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Aydogan Ozcan
University of California, Los Angeles
Aydogan Ozcan
, Ph.D., is the Chancellor’s Professor and the Volgenau Chair for Engineering Innovation at UCLA and an HHMI Professor with the Howard Hughes Medical Institute. He is also the Associate Director of the California NanoSystems Institute. Ozcan is an elected Fellow of the National Academy of Inventors (NAI), Optica, AAAS, SPIE, IEEE, AIMBE, RSC, APS, and the Guggenheim Foundation. Ozcan is also listed as a Highly Cited Researcher by Web of Science, Clarivate. To commercialize virtual staining technology, Ozcan cofounded Pictor Labs, a spinoff company from his lab at UCLA, where he led the company formation, fundraising, and technology transfer from UCLA.
Webinars
Presented by Aydogan Ozcan
October 2024
Integration of Programmable Diffraction with Digital Neural Networks
Ozcan details the integration of programmable diffraction with digital neural networks. Diffractive optical networks are designed by deep learning to all-optically implement various complex functions...
October 2023
Virtual Staining of Label-Free Tissue using Deep Learning
In this presentation, Ozcan provides an overview of his recent work on using deep neural networks in advancing computational microscopy and sensing systems. He also covers their biomedical...
October 2022
KEYNOTE: Deep Learning-Enabled Computational Microscopy and Diffractive Imaging
Ozcan provides an overview of his recent work on using deep neural networks in advancing computational microscopy and sensing systems. He also covers the systems' biomedical applications, including...
October 2021
Deep Learning-Enabled Computational Microscopy for Biomedical Applications
Deep learning is a class of machine learning techniques that use multilayered artificial neural networks for automated analysis of signals or data. The name comes from the general structure of deep...
January 2021
Toward Intelligent Microscopes: Deep Learning's Potential for Biomedical Applications
Deep learning is a class of machine learning techniques that use multilayered artificial neural networks for automated analysis of signals or data. The name comes from the general structure of deep...
Podcast Episodes
Featuring Aydogan Ozcan
March 2021
Nathalie Picque: From Frequency Combs to Holography — and Everything in Between
Frequency combs have revolutionized time and frequency metrology, making stops along the way to key developments in optical clocks, and, as it turns out, broadband spectroscopy. In a conversation...
February 2021
Dirk Englund: Quantum Photonics: Breakthroughs and Limitations
The latest in quantum computing and quantum optics is our focus, as Dirk Englund from MIT’s Quantum Photonics Laboratory shares his insights on the latest in materials processing, PICS,...
February 2020
Aydogan Ozcan: Democratization of Technology; Hologram or Illusion?
Aydogan Ozcan talks about how his research lab is working to make technology accessible to developing countries. And: how a circus in Germany is replacing its live animals with computer-generated...
Articles
By Aydogan Ozcan
January 2024
Virtual Histology: Democratizing Diagnostic Anatomic Pathology
A virtually stained kidney tissue image showing compact nests and sheets of cells with clear cytoplasm and distinct membrane. Courtesy of the Ozcan Lab/UCLA. Histology is the microscopic...
June 2017
Smartphone Fluorescence Microscopy Allows Cost-Effective Molecular Diagnostics
Lack of diagnostic tools in resource-limited settings remains one of the major obstacles to disease diagnosis and treatment in the developing world. Although significant progress has been made in the...
December 2025
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