VIAVI Solutions Inc.

Innovations in the physical design, materials, fabrication, or packaging of photodetectors and optical sensor elements, including thermoelectric, NIR-compliant, and self-mixing interference types, to improve performance or integration.

Systems and methods that utilize optical fibers as sensing elements or for transmitting sensing signals, often for distributed monitoring of environmental conditions, phase changes, or integrating sensing with communication.

Techniques and apparatus for measuring and verifying the performance, properties, and structural integrity of optical components like lenses, waveguides, and optical fibers. This includes loss, refractive index, and physical defects.

Techniques and hardware architectures for optimizing the radio frequency (RF) front-end, antenna systems, and beamforming strategies in wireless networks to improve signal quality, capacity, and interference mitigation.

Design and configuration of adaptable frame structures, resource block groupings, and subcarrier spacings to optimize data transmission across diverse wireless environments and services, including considerations for fronthaul interfaces.

Techniques and systems designed to monitor network health, diagnose issues, optimize traffic flow, and ensure continuous operation and reduced downtime in complex network environments, including cloud and storage area networks.

Techniques and apparatus utilizing various spectroscopy methods (e.g., Raman, NIRS, photometric, interferometric) for identifying substances, measuring concentrations, or monitoring chemical and physical processes in industrial, environmental, or laboratory settings.

Systems and methods for acquiring and analyzing image data across multiple discrete spectral bands or a continuous spectrum, often for material characterization, environmental monitoring, or remote sensing applications.

Methods for designing, transmitting, and utilizing specific reference signals (e.g., DMRS, SRS, PT-RS) to enable accurate channel estimation, interference measurement, synchronization, or sensing in wireless communication systems.

Development of sophisticated optical lens assemblies and computational methods to achieve high-resolution, precise, or specialized imaging, often for medical or scientific applications.

Methods and systems for accurately determining the absolute or relative position of an object or device, often integrating satellite navigation (GNSS), inertial measurement units (IMU), and local ranging or wireless communication technologies.

Application of machine learning models and algorithms to interpret complex optical sensor data for tasks such as object classification, anomaly detection, health monitoring, or environmental state determination, enhancing automation and decision-making.

Systems that combine data from multiple camera sensors or capture multiple images from different perspectives or qualities, often involving image processing techniques like synthesis to create enhanced or comprehensive views.

The design and manufacturing of integrated circuits that combine optical and electronic components, particularly for high-speed data communication between processors and memory.

Methods and compositions for identifying, quantifying, or characterizing specific biological molecules (e.g., nucleic acids, proteins, metabolites, antibodies) or microbial species, often for diagnostic, prognostic, or quality control applications.

Systems and methods for collecting, processing, and ensuring the quality and consistency of data used for network monitoring, asset management, and operational decision-making, including conflict detection and reliability scoring.

Techniques for combining data from disparate sensor types (e.g., cameras, radar, mobile device signals) to achieve a more robust and comprehensive understanding of an environment or subject, often leveraging machine learning for interpretation and correlation.

Systems and methods for automatically deploying, configuring, and updating network devices and services, including software updates, client onboarding, and topology management across various network types.

Utilizing specialized hardware components such as network processing units (NPUs) or dedicated acceleration circuits to offload and speed up network packet processing, traffic generation, or time-sensitive network operations.

Innovations in the physical components and architectures of radar, lidar, and sonar systems, including antenna design, RF signal generation, beam steering mechanisms, and optical elements for improved performance.

Techniques and circuits designed to detect, estimate, and mitigate various physical layer signal impairments such as frequency spurs, phase noise, or non-linear distortions, thereby improving overall signal quality and system performance.

Systems that employ imaging and image processing to automatically detect defects, verify states, or ensure quality control in manufactured goods, printed materials, or industrial processes.

Utilizing machine learning, particularly deep learning, to analyze medical data such as images, sensor readings, or physiological signals for disease prediction, diagnosis, or treatment assessment.

Use of thermal and infrared sensors for non-contact temperature measurement, occupancy detection, structural health monitoring, fire/hazard detection, and process control in diverse industrial, environmental, and security applications.

Technologies for transmitting critical alerts and information during emergencies, often involving wireless networks, specialized devices, and protocols to ensure timely and targeted communication to users or emergency services.

Mobile applications and systems leveraging wireless communication and location data (e.g., GPS, RFID, geo-fencing) to provide context-specific services, transactions, or user interactions.

Methods and apparatus for improving the visual fidelity, resolution, or compression efficiency of video signals, often through advanced processing, up-scaling, or neural network-based filters.

Specialized hardware, architectural designs, and computational methods to improve the speed, efficiency, and security of artificial intelligence and machine learning model execution, particularly for inference and data processing.

Techniques and systems for reducing energy consumption in computer networks while maintaining or improving performance, often involving predictive modeling, simulation, and dynamic adjustments to network infrastructure.