Roarke W. 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
  • Assistant Professor of Physics
  • Faculty Network Member of the Duke Institute for Brain Sciences

Contact Information

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

  • BME 394: Projects in Biomedical Engineering (GE)
  • BME 493-1: Projects in Biomedical Engineering (GE)
  • BME 493: Projects in Biomedical Engineering (GE)
  • BME 494: Projects in Biomedical Engineering (GE)
  • BME 548L: Machine Learning and Imaging (GE, IM)
  • BME 590L: Special Topics with Lab
  • BME 791: Graduate Independent Study
  • BME 792: Continuation of Graduate Independent Study
  • ECE 899: Special Readings in Electrical Engineering
  • EGR 393: Research Projects in Engineering

In the News

Representative Publications

  • Kim, K; Konda, PC; Cooke, CL; Appel, R; Horstmeyer, R, Multi-element microscope optimization by a learned sensing network with composite physical layers., Optics Letters, vol 45 no. 20 (2020), pp. 5684-5687 [10.1364/ol.401105] [abs].
  • Chaware, A; Cooke, CL; Kim, K; Horstmeyer, R, Towards an intelligent microscope: Adaptively learned illumination for optimal sample classification, 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), vol 2020-May (2020), pp. 9284-9288 [10.1109/ICASSP40776.2020.9054477] [abs].
  • Zhou, KC; Horstmeyer, R, Diffraction tomography with a deep image prior., Optics Express, vol 28 no. 9 (2020), pp. 12872-12896 [10.1364/oe.379200] [abs].
  • Konda, PC; Loetgering, L; Zhou, KC; Xu, S; Harvey, AR; Horstmeyer, R, Fourier ptychography: current applications and future promises., Optics Express, vol 28 no. 7 (2020), pp. 9603-9630 [10.1364/oe.386168] [abs].
  • Del Hougne, P; Imani, MF; Diebold, AV; Horstmeyer, R; Smith, DR, Learned Integrated Sensing Pipeline: Reconfigurable Metasurface Transceivers as Trainable Physical Layer in an Artificial Neural Network., Advanced Science (Weinheim, Baden Wurttemberg, Germany), vol 7 no. 3 (2020) [10.1002/advs.201901913] [abs].