Roarke Horstmeyer

Roarke Horstmeyer

Assistant Professor of Biomedical Engineering

External Address: 
Fitzpatrick Center (Ciemas) Ro, 101 Science Drive, Durham, NC 27701
Internal Office Address: 
Box 90548, Durham, NC 27708-0548
Office Hours: 
Office hours for Fall 2020 - Spring 2021:Wednesdays 10-11:30am Thursdays 10am - 11:30am


Roarke Horstmeyer is an assistant professor within Duke's Biomedical Engineering Department. He develops microscopes, cameras and computer algorithms for a wide range of applications, from forming 3D reconstructions of organisms to detecting neural activity deep within tissue. His areas of interest include optics, signal processing, optimization and neuroscience. Most recently, Dr. Horstmeyer was a guest professor at the University of Erlangen in Germany and an Einstein postdoctoral fellow at Charitè Medical School in Berlin. Prior to his time in Germany, Dr. Horstmeyer earned a PhD from Caltech’s electrical engineering department in 2016, a master of science degree from the MIT Media Lab in 2011, and a bachelors degree in physics and Japanese from Duke University in 2006.

Education & Training

  • Ph.D., California Institute of Technology 2016

  • B.S., Duke University 2006

Selected Grants

Point-of-care cellular and molecular pathology of breast tumors on a cell phone awarded by National Institutes of Health (Investigator). 2020 to 2025

Rapid measurement of prefrontal cortical activity using parallelized diffuse correlation spectroscopy awarded by Air Force Office of Scientific Research (Principal Investigator). 2021 to 2024

Hartwell Individual Biomedical Research Award awarded by Hartwell Foundation (Principal Investigator). 2021 to 2024

Horstmeyer, R., et al. “Transmission matrix correlations.” Wavefront Shaping for Biomedical Imaging, 2019, pp. 315–28. Scopus, doi:10.1017/9781316403938.014. Full Text

Dai, Xiang, et al. “Quantitative Jones matrix imaging using vectorial Fourier ptychography.Biomed Opt Express, vol. 13, no. 3, Mar. 2022, pp. 1457–70. Pubmed, doi:10.1364/BOE.448804. Full Text

Glass, Carolyn, et al. “The Role of Machine Learning in Cardiovascular Pathology.Can J Cardiol, vol. 38, no. 2, Feb. 2022, pp. 234–45. Pubmed, doi:10.1016/j.cjca.2021.11.008. Full Text

Yao, Xing, et al. “Increasing a microscope's effective field of view via overlapped imaging and machine learning.Optics Express, vol. 30, no. 2, Jan. 2022, pp. 1745–61. Epmc, doi:10.1364/oe.445001. Full Text

Feiger, B., et al. “Evaluation of U-Net Based Architectures for Automatic Aortic Dissection Segmentation.” Acm Transactions on Computing for Healthcare, vol. 3, no. 1, Jan. 2022. Scopus, doi:10.1145/3472302. Full Text

YANG, X., et al. “Quantized Fourier ptychography with binary images from SPAD cameras.” Photonics Research, vol. 9, no. 10, Oct. 2021, pp. 1958–69. Scopus, doi:10.1364/PRJ.427699. Full Text

Vu, T., et al. “Deep image prior for undersampling high-speed photoacoustic microscopy.” Photoacoustics, vol. 22, June 2021. Scopus, doi:10.1016/j.pacs.2021.100266. Full Text

Fontes, Cassio M., et al. “Ultrasensitive point-of-care immunoassay for secreted glycoprotein detects Ebola infection earlier than PCR.Sci Transl Med, vol. 13, no. 588, Apr. 2021. Pubmed, doi:10.1126/scitranslmed.abd9696. Full Text

DiSpirito, Anthony, et al. “Reconstructing Undersampled Photoacoustic Microscopy Images Using Deep Learning.Ieee Transactions on Medical Imaging, vol. 40, no. 2, Feb. 2021, pp. 562–70. Epmc, doi:10.1109/tmi.2020.3031541. Full Text

Liu, W., et al. “Fast and sensitive diffuse correlation spectroscopy with highly parallelized single photon detection.” Apl Photonics, vol. 6, no. 2, Feb. 2021. Scopus, doi:10.1063/5.0031225. Full Text

Yao, X., et al. “Increasing a microscope’s effective field of view via overlapped imaging and machine learning.” Optics Infobase Conference Papers, Jan. 2021.


Xu, S., et al. “Rapid imaging of deep-tissue motion with parallelized diffuse correlation spectroscopy.” Optics Infobase Conference Papers, 2021.

Zhou, K. C., et al. “Mesoscopic photogrammetry with an unstabilized phone camera.” Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition, 2021, pp. 7531–41. Scopus, doi:10.1109/CVPR46437.2021.00745. Full Text

Cooke, C. L., et al. “Physics-Enhanced Machine Learning for Virtual Fluorescence Microscopy.” Proceedings of the Ieee International Conference on Computer Vision, 2021, pp. 3783–93. Scopus, doi:10.1109/ICCV48922.2021.00378. Full Text

Sharma, S., et al. “High throughput acquisition and analysis of bacterial colony features using gigapixel microscopy.” Optics Infobase Conference Papers, 2021.

Liu, W., et al. “Fast sensitive diffuse correlation spectroscopy with a SPAD array.” Optics Infobase Conference Papers, vol. Part F179-OTS-2020, 2020. Scopus, doi:10.1364/OTS.2020.SM3D.3. Full Text

Liu, W., et al. “Classifying decorrelation events hidden beneath scattering media via SPAD array detection.” Optics Infobase Conference Papers, 2020.

Dai, X., et al. “Towards a vectorial treatment of Fourier ptychographic microscopy.” Optics Infobase Conference Papers, 2020.

Harfouche, M., et al. “Imaging the behavior and neural activity of freely moving organisms with a gigapixel microscope.” Optics Infobase Conference Papers, vol. Part F169-BRAIN 2019, 2019. Scopus, doi:10.1364/BRAIN.2019.BT3A.3. Full Text

Zhong, L., et al. “Depth tracking using a multi-aperture microscope.” Optics Infobase Conference Papers, vol. Part F170-COSI 2019, 2019. Scopus, doi:10.1364/COSI.2019.CM1A.CTh4A.2. Full Text

Wang, Z., et al. “High-speed holographic imaging using compressed sensing and phase retrieval.” Proceedings of Spie  the International Society for Optical Engineering, vol. 10222, 2017. Scopus, doi:10.1117/12.2262737. Full Text