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: firstname.lastname@example.org
- Ph.D. California Institute of Technology, 2016
- B.S. Duke University, 2006
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 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)
- Gigan, S; Katz, O; De Aguiar, HB; Andresen, ER; Aubry, A; Bertolotti, J; Bossy, E; Bouchet, D; Brake, J; Brasselet, S; Bromberg, Y; Cao, H; Chaigne, T; Cheng, Z; Choi, W; Čižmár, T; Cui, M; Curtis, VR; Defienne, H; Hofer, M; Horisaki, R; Horstmeyer, R; Ji, N; LaViolette, AK; Mertz, J; Moser, C; Mosk, AP; Pégard, NC; Piestun, R; Popoff, S; Phillips, DB; Psaltis, D; Rahmani, B; Rigneault, H; Rotter, S; Tian, L; Vellekoop, IM; Waller, L; Wang, L; Weber, T; Xiao, S; Xu, C; Yamilov, A; Yang, C; Yılmaz, H, Roadmap on wavefront shaping and deep imaging in complex media, Jphys Photonics, vol 4 no. 4 (2022) [10.1088/2515-7647/ac76f9] [abs].
- Xu, S; Yang, X; Liu, W; Jönsson, J; Qian, R; Konda, PC; Zhou, KC; Kreiß, L; Wang, H; Dai, Q; Berrocal, E; Horstmeyer, R, Imaging Dynamics Beneath Turbid Media via Parallelized Single-Photon Detection., Advanced Science (Weinheim, Baden Wurttemberg, Germany), vol 9 no. 24 (2022) [10.1002/advs.202201885] [abs].
- Ayaz, H; Baker, WB; Blaney, G; Boas, DA; Bortfeld, H; Brady, K; Brake, J; Brigadoi, S; Buckley, EM; Carp, SA; Cooper, RJ; Cowdrick, KR; Culver, JP; Dan, I; Dehghani, H; Devor, A; Durduran, T; Eggebrecht, AT; Emberson, LL; Fang, Q; Fantini, S; Franceschini, MA; Fischer, JB; Gervain, J; Hirsch, J; Hong, K-S; Horstmeyer, R; Kainerstorfer, JM; Ko, TS; Licht, DJ; Liebert, A; Luke, R; Lynch, JM; Mesquida, J; Mesquita, RC; Naseer, N; Novi, SL; Orihuela-Espina, F; O'Sullivan, TD; Peterka, DS; Pifferi, A; Pollonini, L; Sassaroli, A; Sato, JR; Scholkmann, F; Spinelli, L; Srinivasan, VJ; St Lawrence, K; Tachtsidis, I; Tong, Y; Torricelli, A; Urner, T; Wabnitz, H; Wolf, M; Wolf, U; Xu, S; Yang, C; Yodh, AG; Yücel, MA; Zhou, W, Optical imaging and spectroscopy for the study of the human brain: status report., Neurophotonics, vol 9 no. Suppl 2 (2022) [10.1117/1.nph.9.s2.s24001] [abs].
- Dai, X; Xu, S; Yang, X; Zhou, KC; Glass, C; Konda, PC; Horstmeyer, R, Quantitative Jones matrix imaging using vectorial Fourier ptychography., Biomedical Optics Express, vol 13 no. 3 (2022), pp. 1457-1470 [10.1364/BOE.448804] [abs].
- Glass, C; Lafata, KJ; Jeck, W; Horstmeyer, R; Cooke, C; Everitt, J; Glass, M; Dov, D; Seidman, MA, The Role of Machine Learning in Cardiovascular Pathology., Can J Cardiol, vol 38 no. 2 (2022), pp. 234-245 [10.1016/j.cjca.2021.11.008] [abs].