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
  • 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

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 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 101L: Engineering Design and Communication
  • EGR 393: Research Projects in Engineering

In the News

Representative Publications

  • Gigan, S., O. Katz, H. B. De Aguiar, E. R. Andresen, A. Aubry, J. Bertolotti, E. Bossy, et al. “Roadmap on wavefront shaping and deep imaging in complex media.” Jphys Photonics 4, no. 4 (October 1, 2022). https://doi.org/10.1088/2515-7647/ac76f9.
  • Xu, Shiqi, Xi Yang, Wenhui Liu, Joakim Jönsson, Ruobing Qian, Pavan Chandra Konda, Kevin C. Zhou, et al. “Imaging Dynamics Beneath Turbid Media via Parallelized Single-Photon Detection.” Advanced Science (Weinheim, Baden Wurttemberg, Germany) 9, no. 24 (August 2022): e2201885. https://doi.org/10.1002/advs.202201885.
  • Ayaz, Hasan, Wesley B. Baker, Giles Blaney, David A. Boas, Heather Bortfeld, Kenneth Brady, Joshua Brake, et al. “Optical imaging and spectroscopy for the study of the human brain: status report.” Neurophotonics 9, no. Suppl 2 (August 2022): S24001. https://doi.org/10.1117/1.nph.9.s2.s24001.
  • Dai, Xiang, Shiqi Xu, Xi Yang, Kevin C. Zhou, Carolyn Glass, Pavan Chandra Konda, and Roarke Horstmeyer. “Quantitative Jones matrix imaging using vectorial Fourier ptychography.” Biomed Opt Express 13, no. 3 (March 1, 2022): 1457–70. https://doi.org/10.1364/BOE.448804.
  • Glass, Carolyn, Kyle J. Lafata, William Jeck, Roarke Horstmeyer, Colin Cooke, Jeffrey Everitt, Matthew Glass, David Dov, and Michael A. Seidman. “The Role of Machine Learning in Cardiovascular Pathology.” Can J Cardiol 38, no. 2 (February 2022): 234–45. https://doi.org/10.1016/j.cjca.2021.11.008.