NEC Laboratories America

Data Science and System Security | Peng Yuan

Peng Yuan

Peng Yuan

Senior Associate Researcher

Data Science and System Security

Projects

AI for Space

Overview: 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.

Publications

Incident Diagnosing and Reporting System based on Retrieval Augmented Large Language Model

The Internet-of-Things (IoT) is widely used in many applications such as smart city, transportation, healthcare, and environment monitoring. A key task of IoT maintenance is to analyze the abnormal sensor records and generate incident report. Traditionally, domain experts engage in such labor intensive

NEC Labs America Attends the 39th Annual AAAI Conference on Artificial Intelligence #AAAI25

Our NEC Lab America team attended the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25), in Philadelphia, Pennsylvania at the Pennsylvania Convention Center from February 25 to March 4, 2025. The purpose of the AAAI conference series was to promote research in AI and foster scientific

Temporal Graph-Based Incident Analysis System for Internet of Things (ECML)

Internet-of-things (IoTs) deploy a massive number of sensors to monitor the system and environment. Anomaly detection on sensor data is an important task for IoT maintenance and operation. In real applications, the occurrence of a system-level incident usually involves hundreds of abnormal sensors, making

Temporal Graph based Incident Analysis System for Internet of Things

Internet-of-things (IoTs) deploy a massive number of sensors to monitor the system and environment. Anomaly detection on sensor data is an important task for IoT maintenance and operation. In real applications, the occurrence of a system-level incident usually involves hundreds of abnormal sensors, making

State-Aware Anomaly Detection for Massive Sensor Data in Internet of Things

With the escalating prevalence of Internet of Things (IoTs) in critical infrastructure, the requirement for efficient and effective anomaly detection solution becomes increasingly important. Unfortunately, most prior research works have largely overlooked to adapt detection criteria for different operational

Explainable Anomaly Detection System for Categorical Sensor Data in Internet of Things

Internet of things (IoT) applications deploy massive number of sensors to monitor the system and environment. Anomaly detection on streaming sensor data is an important task for IoT maintenance and operation. However, there are two major challenges for anomaly detection in real IoT applications: (1)

3D Histogram-Based Anomaly Detection for Categorical Sensor Data in Internet of Things

The applications of Internet-of-things (IoT) deploy a massive number of sensors to monitor the system and environment. Anomaly detection on streaming sensor data is an important task for IoT maintenance and operation. In real IoT applications, many sensors report categorical values rather than numerical