Williams, Y. Liu, and X. S. Li, "Leveraging one-sided communication for sparse triangular solvers," SIAM Workshop on Combinatorial Scientific Computing, 2020. [pdf]
  11. Y. Liu, M. Jacquelin, P. Ghysels, and X. S. Li, "Highly scalable distributed-memory sparse triangular solve algorithms," SIAM Workshop on Combinatorial Scientific Computing, 2018. [pdf]
  12. E. Rebrova, G. Ghavez, Y. Liu, P. Ghysels, and X. S. Li, "A study of clustering techniques and hierarchical matrix formats for kernel ridge regression," Proc. IEEE IPDPSW, 2018. [pdf]
  13. Y. Liu, V. Lomakin, and E. Michielssen, "Graphics processing unit-accelerated implementation of the plane wave time domain algorithm," 28th Ann. Rev. Prog. Appl. Computat. Electromagn., 2012. [pdf]
  14. J. Liang, Y. Liu, W. Zhang, Y. Xu, X. Gan, and X. Wang, "Joint compressive sensing in wideband cognitive networks," in Proc. IEEE WCNC, 2010. [pdf]

AWARDS

  • DOD SBIR Award (Co-PI), 2023.
  • LBNL Laboratory Directed Research and Development (LDRD) Award (PI), 2022.
  • Young Scientists Award, 3rd URSI Atlantic Radio Science Meeting (AT-AP-RASC), 2022.
  • Sergei A. Schelkunoff Transactions Prize Paper Award, IEEE Antennas and Propagation Society, 2018.
  • First Price in Student Paper Competition, 12th International Workshop on Finite Elements for Microwave Engineering, 2014.
  • Second Price in Student Paper Competition, 28th Annual Review of Progress in Applied Computational Electromagnetics, 2012.
  • Excellent Graduate Student of Shanghai Jiao Tong University, 2010.
  • Third prize in National Electronic Contest, China, 2009

PROFESSIONAL ACTIVITIES

  • Reviewer for the DOE SIR/STTR; Israel Science Foundation (ISF); IEEE Cluster 2021; International Conference on Parallel Processing (ICPP) 2021; Supercomputing (SC) 2021; SIAM Conference on Parallel Processing for Scientific Computing (PP22); Communications in Computational Physics; CCF Transactions on High Performance Computing; CSIAM Transactions on Applied Mathematics; Journal of Computational Physics; The Journal of the Acoustical Society of America; SIAM Journal of Scientific Computing; IEEE Transaction on Antennas and Propagation; IEEE Antennas and Propagation Magazine; IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control; IEEE Transaction on Microwave Theory and Techniques; IEEE Antennas and Wireless Propagation Letters; IEEE Journal on Multiscale and Multiphysics Computational Techniques; Journal of Applied Computational Electromagnetics Society; International Journal of Numerical Modelling: Electronic Networks, Devices and Fields; International Journal of Antennas and Propagation; Concurrency and Computation: Practice and Experience; the Open Electrical and Electronic Engineering Journal; Journal of Microwaves, Optoelectronics and Electromagnetic Applications.
  • Session Chair for "Time-Domain Numerical Methods," IEEE APS-URSI, 2012; "Acceleration Rechniques for Integral Equations," IEEE APS-URSI, 2017; "Parallel Sparse Triangular Solve on Emerging Platforms," SIAM Conference on Applied Linear Algebra, 2018; "Time-Domain Computational Methods for Complex Electromagnetic and Multiphysics Problems," IEEE APS-URSI, 2019; "Fast and Accurate Integral Methods for Highly Oscillatory Phenomena," SIAM Conference on Computational Science and Engineering, 2019, "Low-Rank Compression-Based Fast Sparse Direct Solvers," SIAM Conference on Parallel Processing for Scientific Computing, 2020.
  • Secretary for IEEE Southeastern Michigan Section, Technical Activities Committee. Treasurer for IEEE Southeastern Michigan Section, Chapter IV (Trident).