Chia-Peng Lee

Title: Innovations by Inventor Chia-Peng Lee

Introduction

Chia-Peng Lee is a notable inventor based in Taipei, Taiwan. He has made significant contributions to the field of technology, particularly in the areas of driving anomaly detection and network flow recognition. With a total of 6 patents to his name, Lee's work reflects a commitment to advancing technological solutions.

Latest Patents

One of his latest patents is a "Method and system for detecting driving anomalies." This invention involves processing raw data from a car's On-Board Diagnostics to generate time-series data. Using this data, an automatic driving behavior separating technology identifies various driving behaviors. An artificial intelligence model is then built to detect anomalies without the need for labeled data, ultimately issuing alarms for identified driving anomalies.

Another significant patent is the "Anomaly flow detection device and anomaly flow detection method." This device retrieves training data transmitted between a monitored network and an external network. It preprocesses packet headers to create training feature vectors and constructs a flow recognition model using unsupervised learning. The model is then used to identify whether the testing data is normal or abnormal, determining if the monitored network's flow is abnormal based on the recognition results.

Career Highlights

Chia-Peng Lee has worked with prestigious institutions such as National Taiwan University and the Industrial Technology Research Institute. His experience in these organizations has allowed him to develop and refine his innovative ideas, contributing to advancements in technology.

Collaborations

Some of his notable coworkers include Phone Lin and En-Hau Yeh. Their collaboration has likely fostered an environment of innovation and creativity, leading to the development of impactful technologies.

Conclusion

Chia-Peng Lee's contributions to technology through his patents and collaborations highlight his role as an influential inventor. His work in driving anomaly detection and network flow recognition showcases the potential for innovation in addressing real-world challenges.