Directory

Fan Lam's directory photo.

Fan Lam

Assistant Professor

Primary Affiliation

Computational Imaging

Affiliations

Status Full-time Faculty

Home Department of Bioengineering

Phone 300-3713

Email fanlam1@illinois.edu

Address 4061 Beckman Institute, 405 North Mathews Avenue

  • Biography

    Professor Lam received his B.S. in Biomedical Engineering from Tsinghua University in 2008 and his M.S. and Ph.D. in Electrical and Computer Engineering from University of Illinois at Urbana-Champaign in 2011 and 2015 respectively.

  • Honors
    • IEEE Senior Membership, 2021 
    • Trailblazer Award, National Institute of Biomedical Imaging and Bioengineering (NIBIB, NIH),  2020 
    • National Science Foundation CAREER Award, 2020 
    • List of Teachers Ranked As Excellent by Students, 2019 
    • IEEE Transactions on Medical Imaging Editorial Board, Associate Editor, 2019 - Present 
    • Junior Fellow, International Society of Magnetic Resonance in Medicine, 2017 
  • Research

    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. Specific scientific pursuits include:

    • Pushing the functional scale of in vivo neuroimaging by developing a new generation of multinuclear, ultrahigh-resolution magnetic resonance spectroscopic imaging technologies for multiplexed molecular imaging of the brain.
    • Developing novel methods for quantitative and multimodal biochemical mapping of the nervous systems, to study tissue microstructures and elucidate connections across modalities and scales.
    • Translating novel molecular imaging technologies to study specific CNS disorders, with the aim of advancing the diagnosis, treatment, and prognosis of these 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

    2020

    • 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

    2018

    • 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

    2017

    • 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