Search Results - aydogan+ozcan

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Deep Learning-Enhanced Dual-Mode Multiplexed Optical Sensor for Point-Of-Care Diagnostics of Cardiovascular Diseases (Case No. 2026-178)

Summary: UCLA researchers in the Departments of Electrical and Computer Engineering and Bioengineering have developed a deep-learning-enhanced multiplexed optical biosensing platform that enables rapid, high sensitivity point-of-care quantification of multiple cardiac biomarkers for cardiovascular diagnostics. Background: Rapid and accessible cardiac...

Published: 3/24/2026 | Inventor(s): Aydogan Ozcan, Dino Di Carlo, Gyeo-Re Han, Artem Goncharov, Merve Eryilmaz

Keywords(s): Biomarker, biomarkers, Cardiovascular, Cardiovascular Disease, cardiovascular diseases, cardiovascular monitoring, cardiovascular therapeutic solution, Deep Learning, Deep learning-based sensing, deep neural networks (DNN), neural network, neural networks, Optics, Point Of Care, point-of-care, point-of-care testing

Category(s): Electrical, Optics & Photonics, Diagnostic Markers, Medical Devices > Cardiac, Medical Devices

Misalignment Resilient Diffractive Optical Networks (Case No. 2020-885)

Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed and experimentally validated a comprehensive training scheme that greatly enhances the robustness of diffractive networks to 3D misalignments and fabrication tolerances in their physical implementation. Background: As an optical machine learning framework,...

Published: 1/28/2026 | Inventor(s): Aydogan Ozcan

Keywords(s): Optical Communication , Optical computing, optical implementation, Optical networks, optical processor

Category(s): Software & Algorithms, Software & Algorithms > Image Processing, Optics & Photonics

Monitoring Structural Health Using Diffractive Optical Processors (Case No. 2025-201)

Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel structural health monitoring system that is highly accurate and cost effective, addressing limitations in current infrastructure and civil health monitoring and a rise in public safety concerns. Background: The need for structural health monitoring...

Published: 12/5/2025 | Inventor(s): Aydogan Ozcan, Ertugrul Taciroglu, Yuntian Wang, Yuhang Li

Keywords(s): 3D structures, Adaptive Optics, AI-generated images and content, all-optical diffractive computing, all-optical transformation, analog computing, analog optical computing, Analogue Electronics, Artifical Intelligence (Machine Learning, Data Mining), Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, artificial-intelligent materials, civil engineering, civil infrastructure, civil monitoring, computational imaging, computational imaging task, Construction, deep diffractive network, Diffraction, diffractive design, diffractive image reconstruction, diffractive network, diffractive processor, diffractive surface, digital image reconstruction, electromagnetic spectrum, Electro-Optics, Image Analysis, Image Processing, Image Resolution, image restoration, image signal processing, Imaging, Infrastructure, Lens (Optics), linear optics, Nanostructure, optical processor, optically-guided structural monitoring, Optics, passive light-matter interactions, security imaging, Signal Reconstruction, Structural health monitoring, structural health monitoring (SHM), structure monitoring, Structures

Category(s): Electrical, Electrical > Signal Processing, Electrical > Imaging, Materials, Materials > Construction Materials, Electrical > Visual Computing, Electrical > Computing Hardware, Electrical > Instrumentation, Energy & Environment, Energy & Environment > Energy Efficiency, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Image Processing, Software & Algorithms > Programs

Design of Task-Specific Optical Systems Using Broadband Diffractive Neural Networks (Case No. 2020-174)

Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a diffractive neural network that can process an all-optical, 3D printed neural network for deep learning applications. Background: Deep learning, a method of machine learning that mimics the human brain’s connectivity through a series of “neural...

Published: 10/17/2025 | Inventor(s): Aydogan Ozcan, Yi Luo, Deniz Mengu, Yair Rivenson

Keywords(s):

Category(s): Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Image Processing

Spectral Kernel Machines With Electrically Tunable Photodetectors (Case No. 2025-105)

Summary: Spectral machine vision traditionally acquires dense 3D hypercubes (x, y, λ) of spatial and spectral information, which must be processed downstream. This imposes major computational burdens, tradeoffs in spatial/spectral resolution, frame rate, and power. The innovation embodied in spectral kernel machines (SKM) is a photodetector...

Published: 10/3/2025 | Inventor(s): Aydogan Ozcan, Yuhang Li, Dehui Zhang, Ali Javey

Keywords(s):

Category(s): Optics & Photonics, Materials, Materials > Nanotechnology, Materials > Functional Materials

Optical Generative Models (Case No. 2025-067)

Summary: Researchers in the UCLA Department of Electrical and Computer Engineering have developed an optics-based system to rapidly generate synthetic images. Background: Generative AI models that create synthetic images, human-like natural language processing capabilities, and even new protein designs are critical for a diverse array of applications....

Published: 11/17/2025 | Inventor(s): Aydogan Ozcan, Shiqi Chen

Keywords(s): Adaptive Optics, all-optical diffractive computing, Electro-Optics, Optical Coherence , Optical computing, Optical Generative Models, Optics

Category(s): Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Image Processing, Optics & Photonics, Electrical, Electrical > Signal Processing, Electrical > Imaging, Electrical > Visual Computing

Lens-Free Wide-Field Super-Resolution Imaging (Case No. 2010-598)

Summary Researchers at UCLA have developed a lens-free, wide-field super-resolution imaging platform that uses a scanned illumination aperture and computational reconstruction to overcome the pixel size limit and achieve high-resolution imaging across large fields of view. The system captures multiple low-resolution holograms under shifted illumination...

Published: 9/24/2025 | Inventor(s): Aydogan Ozcan, Waheb Bishara

Keywords(s):

Category(s): Electrical, Electrical > Instrumentation, Medical Devices, Medical Devices > Medical Imaging, Optics & Photonics, Optics & Photonics > Holography, Optics & Photonics > Microscopy, Optics & Photonics > Spectroscopy

Super-Resolution Image Display Using Diffractive Decoders (Case No. 2022-302)

Summary UCLA researchers in the Department of Electrical and Computer Engineering have developed a super-resolution (SR) image display framework that increases the effective number of useful pixels by 16-fold. This framework combines deep learning-based digital encoding with all-optical decoding to achieve ultra-fast, energy-efficient image super-resolution...

Published: 9/11/2025 | Inventor(s): Aydogan Ozcan, Cagatay Isil, Deniz Mengu

Keywords(s):

Category(s): Electrical, Electrical > Sensors, Electrical > Signal Processing, Electrical > Electronics & Semiconductors

Cascadable All-Optical Nand Gates Using Diffractive Networks (Case No. 2022-107)

Summary UCLA researchers have developed cascadable, all-optical NAND gates built from passive diffractive neural networks, enabling logic operations (e.g. NAND, AND, OR, half-adder) via light propagation and diffraction rather than electronics, potentially lowering latency and power consumption. Background Traditional optical logic gates often rely...

Published: 9/11/2025 | Inventor(s): Aydogan Ozcan, Yi Luo

Keywords(s):

Category(s): Electrical, Electrical > Signal Processing, Electrical > Electronics & Semiconductors

AI-Based Wearable Sensor for Dermatology (Case No. 2025-301)

Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a flexible, cost-effective, AI-enabled wearable sensor that facilitates early, non-invasive diagnosis of allergic contact dermatitis. Background: Allergic contact dermatitis (ACD) is a hypersensitivity reaction of the skin triggered by direct contact...

Published: 3/11/2026 | Inventor(s): Aydogan Ozcan, Shannon Wongvibulson, Paloma Casteleiro Costa, Gyeo-Re Han, Yuzhu Li

Keywords(s): Artificial Intelligence, artificial intelligence augmentation, artificial intelligence/machine learning models, Artificial Neural Network, artificial-intelligent materials, Computer-Aided Diagnosis, deep neural networks (DNN), Dermatology, electrochemical sensors, Medical artificial intelligence (AI), Signal Processing, Signal-To-Noise Ratio, Skin, skin protection, wearable, wearable electronics, wearable medical device, wearable medical devices, wearable sensors, wearable sensors for health

Category(s): Electrical, Electrical > Flexible Electronics, Electrical > Sensors, Medical Devices > Monitoring And Recording Systems, Therapeutics > Dermatology, Diagnostic Markers

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