Fan Lam's directory photo.

Fan Lam

Assistant Professor

Primary Affiliation

Computational Imaging


Status Full-time Faculty

Home Department of Bioengineering

Phone 300-3713


Address 4061 Beckman Institute, 405 North Mathews Avenue

  • Biography

    Fan Lam is an assistant professor in the Department of Bioengineering and is and affiliated with Carl R. Woese Institute for Genomic Biology as the personalized nutrition initiative. His primary research area is bioimaging at multi-scale.


    • B.S., biomedical engineering, Tsinghua University, 2008 
    • M.S., Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 2011
    • Ph.D., electrical and computer engineering, University of Illinois at Urbana-Champaign, 2011 and 2015
  • Honors
    • 2021: IEEE Senior Membership
    • 2020: Trailblazer Award, National Institute of Biomedical Imaging and Bioengineering (NIBIB, NIH)
    • 2020: National Science Foundation CAREER Award
    • 2019: List of Teachers Ranked As Excellent by Students
    • 2019-present: IEEE Transactions on Medical Imaging Editorial Board, Associate Editor
    • 2017: Junior Fellow, International Society of Magnetic Resonance in Medicine
  • Research

    Research areas:

    • Biomedical imaging

    • Bioinformatics

    • Biomedical imaging

    • Image reconstruction

    • Molecular imaging

    • MRI

    • Signal processing

    Professor Lam’s research program focuses on developing and translating new imaging technologies to visualize biological processes in the brain at a level beyond anatomy and neuronal activation, particularly, the molecular and chemical underpinnings of brain function and diseases.

  • 2021

    • Li, Y, Wang, Z, Sun, R & Lam, F 2021, 'Separation of Metabolites and Macromolecules for Short-TE 1H-MRSI Using Learned Component-Specific Representations', IEEE Transactions on Medical Imaging. DOI: 10.1109/TMI.2020.3048933


    • Lam, F & Sutton, BP 2020, 'Intravoxel B0 inhomogeneity corrected reconstruction using a low-rank encoding operator', Magnetic Resonance in Medicine, vol. 84, no. 2, pp. 885-894. DOI: 10.1002/mrm.28182
    • Lam, F, Li, Y & Peng, X 2020, 'Constrained Magnetic Resonance Spectroscopic Imaging by Learning Nonlinear Low-Dimensional Models', IEEE Transactions on Medical Imaging, vol. 39, no. 3, 8770102, pp. 545-555. DOI: 10.1109/TMI.2019.2930586
    • Lam, F, Li, Y, Guo, R, Clifford, B & Liang, ZP 2020, 'Ultrafast magnetic resonance spectroscopic imaging using SPICE with learned subspaces', Magnetic Resonance in Medicine, vol. 83, no. 2, pp. 377-390. DOI: 10.1002/mrm.27980


    • Lam, F, Li, Y, Clifford, B & Liang, Z-P 2018, 'Macromolecule mapping of the brain using ultrashort-TE acquisition and reference-based metabolite removal', Magnetic Resonance in Medicine, vol. 79, no. 5, pp. 2460-2469. DOI: 10.1002/mrm.26896


    • Li, Y, Lam, F, Clifford, B & Liang, ZP 2017, 'A subspace approach to spectral quantification for MR spectroscopic imaging', IEEE Transactions on Biomedical Engineering, vol. 64, no. 10, 8013142, pp. 2486-2489. DOI: 10.1109/TBME.2017.2741922