Title

Haonan Lin

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Photo of Haonan Lin
Title/Position
Assistant Professor
Areas of Research

Areas of Research

Biomedical Imaging & Instrumentation , Cancer Technologies , Biomedical Informatics & Systems Modeling
Contact

Contact

U. A. Whitaker 2108Georgia Tech
haonan.lin@bme.gatech.edu
404-894-2912
Computational Chemical Imaging Lab
Education

Education

  • Ph.D. in Biomedical Engineering, Boston University, 2021
  • B.S. in Engineering Physics, Tsinghua University, 2015
Research Interests

Research Interests

Professor Lin's Research focuses on the development of computation-driven vibrational chemical imaging technologies to noninvasively measure the biochemical processes in living systems and identify novel biomarkers for diseases. Specifically, it includes (1) Developing vibrational chemical imaging platforms beyond the physical limits by computation-driven system design and image reconstruction. (2) Discovering unknown biochemical mechanisms and disease biomarkers using novel chemical imaging data and AI / ML algorithms.

Teaching Interests

Teaching Interests

Professor Lin’s background and research expertise lie in biophotonics, electronics, machine learning, and signal processing. His teaching subjects can be selected from but are not limited to the abovementioned categories, focusing on either undergraduate-level fundamentals of a particular subject or the interdisciplinary graduate-level topics bridging these fields.
Publications

Publications

https://doi.org/10.1126/sciadv.ady0545
Sanjun Fan*, Ran Cheng*, Haonan Lin* (equal contribution), Zhewen Luo, Abigail E. Smith, Chih-Feng Wang, Jinna He, Brian T. Scarpitti, Deben N. Shoup, Hannah C. Schorr, Erjun Liang, Jian Ye, Ji-Xin Cheng#, Zachary D. Schultz#. "Single-Particle Surface-Enhanced Coherent Anti-Stokes Raman Scattering: Nanoparticle Design and Mechanism." Science Advances 12.5 (2026): eady0545.
https://doi.org/10.1016/j.newton.2025.100195
Guangrui Ding, Chang Liu, Jiaze Yin, Xinyan Teng, Yuying Tan, Hongjian He, Haonan Lin# (Co-corresponding), Lei Tian#, Ji-Xin Cheng#. Self-Supervised Elimination of Non-Independent Noise in Hyperspectral Imaging." Newton 1.6 (2025): 100195.
https://doi.org/10.1038/s41592-024-02575-1
Haonan Lin, Scott Seitz, Yuying Tan, Jean-Baptiste Lugagne, Le Wang, Guangrui Ding, Hongjian He, Tyler J. Rauwolf, Mary J. Dunlop, John H. Conor, John A. Porco, Jr., Lei Tian, Ji-Xin Cheng#. “Label-free nanoscopy of cell metabolism by ultrasensitive reweighted visible stimulated Raman scattering.” Nature Methods 22.5 (2025): 1040-1050.
https://doi.org/10.1126/sciadv.adg6061
Yuying Tan*, Haonan Lin* (equal contribution), and Ji-Xin Cheng#. “Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity.” Science Advances 9.33 (2023): eadg6061.
https://doi.org/10.1186/s43593-022-00038-8
Haonan Lin, and Ji-Xin Cheng#. "Computational coherent Raman scattering imaging: breaking physical barriers by fusion of advanced instrumentation and data science." eLight 3.6 (2023): 1-19.
https://doi.org/10.1038/s41467-021-23202-z
Haonan Lin, Hyeon Jeong Lee, Nathan Tague, Jean-Baptiste Lugagne, Cheng Zong, Fengyuan Deng, Wilson Wong, Mary J. Dunlop and Ji-Xin Cheng#. “Microsecond fingerprint stimulated Raman spectroscopic imaging by ultrafast tuning and spatial-spectral learning.” Nature Communications 12.1 (2021): 1-12.