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
- Office Location: Fitzpatrick Center (Ciemas) Ro, 101 Science Drive, Durham, NC 27701
- Office Phone: (650) 686-1368
- Email Address: email@example.com
- B.S. Duke University, 2006
- Ph.D. California Institute of Technology, 2016
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.
- BME 493: Projects in Biomedical Engineering (GE)
- BME 494: Projects in Biomedical Engineering (GE)
- BME 548L: Machine Learning and Imaging (GE, IM)
- BME 789: Internship in Biomedical Engineering
- BME 791: Graduate Independent Study
- BME 792: Continuation of Graduate Independent Study
- EGR 101L: Engineering Design and Communication
- EGR 393: Research Projects in Engineering
In the News
- Invented at Duke Connects University's Research, Innovation and Entrepreneurship Communities (Dec 14, 2022 | Duke Translation & Commercialization)
- A Microscope That Teaches Itself to Know the Best Settings for Diagnostic Images for Malaria (Nov 20, 2019 | Pratt School of Engineering)
- Kreiss, L., S. Jiang, X. Li, S. Xu, K. C. Zhou, K. C. Lee, A. Mühlberg, et al. “Digital staining in optical microscopy using deep learning - a review (Accepted).” PhotoniX 4, no. 1 (December 1, 2023). https://doi.org/10.1186/s43074-023-00113-4.
- Mühlberg, Alexander, Paul Ritter, Simon Langer, Chloë Goossens, Stefanie Nübler, Dominik Schneidereit, Oliver Taubmann, et al. “SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for Prior-Informed Assessment of Muscle Function and Pathology.” Advanced Science (Weinheim, Baden-Wurttemberg, Germany) 10, no. 28 (October 2023): e2206319. https://doi.org/10.1002/advs.202206319.
- Wu, Melissa M., Roarke Horstmeyer, and Stefan A. Carp. “scatterBrains: an open database of human head models and companion optode locations for realistic Monte Carlo photon simulations.” Journal of Biomedical Optics 28, no. 10 (October 2023): 100501. https://doi.org/10.1117/1.jbo.28.10.100501.
- Bian, Liheng, Haoze Song, Lintao Peng, Xuyang Chang, Xi Yang, Roarke Horstmeyer, Lin Ye, et al. “High-resolution single-photon imaging with physics-informed deep learning.” Nature Communications 14, no. 1 (September 2023): 5902. https://doi.org/10.1038/s41467-023-41597-9.
- Harfouche, M., K. Kim, K. C. Zhou, P. C. Konda, S. Sharma, E. E. Thomson, C. Cooke, et al. “Imaging across multiple spatial scales with the multi-camera array microscope.” Optica 10, no. 4 (April 1, 2023): 471–80. https://doi.org/10.1364/OPTICA.478010.