Aydogan Ozcan
Professor
Develops deep-learning-enabled computational microscopy and diffractive optical networks for optical computing and mobile health sensing.
Aydogan Ozcan's lab at UCLA works on medical imaging & healthcare AI and medical image analysis. 105 papers since 2023, 19 at top venues, mostly Nature Communications and Nature. Applications close .
At a glance
- papers, 2023–2026
- 27/ year
- at T1 venues
- 18%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 22 papers2026 · T1 1 · collecting
- 23 papers2025 · T1 7
- 34 papers2024 · T1 7
- 26 papers2023 · T1 4
T1 venuesOtherVenues: Nature Communications, Nature, Nature Machine Intelligence, Nature Methods, npj Digital Medicine
Research focuspaper titles that use each topic's words
- optical32 papers
- Medical imaging & healthcare AI23 papers
- Medical image analysis11 papers
- microscopy6 papers
- optical computing2 papers
Paper list
From the lab homepage.
202622 papers
- ” Science Advances (AAAS) DOI: 10.1126/sciadv.aea1712“Structural Vibration Monitoring with Diffractive Optical Processors (opens in a new tab)
- AAASAutomated HER2 scoring with uncertainty quantification using lensfree holography and deep learning (opens in a new tab)
- Scientific ReportsAutonomous labeling of surgical resection margins using a foundation model (opens in a new tab)
- ACS NanoAutonomous Uncertainty Quantification for Computational Point-of-Care Sensors (opens in a new tab)
- AAASDeep learning-enabled virtual multiplexed immunostaining of label-free tissue for vascular invasion assessment (opens in a new tab)
- Light: Science & ApplicationsDeep learning-enhanced dual-mode multiplexed optical sensor for point-of-care diagnostics of cardiovascular diseases (opens in a new tab)
- Light: Science & ApplicationsDetection and imaging of chemicals and hidden explosives using terahertz time-domain spectroscopy and deep learning (opens in a new tab)
- Laser & Photonics ReviewsInterleaved diffractive networks for information transfer through random diffusers (opens in a new tab)
- Nature Communications (T1)Lying mirror using structured surfaces (opens in a new tab)
- AAASML-automated microfluidic circuit design (opens in a new tab)
- Light: Science & ApplicationsModel-free Optical Processors using In Situ Reinforcement Learning with Proximal Policy Optimization (opens in a new tab)
- Journal of Biomedical OpticsOptical digital twins for disease prevention, diagnosis, therapy, and intervention (opens in a new tab)
202523 papers
- Nature Biomedical EngineeringA robust and scalable framework for hallucination detection in virtual tissue staining and digital pathology (opens in a new tab)
- npj Digital MedicineBlurryScope enables compact, cost-effective scanning microscopy for HER2 scoring using deep learning on blurry images (opens in a new tab)
- Light: Science & ApplicationsBroadband unidirectional visible imaging using wafer-scale nano-fabrication of multi-layer diffractive optical processors (opens in a new tab)
- Gut MicrobesDeep Learning-based Detection of Bacterial Swarm Motion Using a Single Image (opens in a new tab)
- SmallDeep Learning-Enhanced Chemiluminescence Vertical Flow Assay for High-Sensitivity Cardiac Troponin I Testing (opens in a new tab)
- Nature PhotonicsEmergent Photonics for Cardiovascular Health (opens in a new tab)
- Environment InternationalFine particulate matter emissions from electric vehicle fast charging stations (opens in a new tab)
- AAASLabel-Free Evaluation of Lung and Heart Transplant Biopsies Using Tissue Autofluorescence-Based Virtual Staining (opens in a new tab)
- Nature Communications (T1)Machine learning in point-of-care testing: innovations, challenges, and opportunities (opens in a new tab)
- eLightMassively parallel and universal approximation of nonlinear functions using diffractive processors (opens in a new tab)
- Nature (T1)Optical generative models (opens in a new tab)
- Nature Communications (T1)Optimizing Structured Surfaces for Diffractive Waveguides (opens in a new tab)
202434 papers
- Gout, Urate, and Crystal Deposition DiseaseA novel polarized light microscope for examination of birefringent crystals in synovial fluid (opens in a new tab)
- ACS NanoA paper-based multiplexed serological test to monitor immunity against SARS-CoV-2 using machine learning (opens in a new tab)
- Trends in Analytical ChemistryAdvances in point-of-care optical biosensing for underserved populations (opens in a new tab)
- Light: Science & ApplicationsAll-optical complex field imaging using diffractive processors (opens in a new tab)
- Light: Science & ApplicationsAll-optical image denoising using a diffractive visual processor (opens in a new tab)
- Nature Communications (T1)All-optical phase conjugation using diffractive wavefront processing (opens in a new tab)
- ACS NanoAn insertable glucose sensor using a compact and cost-effective phosphorescence lifetime imager and machine learning (opens in a new tab)
- BME FrontiersAutomated HER2 Scoring in Breast Cancer Images Using Deep Learning and Pyramid Sampling (opens in a new tab)
- Nature Communications (T1)Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array (opens in a new tab)
- Advanced Photonics NexusComplex-valued universal linear transformations and image encryption using spatially incoherent diffractive networks (opens in a new tab)
- ACS NanoDeep Learning-based Kinetic Analysis in Paper-based Analytical Cartridges Integrated with Field-effect Transistors (opens in a new tab)
- ACS NanoDeep learning-enhanced paper-based vertical flow assay for high-sensitivity troponin detection using nanoparticle amplification (opens in a new tab)
202326 papers
- Light: Science & ApplicationsAll-optical image classification through unknown random diffusers using a single-pixel diffractive network (opens in a new tab)
- ACS NanoAmphiphilic particle-stabilized nanoliter droplet reactors with a multi-modal portable reader for distributive biomarker quantification (opens in a new tab)
- Nature Methods (T1)Artificial intelligence-enabled Quantitative Phase Imaging Methods for Life Sciences (opens in a new tab)
- AAASCycle Consistency-based Uncertainty Quantification of Neural Networks in Inverse Imaging Problems (opens in a new tab)
- Advanced MaterialsData class-specific all-optical transformations and encryption (opens in a new tab)
- SmallDeep learning-enabled multiplexed point-of-care sensor using a paper-based fluorescence vertical flow assay (opens in a new tab)
- Light: Science & ApplicationsDeep Learning-enabled Virtual Histological Staining of Biological Samples (opens in a new tab)
- Frontiers in BioinformaticsDigital Staining Facilitates Biomedical Microscopy (opens in a new tab)
- IEEE Journal of Selected Topics in Quantum ElectronicseFIN: Enhanced Fourier Imager Network for Generalizable Autofocusing and Pixel Super-Resolution in Holographic Imaging (opens in a new tab)
- Light: Science & ApplicationsHigh-throughput terahertz imaging: progress and challenges (opens in a new tab)
- Opto-Electronic AdvancesIn-flow holographic tomography boosts lipid droplet quantification (opens in a new tab)
- Nature Reviews BioengineeringLateral flow test engineering and lessons learned from COVID-19 (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UCLAFall 2027
Computer Science PhD
- Round
- Single round (Dec 15)
- Opens
- —
- GRE
- optional
- English
- See program page
- Fee
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Not yet confirmed for this intake.
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