Projects | Data Science & System Security

DATA SCIENCE & SYSTEM SECURITY

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Time Series Language Model for Explainable AI

We are developing an advanced multi-modal forecasting system that utilizes both time series data and textual data, such as news articles, to predict future trends and events. This innovative system integrates advanced time series backbone models with large language models (LLMs), combining the strengths of statistical analysis and machine learning techniques.

Time Series Sensor Data Analysis

With ubiquitous sensing and networking capability, traditional complex physical systems have been undergoing revolutionary changes in their ICT capabilities. They are now equipped with a large number of sensors distributed across different parts of the system, which collect a tremendous amount of data from system operation.

DDA: Deep Document Analysis

Unstructured data is growing at an unprecedented rate, valuable knowledge, including findings, observations, business demand, opportunities, is widely recorded as texts in documents. We are developing advanced analysis engines for mining text data in documents, aiming to discover valuable knowledge from large-scale documents and provide informed decision-making for users.

Skill Acquisition Learning (SAiL)

This project aims to learn skills by mimicking experts’ behaviors in given tasks. The proposed SAiL engine is trained to perform action prediction tasks from demonstrations by learning a mapping function between observed states and actions. The main challenges in real applications, medical and health care, for example, are that the collection of such experts’ demonstrations is very expensive and It takes a large amount of time and money for expert training.

Complex System Modeling and Optimization

With ubiquitous sensing and networking capability, traditional complex physical systems have been undergoing revolutionary changes in their ICT capabilities. They are now equipped with a large number of sensors distributed across different parts of the system, which collect a tremendous amount of data from system operation.

Safe and Trustworthy AI

By leveraging big data and deep learning, in recent years, AI technologies have made significant progress. They have been adopted in many applications including malware detection, image classification, and stock market prediction. As our society becomes more automated, more and more systems will rely on AI techniques. And instead of augmenting human decisions, some AI systems will make their own decisions and execute autonomously.

Dynamic Graph Analysis

In many big data applications, data with complex structures are connected for their explicit/implicit interactions and are naturally represented as graphs/networks. The world is full of complex and dynamic interactions between diverse objects. The flood of dynamic graph data poses great computational challenges and entails interdisciplinary collaborations.

Multimodal Data Analysis

Multimodal data are prevalent in industrial monitoring, finance and healthcare. In particular, time series are often tagged with text comments from experts that provide layman users with the domain knowledge to understand the charts. Texts give the patterns qualitative meaning while time series makes the words quantitative. Analyzing the relationship between different data types is the key to unraveling the hidden structure of such data.

AIOPs: Evoking Intelligence in Operations

IT operation is one of the technological foundations of the increasingly digitalized world. It is responsible for ensuring that digitalized businesses and societies run reliably, efficiently and safely. With the rapid advances in networking, computers, and hardware, we face an explosive growth of complexity in networked applications and information services. These large-scale, often distributed, information systems usually consist of a great variety of components that work together in a highly complex, coordinated, and evolving manner.

AI for Space

From planetary image analysis to spacecraft monitoring, AI is becoming an increasingly important tool in space exploration and development. Our AI-powered monitoring solution will perform intricate checks to ensure the spacecraft and satellites operate correctly during the production and operation phases.

NEC Laboratories America

Data Science & System Security | Projects

Time Series Language Model for Explainable AI

Time Series Sensor Data Analysis

DDA: Deep Document Analysis

Skill Acquisition Learning (SAiL)

Complex System Modeling and Optimization

Safe and Trustworthy AI

Dynamic Graph Analysis

Multimodal Data Analysis

AIOPs: Evoking Intelligence in Operations

AI for Space