Roarke W. Horstmeyer

Horstmeyer

Assistant Professor of Biomedical Engineering

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.

Appointments and Affiliations

  • Assistant Professor of Biomedical Engineering
  • Faculty Network Member of the Duke Institute for Brain Sciences

Contact Information

Education

  • Ph.D. California Institute of Technology, 2016
  • B.S. Duke University, 2006

Research Interests

Computational optics, machine learning, and designing new algorithms for image processing. A main focus is to improve how we capture and use images of microscopic phenomena within a range of biomedical contexts. In general, I like to create new optical devices that can improve the utility of the information that we can gather about the world around us.

Courses Taught

  • EGR 393: Research Projects in Engineering
  • EGR 101L: Engineering Design and Communication
  • BME 792: Continuation of Graduate Independent Study
  • BME 791: Graduate Independent Study
  • BME 789: Internship in Biomedical Engineering
  • BME 548L: Machine Learning and Imaging (GE, IM)
  • BME 494: Projects in Biomedical Engineering (GE)
  • BME 493: Projects in Biomedical Engineering (GE)

In the News

Representative Publications

  • Zhou, KC; Harfouche, M; Zheng, M; Jönsson, J; Lee, KC; Kim, K; Appel, R; Reamey, P; Doman, T; Saliu, V; Horstmeyer, G; Lee, SA; Horstmeyer, R, Computational 3D topographic microscopy from terabytes of data per sample, Journal of Big Data, vol 11 no. 1 (2024) [10.1186/s40537-024-00901-0] [abs].
  • Kreiss, L; Wu, M; Wayne, M; Xu, S; McKee, P; Dwamena, D; Kim, K; Lee, KC; Liu, W; Ulku, A; Harfouche, M; Yang, X; Cook, C; Chaware, A; Lee, SA; Buckley, E; Bruschini, C; Charbon, E; Huettel, S; Horstmeyer, R, Beneath the Surface: Revealing Deep-Tissue Blood Flow in Human Subjects
    with Massively Parallelized Diffuse Correlation Spectroscopy
    (2024) [abs].
  • Xu, S; Yang, X; Ritter, P; Dai, X; Lee, KC; Kreiss, L; Zhou, KC; Kim, K; Chaware, A; Neff, J; Glass, C; Lee, SA; Friedrich, O; Horstmeyer, R, Tensorial tomographic Fourier ptychography with applications to muscle tissue imaging, Advanced Photonics, vol 6 no. 2 (2024) [10.1117/1.AP.6.2.026004] [abs].
  • Kreiss, L; Jiang, S; Li, X; Xu, S; Zhou, KC; Lee, KC; Mühlberg, A; Kim, K; Chaware, A; Ando, M; Barisoni, L; Lee, SA; Zheng, G; Lafata, KJ; Friedrich, O; Horstmeyer, R, Digital staining in optical microscopy using deep learning - a review, PhotoniX, vol 4 no. 1 (2023) [10.1186/s43074-023-00113-4] [abs].
  • Mühlberg, A; Ritter, P; Langer, S; Goossens, C; Nübler, S; Schneidereit, D; Taubmann, O; Denzinger, F; Nörenberg, D; Haug, M; Schürmann, S; Horstmeyer, R; Maier, AK; Goldmann, WH; Friedrich, O; Kreiss, L, SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for Prior-Informed Assessment of Muscle Function and Pathology., Advanced science (Weinheim, Baden-Wurttemberg, Germany), vol 10 no. 28 (2023) [10.1002/advs.202206319] [abs].