Jason Paul Chang

Title: Jason Paul Chang: Innovator in Deep Learning for Online User Activity Detection

Introduction

Jason Paul Chang is an accomplished inventor based in San Mateo, CA. He has made significant contributions to the field of deep learning, particularly in detecting abusive user activity in online networks. His innovative approach leverages advanced algorithms to enhance user safety in digital environments.

Latest Patents

Chang holds a patent for a groundbreaking invention titled "Deep learning using activity graph to detect abusive user activity in online networks." This patent introduces a deep learning algorithm that operates on a transition matrix formed from user activities. The transition matrix records the frequencies of transitions between various paths of user activity, allowing for a comprehensive analysis of user behavior.

Career Highlights

Currently, Jason Paul Chang is employed at Microsoft Technology Licensing, LLC, where he continues to develop and refine his innovative ideas. His work focuses on enhancing the security and integrity of online networks through advanced technological solutions.

Collaborations

Chang collaborates with talented individuals such as Yi Wu and Mariem Boujelbene, contributing to a dynamic and innovative work environment.

Conclusion

Jason Paul Chang's contributions to deep learning and user activity detection represent a significant advancement in online safety technology. His innovative patent and ongoing work at Microsoft Technology Licensing, LLC, highlight his commitment to improving digital user experiences.