NEC Laboratories Europe GmbH

Methods and systems for identifying, extracting, and structuring specific entities, relationships, or insights from text-based documents, often involving techniques like named entity recognition, relation extraction, or summarization.

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.

Applying artificial intelligence and machine learning techniques to enhance cryptographic systems, such as generating encryption models, improving zero-trust architectures, or enabling privacy-preserving computations like federated learning.

Systems and methods utilizing artificial intelligence, particularly large language models and neural networks, to extract, summarize, generate, or categorize information from unstructured or semi-structured data sources.

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.

Systems that process data to provide personalized recommendations, predict events, or automate decision-making processes based on learned patterns, user behavior, or environmental factors.

Applying computational methods, often involving machine learning and multiomics data, to design, analyze, and understand biomolecules, genetic sequences, or complex biological systems.

Focuses on using distributed ledger technology (DLT) like blockchain to secure financial transactions, manage digital identities, or ensure data integrity and traceability across various applications.

Utilizing dedicated hardware components, secure enclaves, or trusted execution environments to perform cryptographic operations, enhancing security, performance, or isolation from software vulnerabilities.

Systems that use user data, preferences, and machine learning to generate tailored advice, product recommendations, goal-setting plans, or contextual information for individuals across different domains.

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.

Computational methods and systems for analyzing biological data (e.g., genomic, proteomic, clinical) to diagnose diseases, predict patient prognosis, assess treatment response, or stratify patients for therapy.

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.

Techniques for protecting data at rest or in backup, ensuring its integrity, confidentiality, and verifiable origin, often involving encryption, unique identifiers, or secure repositories.

Technologies for securing, managing, and transacting with virtual currencies, non-fungible tokens (NFTs), and other blockchain-based digital assets, including hardware wallets and tokenization schemes for various purposes.

Techniques for combining and analyzing information from multiple distinct data modalities (e.g., text, image, video, audio, sensor data) to derive richer insights or improve system performance and decision-making.

Technologies enabling the creation and management of virtual computing environments, including virtual machines and virtual desktops, with an emphasis on secure and efficient remote access, updates, and performance.

Systems and methods for encrypting data at a fine-grained level (e.g., per data unit or based on sensitivity) and controlling access to it, often involving delegated authorization, contextual policies, or secure data sharing.

Methods and systems for combining and analyzing diverse biological datasets (e.g., genomics, transcriptomics, proteomics, metabolomics) to uncover complex biological relationships, disease mechanisms, or temporal trajectories.

Methods and systems for integrating, transforming, and managing complex or domain-specific data from disparate sources into a unified structure, often for specific applications like social networks, genomics, or business forms.

Computational techniques and algorithms for processing, aligning, and interpreting raw biological sequence data (DNA, RNA, protein), including identifying genetic variations, classifying organisms, or predicting sequence attributes.

Methods for training machine learning models across multiple decentralized devices or servers while keeping data localized, often involving aggregation of model parameters and secure communication.

Mechanisms to facilitate the secure exchange of data between different entities or systems while enforcing usage policies, managing digital content rights, and ensuring data consistency during replication or transfer.

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.

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.

Methods and frameworks for systematically verifying the correctness, performance, and security of software systems, including infrastructure as code, virtual workloads, APIs, and identifying potential vulnerabilities or inconsistencies.

Techniques for generating human-like text or other content using large pre-trained models, often involving prompt engineering, speculative decoding, or multi-modal inputs for content creation.

Techniques for improving the performance, efficiency, or practicality of fully homomorphic encryption (FHE) schemes, often involving hardware accelerators or optimized algorithms for operations like bootstrapping and key-switching.

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 systems for generating, distributing, updating, rotating, and securely destroying cryptographic keys to maintain data confidentiality and integrity over time, including quantum key distribution.

Systems and methods for non-invasive or minimally invasive collection and analysis of physiological data (e.g., blood pressure, electrolytes, genetic markers, B cell repertoire) to assess patient health status, screen for conditions, or aid in diagnosis.

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.

Systems and methods for automating the lifecycle of machine learning models, including pipeline deployment, model management, versioning, and configuring for different inference environments.

Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or data processing.

Systems designed to streamline and automate various commercial transactions, including mobile-enhanced processes, secure online checkouts, customer service interactions, and privilege issuance, often leveraging digital authentication.

Systems and methods for securely and reliably delivering, installing, and managing software or firmware updates to distributed or embedded devices, often considering network conditions, resource constraints, or storage repartitioning.