Roarke 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
  • Assistant Professor in the Department of Electrical and Computer Engineering
  • Faculty Network Member of the Duke Institute for Brain Sciences

Contact Information

Education

  • B.S. Duke University, 2006
  • Ph.D. California Institute of Technology, 2016
  • Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany), 2022

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

  • ISS 795T: Bass Connections Information, Society & Culture Research Team
  • ISS 395T: Bass Connections Information, Society & Culture Research Team
  • 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)

In the News

Representative Publications

  • Wu, M. M., L. Kreiss, M. A. Wayne, M. B. Robinson, C. Bruschini, E. Charbon, and R. Horstmeyer. “Autocorrelation Bias in Diffuse Correlation Spectroscopy Observable via SPAD Arrays (Accepted).” IEEE Journal of Selected Topics in Quantum Electronics 32, no. 4 (July 1, 2026). https://doi.org/10.1109/JSTQE.2025.3637165.
  • Chul Lee, Kyung, Hyesuk Chae, Jongho Kim, Lucas Kreiss, Hyeongyu Kim, Yong Guk Kang, Kevin C. Zhou, et al. “Semi-supervised virtual staining using learned-illumination Fourier ptychography for high-speed label-free histopathology.” Journal of Physics: Photonics 8, no. 1 (March 1, 2026): 015025–015025. https://doi.org/10.1088/2515-7647/ae270f.
  • Wang, R., Q. Zhao, L. Loetgering, F. Allars, Z. Hong, T. J. Pennycook, R. Horstmeyer, J. Rodenburg, A. Maiden, and G. Zheng. “Ptychography at all wavelengths.” Nature Reviews Methods Primers 5, no. 1 (December 1, 2025). https://doi.org/10.1038/s43586-025-00438-3.
  • Bercaw, Jefferson R., Patrick X. Bradley, Christopher C. Otap, Lauren N. Heckelman, Krystal S. Tamayo, Kwadwo A. Owusu-Akyaw, Andrzej S. Kosinski, Roarke W. Horstmeyer, Charles E. Spritzer, and Louis E. DeFrate. “A deep learning-based approach for measuring patellar cartilage deformations from knee MR images.” J Biomech 192 (November 2025): 112930. https://doi.org/10.1016/j.jbiomech.2025.112930.
  • Hu, Jia, Arun Cherkkil, Daniel A. Surinach, Ibrahim Oladepo, Ridwan Hossain, Skylar Fausner, Kapil Saxena, et al. “Pan-cortical cellular imaging in freely behaving mice using a miniaturized micro-camera array microscope (mini-MCAM).” Science Advances 11, no. 44 (October 2025): eadt3634. https://doi.org/10.1126/sciadv.adt3634.