Asterios Stergioudis

Title: Asterios Stergioudis: Innovator in Anomaly Detection and Model Processing

Introduction

Asterios Stergioudis is a notable inventor based in Salonika, Greece. He has made significant contributions to the fields of model processing and anomaly detection, holding a total of 3 patents. His work focuses on developing methods that enhance data processing and analysis, which are crucial in various technological applications.

Latest Patents

One of Asterios's latest patents is titled "Local model processing and remote verification." This method involves receiving first data from a device, which is based on the output of a model processed by that device. The system further processes second data to produce a second output and determines third data that is consistent with the first data. This innovative approach aims to improve the reliability of model outputs in computing systems.

Another significant patent is "Root cause analysis in multivariate unsupervised anomaly detection." This invention provides systems and methods for detecting anomalies and conducting root cause analysis. The root cause analyzer utilizes a classification model trained on data samples and their corresponding anomaly labels. It determines the contributions of anomalous features in data samples, enabling devices to take appropriate actions based on predictions of anomalies.

Career Highlights

Asterios has worked with prominent companies, including Citrix Systems, Inc. His experience in these organizations has allowed him to refine his skills and contribute to cutting-edge technological advancements.

Collaborations

Throughout his career, Asterios has collaborated with talented individuals such as Aikaterini Kalou and Daniel George Wing. These partnerships have fostered innovation and enhanced the development of his projects.

Conclusion

Asterios Stergioudis is a distinguished inventor whose work in model processing and anomaly detection has made a significant impact in the tech industry. His patents reflect a commitment to advancing technology and improving data analysis methods.