Ozcan Research Lab
  • NEWS
  • PEOPLE
  • RESEARCH
  • PUBLICATIONS
  • UNDERGRADUATE RESEARCH
Select Page
Cascadable all-optical NAND gates using diffractive networks

Cascadable all-optical NAND gates using diffractive networks

Oct 28, 2022

Y. Luo, D. Mengu and A. Ozcan, “Cascadable all-optical NAND gates using diffractive networks” Scientific Reports (2022) DOI: 10.1038/s41598-022-11331-4
Classification and reconstruction of spatially overlapping phase images using diffractive optical networks

Classification and reconstruction of spatially overlapping phase images using diffractive optical networks

Oct 28, 2022

D. Mengu, M. Veli, Y. Rivenson and A. Ozcan, “Classification and reconstruction of spatially overlapping phase images using diffractive optical networks” Scientific Reports (2022) DOI: 10.1038/s41598-022-12020-y
At the intersection of optics and deep learning: statistical inference, computing, and inverse design

At the intersection of optics and deep learning: statistical inference, computing, and inverse design

Oct 28, 2022

D. Mengu, S.S. Rahman, Y. Luo, J. Li and A. Ozcan, “At the intersection of optics and deep learning: statistical inference, computing, and inverse design” Advances in Optics and Photonics (2022) DOI: 10.1364/AOP.450345– PDF
All-optical phase recovery: diffractive computing for quantitative phase imaging

All-optical phase recovery: diffractive computing for quantitative phase imaging

Oct 28, 2022

D. Mengu and A. Ozcan, “All-optical phase recovery: diffractive computing for quantitative phase imaging” Advanced Optical Materials (2022) DOI: 10.1002/adom.202200281– PDF
Polarization Multiplexed Diffractive Computing: All-Optical Implementation of a Group of Linear Transformations Through a Polarization-Encoded Diffractive Network

Polarization Multiplexed Diffractive Computing: All-Optical Implementation of a Group of Linear Transformations Through a Polarization-Encoded Diffractive Network

Oct 28, 2022

J. Li, Y. Hung, O. Kulce, D. Mengu and A. Ozcan, “Polarization Multiplexed Diffractive Computing: All-Optical Implementation of a Group of Linear Transformations Through a Polarization-Encoded Diffractive Network,” Light: Science & Applications (Nature Publishing...
Few-shot Transfer Learning for Holographic Image Reconstruction using a Recurrent Neural Network

Few-shot Transfer Learning for Holographic Image Reconstruction using a Recurrent Neural Network

Oct 28, 2022

L. Huang, X. Yang, T. Liu, and A. Ozcan, “Few-shot Transfer Learning for Holographic Image Reconstruction using a Recurrent Neural Network” APL Photonics (2022) DOI: 10.1063/5.0090582
« Older Entries
Next Entries »

Recent Posts

  • To image, or not to image: Class-specific diffractive cameras with all-optical erasure of undesired objects
  • Mobility of polypropylene microplastics in stormwater biofilters under freeze-thaw cycles
  • Computational Imaging Without a Computer: Seeing Through Random Diffusers at the Speed of Light
  • Characterization of exhaled e-cigarette aerosols in a vape shop using a field-portable holographic on-chip microscope
  • Sub-picomolar lateral flow antigen detection with two-wavelength imaging of composite nanoparticles

Archives

  • November 2022
  • October 2022

Categories

  • Press Releases
  • Research Papers
  • Uncategorized

Engineer Change.

UCLA Samueli School of Engineering
Department of Electrical and Computer Engineering
Los Angeles, CA 90095

Contact

Aydogan Ozcan
Phone: (310) 825-0915
Email: ozcan@ucla.edu
Publications
HHMI Program
CV
Undergrad Research
BioGames
ECE Department
  • Facebook
  • X
  • Instagram
© 2020 UCLA Samueli School Of Engineering