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 matrix and tensor algorithms for dense and sparse linear systems, randomized algorithms, highly oscillatory problems, high-dimensional PDEs, communication avoiding algorithms, uncertainty quantification and autotuning, scientific machine learning, multi-resolution algorithms, multi-physics and multi-scale modeling. My application interests span electromagnetics, seismic inversion, accelerator physics, fusion simulation, quantum chemistry, nuclear physics, X-ray tomography, optical computing, and quantum computing, etc.

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

  • Randomized algorithms, low rank matrix and tensor algorithms, and hierarchical matrix algorithms for dense and sparse linear systems.
  • Communication avoiding and GPU-based algorithms for sparse direct solvers.
  • Green's function-based methods for electromagnetics, acoustics, particle physics, kernel methods and quantum chemistry.
  • Surrogate model-based autotuning and uncertainty quantification tools for exascale applications.
  • Neural operators for solving high-dimensional PDEs.
  • Matrix completion, compressive sensing techniques, and dictionary learning algorithms for wireless communication, electromagnetics and inverse problems.
  • Provably and practically scalable parallelization schemes for computing platforms with extreme heterogeneity.

MY FAVORITE PAPERS (full list at [here])

  1. (Linear algebra) Tensor algorithm: "A linear-complexity tensor butterfly algorithm for compressing high-dimensional oscillatory integral operators," [pdf]
  2. (Linear algebra) Sparse solver: "Sparse approximate multifrontal factorization with butterfly compression for high frequency wave equations," [pdf]
  3. (Linear algebra) Randomized algorithm: "Butterfly factorization via randomized matrix-vector multiplications," [pdf]
  4. (Computer science) Communication-avoiding algorithm: "Unified communication optimization strategies for sparse triangular solver on CPU and GPU clusters," [pdf]
  5. (Machine learning) Bayesian optimization: "GPTune: multitask learning for autotuning exascale applications," [pdf]
  6. (Machine learning) SciML for fusion: "Sparsified time-dependent Fourier neural operators for fusion simulations," [pdf]
  7. (Electromagnetics) Time-domain integral equation: "Wavelet-enhanced plane-wave time-domain algorithm for analysis of transient scattering from electrically large conducting objects," [pdf]
  8. (Electromagnetics) Direct solver for integral equation: "A butterfly-based direct integral equation solver using hierarchical LU factorization for analyzing scattering from electrically large conducting objects," [pdf]

AWARDS

  • LBNL SPOT Award, 2024.
  • 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

  • TPC co-chair for ACES Conference, 2025
  • Publication chair for IEEE NEMO Conference, 2023
  • Steering committee member for “Celebrating Maxwell’s Equations: 150 Years” workshop, 2015.
  • TPC members for multiple conferences: HiPC, IPDPS, IEEE Cluster, ICPP, SC, SIAM PP.
  • Proposal reviewers: DOE SBIR/STTR, NWO, ISF, LBNL LDRD, NNSA-PATH, LBNL red team reviewer. Reviewers for 34 journals and conferences.
  • Chairs/judges for 9 sessions/mini-symposiums in several applied math, computer science and electromagnetics conferences.
  • Secretary for IEEE Southeastern Michigan Section, Technical Activities Committee. Treasurer for IEEE Southeastern Michigan Section, Chapter IV (Trident).
  • Mentors for multiple internship programs: VFP, NSF-MSGI, DOE-CSGF, SRP, NNSA-MSIIP, LBNL CS summer program, etc.